To see the other types of publications on this topic, follow the link: Physiological biometrics.
Journal articles on the topic 'Physiological biometrics'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Physiological biometrics.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Sable, Harsh, and Divya Bajpai Tripathy. "A Review on Comparative Analysis on Different Sort of Physiological and Behavioral Biometric Framework." International Journal of Advance Research and Innovation 9, no. 2 (2021): 1–9. http://dx.doi.org/10.51976/ijari.922101.
Full textAbstract:
Biometrics as the investigation of seeing an individual ward on their physical or conduct characteristics, biometric have now been conveyed in diverse business, ordinary resident and national security applications. Customarily the usage of biometrics devices has improved our capacity to give approved entry to material foundations. Biometric is the usage of a person's novel physiological, lead, and morphological trademark to give valuable person distinguishing proof. Biometric structures that are starting at now available today break down fingerprints, engravings, iris and retina models, and face. Mechanisms that are similar to biometrics anyway are not named such are lead systems, for instance, voice, imprint and keystroke mechanisms. These days biometrics is in effect effectively executed in numerous fields like measurable, security, recognizable proof and approval frameworks.
2
Rajvanshi, Saumya, Shiv Chauhan, and Savneet Kaur. "A New Wave in Biometric System: Systematic Study." CGC International Journal of Contemporary Technology and Research 4, no. 2 (2022): 300–305. http://dx.doi.org/10.46860/cgcijctr.2022.07.31.300.
Full textAbstract:
Biometric system is a technique used to identify a person using its personal identification methods. The main concept of biometric systems is to provide confidentiality and security to the user. A number of biometric systems are introduced but some systems are widely used and are famous because of their usage and security they provide. Physiological and Behavioral biometrics are the two types of biometric systems. Biometric systems include physiological biometrics like face recognition, fingerprint recognition, iris recognition and behavioral biometrics like signature recognition and voice recognition. All these recognition systems are discussed in this research paper. Biometric systems work on three levels: Enrollment, Verification, and Identification. Enrollment is the process in which patterns are captured from the user and stored in the database. Verification means to confirm that the sample entered by the user belongs to him or not. When the user wants to access the data then the user must use his/her biometrics so that the system checks that the person who wants to access the data is the real owner of the data or not. This process is identification. All three levels are the working levels of the Biometric System. In earlier years, biometrics were used only at ground levels to provide basic security to data but now the tables have turned. It is playing a major role in providing security to our data. Biometrics are not only used in day-to-day life in phone unlocking, phone assistants, attendance systems but also used at advanced levels like in airports, border security, cloud computing etc. In this research paper, we will discuss the future scope of biometric systems and how it could even change the future.
3
Shopon, Md, Sanjida Nasreen Tumpa, Yajurv Bhatia, K. N. Pavan Kumar, and Marina L. Gavrilova. "Biometric Systems De-Identification: Current Advancements and Future Directions." Journal of Cybersecurity and Privacy 1, no. 3 (2021): 470–95. http://dx.doi.org/10.3390/jcp1030024.
Full textAbstract:
Biometric de-identification is an emerging topic of research within the information security domain that integrates privacy considerations with biometric system development. A comprehensive overview of research in the context of authentication applications spanning physiological, behavioral, and social-behavioral biometric systems and their privacy considerations is discussed. Three categories of biometric de-identification are introduced, namely complete de-identification, auxiliary biometric preserving de-identification, and traditional biometric preserving de-identification. An overview of biometric de-identification in emerging domains such as sensor-based biometrics, social behavioral biometrics, psychological user profile identification, and aesthetic-based biometrics is presented. The article concludes with open questions and provides a rich avenue for subsequent explorations of biometric de-identification in the context of information privacy.
4
Hina Ali and Saba Shaikh. "Comprehensive Review on Different Types of Biometrics and the Impact of Pandemic on Biometric Security." International Journal of Information Systems and Computer Technologies 3, no. 2 (2024): 70–79. http://dx.doi.org/10.58325/ijisct.003.02.0074.
Full textAbstract:
With the rapid rise of electronic crimes and their related difficulties, implementing a trustworthy user authentication system has become a critical responsibility for access control and data security. Because of this, the influence of biometrics in information security has become very popular. Everybody in this world has distinct physiological and behavioural features that set us apart from others. These unique features (or IDs) are used in biometrics to determine and authenticate people's identities. This research includes comparisons between two major categories of biometrics, namely physiological and behavioural biometrics, that include finger prints, varied iris patterns, blood vessels, eye retina, vocal inflections in speech, signatures, key strokes, walking, and hand shape and geometry, all of which are unique identifiers. This research also includes the impact of COVID-19 on biometric security.
5
Thakor, Kiran B. "Comparative Analysis of Vein Biometrics Methodologies: A Comprehensive Review." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 5365–73. http://dx.doi.org/10.22214/ijraset.2023.52830.
Full textAbstract:
Abstract: Vein biometrics has emerged as a promising modality for secure and reliable personal identification. With its unique characteristics and inherent physiological properties, veins offer distinct advantages over other biometric modalities. However, the methodology employed in vein biometrics plays a crucial role in determining its performance and accuracy. This paper presents a comprehensive comparison of various methodologies used in vein biometrics, aiming to provide insights into the strengths, weaknesses, and advancements in this field.
6
Gupta, Ms Neha. "A New Wave in Biometric System: Systematic Study incorporated with Artificial Intelligence." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem33563.
Full textAbstract:
Biometric system is a technique used to identify a person using its personal identification methods. The main concept of biometric systems is to provide confidentiality and security to the user. A number of biometric systems are introduced but some systems are widely used and are famous because of their usage and security they provide. Physiological and Behavioral biometrics are the two types of biometric systems. Biometric systems include physiological biometric like face recognition, finger print recognition, ir is recognition and behavioral biometrics like signature recognition and voice recognition. All these recognition systems are discussed in this research paper. Biometric systems work on three levels: Enrollment, Verification, and Identification. Enrollment is the process in which patterns are captured from the user and stored in the database. Verification means to confirm that the sample entered by the user belongs to him or not. When the user wants to access the data then the user must use his/her biometrics that the systematic hacks that the person who wants to access the data is the real owner of the data or not. This process is identification. All three levels are the working levels of the Biometric System. In earlier years, biometrics was used only at ground levels to provide basic security to data but now the tables have turned. It is playing a major role in providing security to our data. Biometrics are not only used in day-to-day life in phone unlocking, phone assistants, attendance systems but also used at advanced levels like in airports, border security, cloud computing etc. In this research paper, we will discuss the future scope of biometric systems and how it could even change the future.
7
K. P. Ajitha, Gladis, and D. Sharmila. "Systematic digital signal processing approach in various biometric identification." i-manager's Journal on Digital Signal Processing 10, no. 2 (2022): 7. http://dx.doi.org/10.26634/jdp.10.2.19290.
Full textAbstract:
Biometrics are unique physical characteristics, such as fingerprints, that can be used for automatic recognition. Biometric identifiers are often classified as physiological characteristics associated with body shape. The goal is to capture a piece of biometric data from that person. It could be a photograph of their face, a recording of their voice, or a picture of their fingerprints. While there are numerous types of biometrics for authentication, the six most common are facial, voice, iris, near-field communication, palm or finger vein patterns, and Quick Response (QR) code. Biometrics is a subset of the larger field of human identification science. This paper explores computational approaches to speaker recognition, face recognition, speech recognition, and fingerprint recognition to assess the overall state of digital signal processing in biometrics.
8
Singh, Law Kumar, Munish Khanna, and Hitendra Garg. "Multimodal Biometric Based on Fusion of Ridge Features with Minutiae Features and Face Features." International Journal of Information System Modeling and Design 11, no. 1 (2020): 37–57. http://dx.doi.org/10.4018/ijismd.2020010103.
Full textAbstract:
Multimodal biometrics refers to the exploiting combination of two or more biometric modalities in an identification of a system. Fingerprint, face, retina, iris, hand geometry, DNA, and palm print are physiological traits while voice, signature, keystrokes, gait are behavioural traits used for identification by a system. Single biometric features like faces, fingerprints, irises, retinas, etc., deteriorate or change with time, environment, user mode, physiological defects, and circumstance therefore integrating multi features of biometric traits increase robustness of the system. The proposed multimodal biometrics system presents recognition based on face detection and fingerprint physiological traits. This proposed system increases the efficiency, accuracy and decreases execution time of the system as compared to the existing systems. The performance of proposed method is reported in terms of parameters such as False Rejection Rate (FRR), False Acceptance Rate (FAR) and Equal Error Rate (EER) and accuracy is reported at 95.389%.
9
Booysens, Aimee, and Serestina Viriri. "Exploration of Ear Biometrics Using EfficientNet." Computational Intelligence and Neuroscience 2022 (August 31, 2022): 1–14. http://dx.doi.org/10.1155/2022/3514807.
Full textAbstract:
Biometrics is the recognition of a human using biometric characteristics for identification, which may be physiological or behavioral. The physiological biometric features are the face, ear, iris, fingerprint, and handprint; behavioral biometrics are signatures, voice, gait pattern, and keystrokes. Numerous systems have been developed to distinguish biometric traits used in multiple applications, such as forensic investigations and security systems. With the current worldwide pandemic, facial identification has failed due to users wearing masks; however, the human ear has proven more suitable as it is visible. Therefore, the main contribution is to present the results of a CNN developed using EfficientNet. This paper presents the performance achieved in this research and shows the efficiency of EfficientNet on ear recognition. The nine variants of EfficientNets were fine-tuned and implemented on multiple publicly available ear datasets. The experiments showed that EfficientNet variant B8 achieved the best accuracy of 98.45%.
10
Kumar Singha, Anjani, Anshu Singla, and Rajneesh Kumar Pandey. "STUDY AND ANALYSIS ON BIOMETRICS AND FACE RECOGNITION METHODS." EPH - International Journal of Science And Engineering 2, no. 2 (2016): 29–34. http://dx.doi.org/10.53555/eijse.v2i2.145.
Full textAbstract:
Human Biometrics is a rising technology, which has been broadly used in forensics, safe access and top-security prison. A biometric system is primarily a pattern recognition system that recognizes a person by determining the verification by using his different biological features i.e. Fingerprint, retina-scan, iris scan, hand geometry, and face recognition are important physiological biometrics and behavioral trait are Voice recognition, keystroke-scan, and signature-scan. In this paper different biometrics techniques such as Iris scan, retina scan and face recognition techniques are discussed.
11
Drosou, A., D. Ioannidis, K. Moustakas, and D. Tzovaras. "Unobtrusive Behavioral and Activity-Related Multimodal Biometrics: The ACTIBIO Authentication Concept." Scientific World JOURNAL 11 (2011): 503–19. http://dx.doi.org/10.1100/tsw.2011.51.
Full textAbstract:
Unobtrusive Authentication Using ACTIvity-Related and Soft BIOmetrics (ACTIBIO) is an EU Specific Targeted Research Project (STREP) where new types of biometrics are combined with state-of-the-art unobtrusive technologies in order to enhance security in a wide spectrum of applications. The project aims to develop a modular, robust, multimodal biometrics security authentication and monitoring system, which uses a biodynamic physiological profile, unique for each individual, and advancements of the state of the art in unobtrusive behavioral and other biometrics, such as face, gait recognition, and seat-based anthropometrics. Several shortcomings of existing biometric recognition systems are addressed within this project, which have helped in improving existing sensors, in developing new algorithms, and in designing applications, towards creating new, unobtrusive, biometric authentication procedures in security-sensitive, Ambient Intelligence environments. This paper presents the concept of the ACTIBIO project and describes its unobtrusive authentication demonstrator in a real scenario by focusing on the vision-based biometric recognition modalities.
12
Arunarani, S., and R. Gobinath. "A survey on multimodal biometrics for human authentication." International Journal of Engineering & Technology 7, no. 3.3 (2018): 273. http://dx.doi.org/10.14419/ijet.v7i2.33.14167.
Full textAbstract:
Authentication process identifies an individual to get an endorsed access by entering their login credentials. The inconvenience with this method is the user must remember the keywords, and the passwords can be predicted or if it is hard to guess it will be cracked through brute force. Due to this fault, this method is lack of integrity. Biometrics sample recognize a person based on his behavioral or physiological char-acteristics. Unimodal biometric systems have to resist with a different types of problems such as inconsistent data, intra-class variations, deceit attacks and high error rates. Multimodal biometrics implements secure authentication using various biometric traits. This survey gives us a wide scope for improving and enhancing the biometric applications. In this paper, we have explained multimodal biometrics to decrease the error rate and increase the security.
13
Elshahed, Marwa A. "Personal identity verification based ECG biometric using non-fiducial features." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 3007. http://dx.doi.org/10.11591/ijece.v10i3.pp3007-3013.
Full textAbstract:
Biometrics was used as an automated and fast acceptable technology for human identification and it may be behavioral or physiological traits. Any biometric system based on identification or verification modes for human identity. The electrocardiogram (ECG) is considered as one of the physiological biometrics which impossible to mimic or stole. ECG feature extraction methods were performed using fiducial or non-fiducial approaches. This research presents an authentication ECG biometric system using non-fiducial features obtained by Discrete Wavelet Decomposition and the Euclidean Distance technique was used to implement the identity verification. From the obtained results, the proposed system accuracy is 96.66% also, using the verification system is preferred for a large number of individuals as it takes less time to get the decision.
14
Marwa, A. Elshahed. "Personal identity verification based ECG biometric using non-fiducial features." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (2020): 3007–13. https://doi.org/10.11591/ijece.v10i3.pp3007-3013.
Full textAbstract:
Biometrics was used as an automated and fast acceptable technology for human identification and it may be behavioral or physiological traits. Any biometric system based on identification or verification modes for human identity. The electrocardiogram (ECG) is considered as one of the physiological biometrics which impossible to mimic or stole. ECG feature extraction methods were performed using fiducial or non-fiducial approaches. This research presents an authentication ECG biometric system using non-fiducial features obtained by Discrete Wavelet Decomposition and the Euclidean Distance technique was used to implement the identity verification. From the obtained results, the proposed system accuracy is 96.66% also, using the verification system is preferred for a large number of individuals as it takes less time to get the decision.
15
Reddy, M. V. Bramhananda, and V. Goutham. "IRIS TECHNOLOGY: A REVIEW ON IRIS BASED BIOMETRIC SYSTEMS FOR UNIQUE HUMAN IDENTIFICATION." International Journal of Research -GRANTHAALAYAH 6, no. 1 (2018): 80–90. http://dx.doi.org/10.29121/granthaalayah.v6.i1.2018.1596.
Full textAbstract:
Biometric features are widely used in real time applications for unique human identification. Iris is one of the physiological biometric features which are regarded as highly reliable in biometric identification systems. Often iris is combined with other biometric features for robust biometric systems. It is also observed that biometrics is combined with cryptography for stronger security mechanisms. Since iris is unique for all individuals across the globe, many researchers focused on using iris or along with other biometrics for security with great precision. Multimodal biometric systems came into existence for better accuracy in human authentication. However, iris is considered to be most discriminatory of facial biometrics. Study of iris based human identification in ideal and non-cooperative environments can provide great insights which can help researchers and organizations that depend on iris-based biometric systems. The technical knowhow of iris strengths and weaknesses can be great advantage. This is more important in the wake of widespread use of smart devices which are vulnerable to attacks. This paper throws light into various iris-based biometric systems, issues with iris in the context of texture comparison, cancellable biometrics, iris in multi-model biometric systems, iris localization issues, challenging scenarios pertaining to accurate iris recognition and so on.
16
Dr, M. V. Bramhananda Reddy, and V. Goutham Dr. "IRIS TECHNOLOGY: A REVIEW ON IRIS BASED BIOMETRIC SYSTEMS FOR UNIQUE HUMAN IDENTIFICATION." International Journal of Research - Granthaalayah 6, no. 1 (2018): 80–90. https://doi.org/10.5281/zenodo.1162210.
Full textAbstract:
Biometric features are widely used in real time applications for unique human identification. Iris is one of the physiological biometric features which are regarded as highly reliable in biometric identification systems. Often iris is combined with other biometric features for robust biometric systems. It is also observed that biometrics is combined with cryptography for stronger security mechanisms. Since iris is unique for all individuals across the globe, many researchers focused on using iris or along with other biometrics for security with great precision. Multimodal biometric systems came into existence for better accuracy in human authentication. However, iris is considered to be most discriminatory of facial biometrics. Study of iris based human identification in ideal and non-cooperative environments can provide great insights which can help researchers and organizations that depend on iris-based biometric systems. The technical knowhow of iris strengths and weaknesses can be great advantage. This is more important in the wake of widespread use of smart devices which are vulnerable to attacks. This paper throws light into various iris-based biometric systems, issues with iris in the context of texture comparison, cancellable biometrics, iris in multi-model biometric systems, iris localization issues, challenging scenarios pertaining to accurate iris recognition and so on.
17
Chinyemba, Melissa K., and Jackson Phiri. "Gaps in the Management and Use of Biometric Data: A Case of Zambian Public and Private Institutions." Zambia ICT Journal 2, no. 1 (2018): 35–43. http://dx.doi.org/10.33260/zictjournal.v2i1.49.
Full textAbstract:
The current physical and cybersecurity systems rely on traditional three-factor authentication to mitigate the threats posed by insider attacks. Key is the use of biometric information. Biometrics are a unique measurement and analysis of the unique physiological special traits such as voice, eye structure and others that can be used in the discipline of varying person identification. Biometry, which is the analysis of these biometrics is a complex process but guarantees identification and non-repudiation. If used to identify humans then several issues such as where is the biometric data stored? Who has access to it? And how does one ensure that such data satisfies the principle of availability. To achieve availability, secure transportation arises. To achieve transportation, non-repudiation, confidentiality and authentication, integrity arise. A storage and transport system is recommended to these challenges. In this paper, we explore the gaps into how public and private institution store and manage biometrics information. We benchmarked each organization again the ISO 30107 and ISO 24745. Our results show that while most companies are adopting and using biometrics systems, few have adopted the ISO biometrics standards that govern the storage and management of biometric information and hence creating security risk.
18
Sayoud, Halim. "Biometrics." International Journal of Technoethics 2, no. 1 (2011): 19–34. http://dx.doi.org/10.4018/jte.2011010102.
Full textAbstract:
The term biometrics is derived from the Greek words: bio (life) and metrics (to measure). “Biometric technologies” are defined as automated methods of verifying or recognizing the identity of a living person based on a physiological or behavioral characteristic. Several techniques and features were used over time to recognize human beings several years before the birth of Christ. Today, this research field has become very employed in many applications such as security applications, multimedia applications and banking applications. Also, many methods have been developed to strengthen the biometric accuracy and reduce the imposture errors by using several features such as face, speech, iris, finger vein, etc. From a security purpose and economic point of view, biometrics has brought a great benefit and has become an important tool for governments and institutions. However, citizens are expressing their thorough worry, which is due to the freedom limitations and loss of privacy. This paper briefly presents some new technologies that have recently been proposed in biometrics with their levels of reliability, and discusses the different social and ethic problems that may result from the abusive use of these technologies.
19
Channegowda, Arjun Benagatte, and H. N. Prakash. "Multimodal biometrics of fingerprint and signature recognition using multi-level feature fusion and deep learning techniques." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (2021): 187. http://dx.doi.org/10.11591/ijeecs.v22.i1.pp187-195.
Full textAbstract:
Providing security in biometrics is the major challenging task in the current situation. A lot of research work is going on in this area. Security can be more tightened by using complex security systems, like by using more than one biometric trait for recognition. In this paper multimodal biometric models are developed to improve the recognition rate of a person. The combination of physiological and behavioral biometrics characteristics is used in this work. Fingerprint and signature biometrics characteristics are used to develop a multimodal recognition system. Histograms of oriented gradients (HOG) features are extracted from biometric traits and for these feature fusions are applied at two levels. Features of fingerprint and signatures are fused using concatenation, sum, max, min, and product rule at multilevel stages, these features are used to train deep learning neural network model. In the proposed work, multi-level feature fusion for multimodal biometrics with a deep learning classifier is used and results are analyzed by a varying number of hidden neurons and hidden layers. Experiments are carried out on SDUMLA-HMT, machine learning and data mining lab, Shandong University fingerprint datasets, and MCYT signature biometric recognition group datasets, and encouraging results were obtained.
20
Channegowda, Arjun Benagatte, and H. N. Prakash. "Multimodal biometrics of fingerprint and signature recognition using multi-level feature fusion and deep learning techniques." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 1 (2021): 187–95. https://doi.org/10.11591/ijeecs.v22.i1.pp187-195.
Full textAbstract:
Providing security in biometrics is the major challenging task in the current situation. A lot of research work is going on in this area. Security can be more tightened by using complex security systems, like by using more than one biometric trait for recognition. In this paper multimodal biometric models are developed to improve the recognition rate of a person. The combination of physiological and behavioral biometrics characteristics is used in this work. Fingerprint and Signature biometrics characteristics are used to develop a multimodal recognition system. Histograms of oriented gradients (HOG) features are extracted from biometric traits and for these feature fusions are applied at two levels. Features of Fingerprint and Signatures are fused using concatenation, sum, max, min, and product rule at multilevel stages, these features are used to train deep learning neural network model. In the proposed work, Multi-level feature fusion for multimodal biometrics with a deep learning classifier is used and results are analyzed by a varying number of hidden neurons and hidden layers. Experiments are carried out on SDUMLA-HMT, machine learning and data mining lab, Shandong University fingerprint datasets, and MCYT signature biometric recognition group datasets, and encouraging results were obtained.
21
Kostyuk, Nataliya, Phyadragren Cole, Natarajan Meghanathan, Raphael D. Isokpehi, and Hari H. P. Cohly. "Gas Discharge Visualization: An Imaging and Modeling Tool for Medical Biometrics." International Journal of Biomedical Imaging 2011 (2011): 1–7. http://dx.doi.org/10.1155/2011/196460.
Full textAbstract:
The need for automated identification of a disease makes the issue of medical biometrics very current in our society. Not all biometric tools available provide real-time feedback. We introduce gas discharge visualization (GDV) technique as one of the biometric tools that have the potential to identify deviations from the normal functional state at early stages and in real time. GDV is a nonintrusive technique to capture the physiological and psychoemotional status of a person and the functional status of different organs and organ systems through the electrophotonic emissions of fingertips placed on the surface of an impulse analyzer. This paper first introduces biometrics and its different types and then specifically focuses on medical biometrics and the potential applications of GDV in medical biometrics. We also present our previous experience with GDV in the research regarding autism and the potential use of GDV in combination with computer science for the potential development of biological pattern/biomarker for different kinds of health abnormalities including cancer and mental diseases.
22
Költzsch, Gregor. "BIOMETRICS - MARKET SEGMENTS AND APPLICATIONS." Journal of Business Economics and Management 8, no. 2 (2007): 119–22. http://dx.doi.org/10.3846/16111699.2007.9636159.
Full textAbstract:
Biometric methods are concerned with the measurement and evaluation of human physiological or behavioral characteristics. During the last years, the economic relevance of the biometric industry and market has increased rapidly. Although public security projects have initiated the positive market development, future growth will be also generated by private sector demand such as secure and convenient banking, payment applications etc. The deployment of biometrics to machine readable travel documents such as passports provides citizens with first experiences in biometric applications, thereby functioning as pioneer projects and market openers for other market segments. For example, biometric passports will redefine the border control process in the future, and in the midterm, aviation security is another market segment that will contribute to the growth. To prepare for this business, the industry must carefully analyze the market and meet the demand. This article assesses the economic relevance of biometrics and discusses selected market segments.
23
Jain, Rubal, and Chander Kant. "Attacks on Biometric Systems: An Overview." International Journal of Advances in Scientific Research 1, no. 7 (2015): 283. http://dx.doi.org/10.7439/ijasr.v1i7.1975.
Full textAbstract:
Biometrics is a pattern recognition system that refers to the use of different physiological (face, fingerprints, etc.) and behavioral (voice, gait etc.) traits for identification and verification purposes. A biometrics-based personal authentication system has numerous advantages over traditional systems such as token-based (e.g., ID cards) or knowledge-based (e.g., password) but they are at the risk of attacks. This paper presents a literature review of attack system architecture and makes progress towards various attack points in biometric system. These attacks may compromise the template resulting in reducing the security of the system and motivates to study existing biometric template protection techniques to resist these attacks.
24
Medjahed, Chahreddine, Abdellatif Rahmoun, Christophe Charrier, and Freha Mezzoudj. "A deep learning-based multimodal biometric system using score fusion." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (2022): 65. http://dx.doi.org/10.11591/ijai.v11.i1.pp65-80.
Full textAbstract:
Recent trends in artificial intelligence tools-based biometrics have overwhelming attention to security matters. The hybrid approaches are motivated by the fact that they combine mutual strengths and they overcome their limitations. Such approaches are being applied to the fields of biomedical engineering. A biometric system uses behavioural or physiological characteristics to identify an individual. The fusion of two or more of these biometric unique characteristics contributes to improving the security and overcomes the drawbacks of unimodal biometric-based security systems. This work proposes efficent multimodal biometric systems based on matching score concatenation fusion of face, left and right palm prints. Multimodal biometric identification systems using convolutional neural networks (CNN) and k-nearest neighbors (KNN) are proposed and trained to recognize and identify individuals using multi-modal biometrics scores. Some popular biometrics benchmarks such as FEI face dataset and IITD palm print database are used as raw data to train the biometric systems to design a strong and secure verification/identification system. Experiments are performed on noisy datasets to evaluate the performance of the proposed model in extreme scenarios. Computer simulation results show that the CNN and KNN multi-modal biometric system outperforms most of the most popular up to date biometric verification techniques.
25
Chahreddine, Medjahed, Rahmoun Abdellatif, Charrier Christophe, and Mezzoudj Freha. "A deep learning-based multimodal biometric system using score fusion." International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (2022): 65–80. https://doi.org/10.11591/ijai.v11.i1.pp65-80.
Full textAbstract:
Recent trends in artificial intelligence tools-based biometrics have overwhelming attention to security matters. The hybrid approaches are motivated by the fact that they combine mutual strengths and they overcome their limitations. Such approaches are being applied to the fields of biomedical engineering. A biometric system uses behavioural or physiological characteristics to identify an individual. The fusion of two or more of these biometric unique characteristics contributes to improving the security and overcomes the drawbacks of unimodal biometric-based security systems. This work proposes efficent multimodal biometric systems based on matching score concatenation fusion of face, left and right palm prints. Multimodal biometric identification systems using convolutional neural networks (CNN) and k-nearest neighbors (KNN) are proposed and trained to recognize and identify individuals using multi-modal biometrics scores. Some popular biometrics benchmarks such as FEI face dataset and IITD palm print database are used as raw data to train the biometric systems to design a strong and secure verification/identification system. Experiments are performed on noisy datasets to evaluate the performance of the proposed model in extreme scenarios. Computer simulation results show that the CNN and KNN multi-modal biometric system outperforms most of the most popular up to date biometric verification techniques.
26
N, Nithiya. "Automatic License Checking Using Fingerprint." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 3440–42. https://doi.org/10.22214/ijraset.2025.68994.
Full textAbstract:
Driving license verification framework is a serious issue in many countries. therefore, the biometric based driving license verification framework is employed because it's exceedingly simple and beneficial to screen. Biometrics suggests approximation regarding mortal traits. Biometrics proof (or reasonable countersign) is utilized in programming as a type of ID and access control. It's also used to perceive individuals in groups that are in perception. Biometric identifiers are also visible, quantifiable characteristics used to marker and characterize individuals. Biometric identifiers are continually requested as physical instead of social characteristics. Physiological characteristics are related to the state of the body. Biometrics studies typically consist of discrete cutlet print, face, iris, voice, mark, and hand computation identification and authentication. Out of these open biometric features special cutlet print emerges perhaps the best point providing superior mismatch rate as well as durable. Other characters are face, iris, voice, hand, and hand figure identification varying with times but point remaining the same as age persists. Thus point becomes reliable. Through imposing this biometric rooted system i.e. point technology to identify driving license bone can rule out additional time operation to support all cars.
27
Zuffo, Alan Mario, Fábio Steiner, Luciano Façanha Marques, et al. "Seed biometry according to the canafístula maturation stage." CONTRIBUCIONES A LAS CIENCIAS SOCIALES 18, no. 4 (2025): e17159. https://doi.org/10.55905/revconv.18n.4-235.
Full textAbstract:
Canafistula is a species of great ecological relevance and economic potential. To promote its propagation, it is essential to understand the factors that affect seed quality, especially biometrics and the maturation stage. Given the importance of maturation and biometrics in the quality of canafistula seeds, this study aimed to evaluate the variation in biometric attributes throughout the maturation stages and to determine the ideal stage for seed harvest. The seeds were collected from the crowns of 10 trees according to the maturation stage (green seed, green-to-brown transition, light brown and dark brown), and the following parameters were evaluated: longitudinal length, width, thickness, dry mass and water content of the seeds. seeds. The maturation process significantly affects the biometric and physiological characteristics of canafístula seeds. Seeds in the early stages of maturation (green) had larger dimensions due to their high moisture content, whereas seeds in more advanced stages (dark brown) had greater accumulation of dry mass, indicating physiological maturity.
28
Jafarov, N., A. Pashaev, and R. Mastaliev. "COMPARATIVE ANALYSIS OF SOME BIOMETRIC AUTHENTICATION SYSTEMS." Sciences of Europe, no. 129 (November 27, 2023): 236–46. https://doi.org/10.5281/zenodo.10209592.
Full textAbstract:
The article discusses the basics, advantages and disadvantages of using several types of widely used biometric data for authentication with reference to literature sources. Considering that the biometric characteristics of a person are discrete and unique. Some of these features are difficult to reproduce or accurately manufacture. Therefore, for authentication, specific human organs are used (fingerprints, iris, facial structure in 2D, 3D format, hand veins, etc.) and corresponding biometric devices are created. Biometric devices are used to screen and classify people based on their physiological characteristics. These technologies can be classified as behavioral or physiological biometrics. The article is devoted to the listed biometric data and a brief summary of the use of authentication tools provided by them.
29
Jha, Abhishek, Ashish A, and Lalita Verma. "Biometric Authentication." YMER Digital 21, no. 05 (2022): 1041–49. http://dx.doi.org/10.37896/ymer21.05/b9.
Full textAbstract:
Progresses in the field of Information Technology likewise make Information Security an indivisible piece of it. To manage security, Authentication assumes a significant part. This paper presents a survey on the biometric confirmation strategies and some future conceivable outcomes in this field. In biometrics, an individual should be distinguished in view of some trademark physiological boundaries. A wide assortment of frameworks requires solid individual acknowledgment plans to either affirm or decide the character of an individual mentioning their administrations. The motivation behind such plans is to guarantee that the delivered administrations are gotten to simply by a real client, and not any other individual. By utilizing biometrics, it is feasible to affirm or lay out a singular's character. The place of biometrics in the current field of Security has been portrayed in this work. We have additionally illustrated conclusions about the convenience of biometric verification frameworks, correlation between various procedures and their benefits and inconveniences in this paper
30
Alam, Varisha. "Ordering of Huge Biometric Information in Database System." Journal of Informatics Electrical and Electronics Engineering (JIEEE) 2, no. 2 (2021): 1–19. http://dx.doi.org/10.54060/jieee/002.02.011.
Full textAbstract:
The word biometrics is derived from the Greek words 'bios' and 'metric' which means living and calculation appropriately. Biometrics is the electronic identification of individuals based on their physiological and biological features. Biometric attributes are data take out from biometric test which can be used for contrast with a biometric testimonial. Biometrics composed methods for incomparable concede humans based upon one or more inherent material or behavioral characteristics. In Computer Science, bio-metrics is employed as a kind of recognition access management and access command. Biometrics has quickly seemed like an auspicious technology for attestation and has already found a place in the most sophisticated security areas. A systematic clustering technique has been there for partitioning huge biometric databases throughout recognition. As we tend to are still obtaining the higher bin-miss rate, so this work is predicated on conceiving an ordering strategy for recognition of huge biometric database and with larger precision. This technique is based on the modified B+ tree that decreases the disk accesses. It reduced the information retrieval time and feasible error rates. The ordering technique is employed to proclaims a person’s identity with a reduced rate of differentiation instead of searching the whole database. The response time degenerates, further-more because the accuracy of the system deteriorates as the size of the database increases. Hence, for vast applications, the requirement to reduce the database to a little fragment seems to attain higher speeds and improved accuracy.
31
Koong, Chorng-Shiuh, Tzu-I. Yang, and Chien-Chao Tseng. "A User Authentication Scheme Using Physiological and Behavioral Biometrics for Multitouch Devices." Scientific World Journal 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/781234.
Full textAbstract:
With the rapid growth of mobile network, tablets and smart phones have become sorts of keys to access personal secured services in our daily life. People use these devices to manage personal finances, shop on the Internet, and even pay at vending machines. Besides, it also helps us get connected with friends and business partners through social network applications, which were widely used as personal identifications in both real and virtual societies. However, these devices use inherently weak authentication mechanism, based upon passwords and PINs that is not changed all the time. Although forcing users to change password periodically can enhance the security level, it may also be considered annoyances for users. Biometric technologies are straightforward because of the simple authentication process. However, most of the traditional biometrics methodologies require diverse equipment to acquire biometric information, which may be expensive and not portable. This paper proposes a multibiometric user authentication scheme with both physiological and behavioral biometrics. Only simple rotations with fingers on multitouch devices are required to enhance the security level without annoyances for users. In addition, the user credential is replaceable to prevent from the privacy leakage.
32
Lee, Boo-Ha, and Shin-Uk Park. "Legislative Policy Consideration for Reinforcement of Biometrics Protection." LAW RESEARCH INSTITUTE CHUNGBUK NATIONAL UNIVERSITY 13, no. 1 (2022): 171–98. http://dx.doi.org/10.34267/cbstl.2022.13.1.171.
Full textAbstract:
Article 23 (1) of the Personal Information Protection Act stipulates that “A personal information controller shall not process any information prescribed by Presidential Decree (hereinafter referred to as ‘sensitive data’), including ideology, belief, admission to or withdrawal from a trade union or political party, political opinions, health, sex life, and other personal information that is likely to markedly threaten the privacy of any data subject.” Article 18 of the Enforcement Decree of the Personal Information Protection Act stipulates that ‘Information prescribed by Presidential Decree’ in the main clause , with the exception of the subparagraph, of Article 23 (1) of the Act means the following data or information. In subparagraph 3, “Personal information resulting from specific technical processing of data relating to the physical, physiological or behavioral characteristics of an individual for the purpose of uniquely identifying that individual” is defined as one of the sensitive data.
 The range of sensitive data is wider than that of biometrics. ‘Data that constitutes a criminal history record’ defined in subparagraph 5 of Article 2 of the Act on the Lapse of Criminal Sentences, etc. as stipulated in Article 18 (3) of the Enforcement Decree of the Personal Information Protection Act and Article 18 (4) of the Enforcement Decree of the Personal Information Protection Act ‘Personal information revealing racial or ethnic origin’ is sensitive data completely different from biometric information.
 Therefore, it is necessary to enact a separate law to protect and manage biometrics or biometric information that requires more protection than sensitive data.
 As safety measures for biometrics security, there are first, security measures for forged/falsified biometric information, second, protection of the transmission section when collecting and inputting biometric information, third, use within the scope of the agreed purpose, fourth, biometric information collection and input processing at the terminal, fifth, encryption when storing biometric information, sixth, destruction of biometric information, seventh, separate storage when storing original biometric information, eighth, in case of leakage of biometric information, protective measures are taken.
 The Act on Protection and Management of Biometrics (draft) includes Chapter 1 General Provisions, Chapter 2 Establishment of Biometrics Protection Policy, Chapter 3 Collection and Use of Biometrics and Restrictions on It, Chapter 4 Safe Management of Biometrics, and Chapter 5, Guarantee of Rights of Data Subjects.
33
K. Selsiya, Dr. D. Banumathy, Nijanthan, and Dr. G. Madasamyraja. "Person Authentication System Using Multimodal Biometrics." International Journal of Scientific Research in Science, Engineering and Technology 11, no. 3 (2024): 276–80. http://dx.doi.org/10.32628/ijsrset24113129.
Full textAbstract:
Biometrics is the automated process used to recognize human by measuring their behavioural and physiological characteristics. Biometrics are generally used either for verification The use of biometric for identification purposes requires that a particular biometric factor be unique for each individual that it can be calculated, and that it is invariant over time. Biometrics such as signatures, photographs, fingerprints, voiceprints and retinal blood vessel patterns all have noteworthy drawbacks. Although signatures and photographs are cheap and easy to obtain and store, they are impossible to identify automatically with assurance, and are easily forget. Human iris on the other hand as an internal organ of the eye and as well protected from the external environment, yet it is easily visible from within one meter of distance makes it a perfect biometric for an identification system with the ease of speed, reliability and automation Iris recognition is an automated method of biometric identification that uses mathematical pattern-recognition techniques on images of the irises of an individual’s eyes, whose complex random patterns are unique. Proposed system provides a comprehensive implementation of periocular biometrics and a deep insight of various aspects such as utility of peri-ocular region In this project face and eye points are captured using Grassmann algorithm and Gabor filter for eye features extraction. Each trait is analysed separately and given its own score. The results are combined using deep leaning algorithm to provide a single decision in real time environments.
34
Singh, Law Kumar, Munish Khanna, Shankar Thawkar, and Jagadeesh Gopal. "Robustness for Authentication of the Human Using Face, Ear, and Gait Multimodal Biometric System." International Journal of Information System Modeling and Design 12, no. 1 (2021): 39–72. http://dx.doi.org/10.4018/ijismd.2021010103.
Full textAbstract:
Biometrics is the science that deals with personal human physiological and behavioral characteristics such as fingerprints, handprints, iris, voice, face recognition, signature recognition, ear recognition, and gait recognition. Recognition using a single trait has several problems and multimodal biometrics system is one of the solutions. In this work, the novel and imperative biometric feature gait is fused with face and ear biometric features for authentication and to overcome problems of the unimodal biometric recognition system. The authors have also applied various normalization methods to sort out the best solution for such a challenge. The feature fusion of the proposed multimodal biometric system has been tested using Min-Max and Z-score techniques. The computed results demonstrate that Z-Score outperforms the Min-Max technique. It is deduced that the Z-score is a promising method that generates a high recognition rate of 95% and a false acceptance rate of 10%.
35
Ayanaba, Rasheed Abubakar. "Image-assisted Biometric Identification." Advances in Multidisciplinary and scientific Research Journal Publication 1, no. 1 (2022): 131–38. http://dx.doi.org/10.22624/aims/crp-bk3-p22.
Full textAbstract:
Biometrics is a rapidly developing technology that has seen widespread use in forensics applications such as criminal identification, secure access, and prison security. A biometric system is a pattern recognition system that recognizes a person by determining the authenticity of a physiological and/or behavioural feature that that person possesses. One of the most widely accepted biometrics utilized by humans in their visual interactions is image- assisted based (facial) biometric. Image-assisted biometric identification is the use of face recognition technology in capturing image of a unique feature of an individual such as an eye or face, and comparing it with a template captured earlier and stored a database. Face recognition is one of the more recent biometrics technologies. The system examines face features and tries to match them to a database of digitized images. This technology is quite new, having only been available commercially since the 1990s. Face recognition has gotten a lot of press after the 9/11 attacks because of its capacity to identify known terrorists and criminals. [1]. Although the technology is mostly utilized for security and law enforcement, there is growing interest in other applications. Keyword: Image-assisted based biometric identification, Face recognition technology, Image
36
Edim Bassey Edim and Akpan Itoro Udofot. "Biometric Authentication and Algorithm: A review." International Journal of Science and Research Archive 14, no. 3 (2025): 960–86. https://doi.org/10.30574/ijsra.2025.14.3.0473.
Full textAbstract:
Biometric authentication represents a cutting-edge security mechanism that leverages unique physiological and behavioral traits to verify an individual’s identity. In an era where data security and privacy are paramount, biometric technologies play a critical role in fortifying systems against unauthorized access and breaches. Unlike traditional authentication methods such as passwords or physical keys, biometrics offer a blend of reliability, convenience, and near-impossible impersonation positioning them as a cornerstone of modern security frameworks.
37
Shinde, Krishna, and Sumegh Tharewal. "Development of Face and Signature Fusion Technology for Biometrics Authentication." International Journal of Emerging Research in Management and Technology 6, no. 9 (2018): 61. http://dx.doi.org/10.23956/ijermt.v6i9.86.
Full textAbstract:
The Biometrics system is getting popularity since last decade As per Information Technology industry demand. This techn-ology are satisfy authentication and authorization process needs. But the unimodal biometric system have own limitations. the limitation of unimodal, we can choosing the approach of multimodal biometric system. In this research paper choose the physiological model for face recognition and behavioural model for signature recognition. The recognition of face and signature used match score level fusion. In this fusion technology for secured authentication of person
38
Ferrag, Mohamed Amine, Leandros Maglaras, and Abdelouahid Derhab. "Authentication and Authorization for Mobile IoT Devices Using Biofeatures: Recent Advances and Future Trends." Security and Communication Networks 2019 (May 5, 2019): 1–20. http://dx.doi.org/10.1155/2019/5452870.
Full textAbstract:
Biofeatures are fast becoming a key tool to authenticate the IoT devices; in this sense, the purpose of this investigation is to summarise the factors that hinder biometrics models’ development and deployment on a large scale, including human physiological (e.g., face, eyes, fingerprints-palm, or electrocardiogram) and behavioral features (e.g., signature, voice, gait, or keystroke). The different machine learning and data mining methods used by authentication and authorization schemes for mobile IoT devices are provided. Threat models and countermeasures used by biometrics-based authentication schemes for mobile IoT devices are also presented. More specifically, we analyze the state of the art of the existing biometric-based authentication schemes for IoT devices. Based on the current taxonomy, we conclude our paper with different types of challenges for future research efforts in biometrics-based authentication schemes for IoT devices.
39
Bhirud, Priya, and Nandana Prabhu. "Performance Evaluation of Filters of Discrete Wavelet Transforms for Biometrics." International Journal of Informatics and Communication Technology (IJ-ICT) 3, no. 2 (2014): 97. http://dx.doi.org/10.11591/ijict.v3i2.pp97-102.
Full textAbstract:
<p>Biometrics associated with automated methods of identifying a person or verifying the identity of a person based on physiological or behavioral characteristics. Commonly used biometric features are facial features, fingerprints, voice, facial thermo grams, iris, posture/gait, palm print, hand geometry etc. Compared with other biometric characteristics iris is the most stable and hence the most reliable biometric characteristic over the period of a lifetime. This proposed work provides comparative study of various filters of Wavelet Transforms in terms of size and PSNR of images<em>.</em></p>
40
Diac, Madalina Maria, Simona Irina Damian, Bianca Diana Butincu, Anton Knieling, and Diana Bulgaru Iliescu. "Ethical Aspects of Biometric Identification." BRAIN. Broad Research in Artificial Intelligence and Neuroscience 14, no. 4 (2023): 124–39. http://dx.doi.org/10.18662/brain/14.4/496.
Full textAbstract:
The term biometrics derives from Greek (bio=life and metrics=measure) and implies the measurement of biological signs. Biometrics is the science of recognizing people based on their physical, behavioral, and physiological attributes, such as fingerprint, face scan, iris, retina, and voice. The present paper aims to develop a study on biometric identification. The major objective of the study is to conduct a survey among the Romanian population on the importance and knowledge of biometric identification methods. This objective was achieved by assessing the knowledge held by the general population of Romania regarding biometric indicators and the degree of adaptability and openness of citizens related to the widest possible implementation of biometrics. The study was based on conducting a quantitative analysis using a questionnaire. Due to the high degree of accessibility, the online environment was chosen as a method of application, distribution being made through social networks. A biometric template digitizes the human body, it has been argued that the collection of biometric identifiers not only interferes with the privacy and right to protection of a person's data, but also with the integrity of an individual's body. In conclusion, the creation and storage of a unique biometric template must be seen in relation to the purpose of the operation. The protection of citizens from criminal activities is a primary obligation of the state. However, it must be exercised with due respect for a number of fundamental ethical values and in the light of modern human rights law.
41
Manikis, Georgios C., Marios Spanakis, and Emmanouil G. Spanakis. "Personalized Mobile eHealth Services for Secure User Access Through a Multi Feature Biometric Framework." International Journal of Reliable and Quality E-Healthcare 8, no. 1 (2019): 40–51. http://dx.doi.org/10.4018/ijrqeh.2019010104.
Full textAbstract:
Humans have various features that differentiates one person from another which can be used to identify an individual for security purposes. These biometrics can authenticate or verify a person's identity and can be sorted in two classes, physiological and behavioural. In this article, the authors present their results of experimentation on publicly available facial images and the efficiency of a prototype version of SpeechXRays, a multi-modal biometric system that uses audio-visual characteristics for user authentication in eHealth platforms. Using the privacy and security mechanism provided, based on audio and video biometrics, medical personnel are able to be verified and subsequently identified for two different eHealth applications. These verified persons are then able to access control, identification, workforce management or patient record storage. In this work, the authors argue how a biometric identification system can greatly benefit healthcare, due to the increased accuracy of identification procedures.
42
., Anju, and Anuradha Saini. "Designing an Authentication Mechanism using Biometric System." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 5 (2018): 124. http://dx.doi.org/10.23956/ijarcsse.v8i5.691.
Full textAbstract:
Biometrics" designates "life quantification" but the term is conventionally associated with the utilization of unique physiological characteristics to identify an individual. The application to which most people associate with biometrics is security. A number of biometric traits have been developed and are habituated to authenticate the identity of a person. The conception is to utilize the special characteristics of a person to identify him. By utilizing these special characteristics, we mean utilizing the features such as iris, face, dactylogram, signature etc. The method of identification predicated on biometrics characteristics is preferred over traditional passwords and PIN predicated methods for sundry reasons such as: The person to be identified is required to be physically present at the time-of-identification. Here we have utilized dactylogram and iris traits at feature level extraction. The features are extracted from the pre-processed images of iris and dactylogram. The main goal of optimization in this scenario is to enhance the technique of feature extraction by utilizing better steps.
43
Gu, Datong, Minh Nguyen, and Weiqi Yan. "Cross Models for Twin Recognition." International Journal of Digital Crime and Forensics 8, no. 4 (2016): 26–36. http://dx.doi.org/10.4018/ijdcf.2016100103.
Full textAbstract:
Nowadays, Biometrics has become a popular tool in personal identification as it can use physiological or behavioral characteristics to identify individuals. Recent advances in information technology has increased the accuracy of biometric to another level, there is still a slew of problems existed, such as complex environment, aging and unique problems. Among many classes of identifications, recognizing twins is one of the most difficult tasks as they resemble each other. This affects the use of biometrics in general cases and raises potential risks of biometrics in access control. In this paper, the authors manage to distinguish twins using four different models, namely, face recognition, ear recognition, voice recognition and lip movement recognition. Their results show that voice recognition has the best performance in twin recognition with 100% accuracy. This is much higher than that of face recognition and ear recognition (with 58% and 53% respectively); and lip movement recognition that yields 76% accuracy.
44
Madalina, Maria Diac, Irina Damian Simona, Diana Butincu Bianca, Knieling Anton, and Bulgaru Iliescu Diana. "Ethical Aspects of Biometric Identification." BRAIN. Broad Research in Artificial Intelligence and Neuroscience 14, no. 4 (2024): 124–39. https://doi.org/10.18662/brain/14.4/496.
Full textAbstract:
The term <em>biometrics</em> derives from Greek (<em>bio=life and metrics=measure) and implies the measurement of biological signs</em>. Biometrics is the science of recognizing people based on their physical, behavioral, and physiological attributes, such as fingerprint, face scan, iris, retina, and voice. The present paper aims to develop a study on biometric identification. The major objective of the study is to conduct a survey among the Romanian population on the importance and knowledge of biometric identification methods. This objective was achieved by assessing the knowledge held by the general population of Romania regarding biometric indicators and the degree of adaptability and openness of citizens related to the widest possible implementation of biometrics. The study was based on conducting a quantitative analysis using a questionnaire. Due to the high degree of accessibility, the online environment was chosen as a method of application, distribution being made through social networks. A biometric template digitizes the human body, it has been argued that the collection of biometric identifiers not only interferes with the privacy and right to protection of a person's data, but also with the integrity of an individual's body. In conclusion, the creation and storage of a unique biometric template must be seen in relation to the purpose of the operation. The protection of citizens from criminal activities is a primary obligation of the state. However, it must be exercised with due respect for a number of fundamental ethical values and in the light of modern human rights law.
45
Murli, Manohar Yadav*, Nigam Kriti, Srivastava Ankit, and Kumar Pradeep. "RECENT ADVANCEMENTS IN EAR BIOMETRICS: A REVIEW." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 4 (2016): 653–59. https://doi.org/10.5281/zenodo.49811.
Full textAbstract:
Ascertaining the identity of a person is quite an important aspect of Forensic Science. There are so many physiological features have been proved to be highly discriminating among individuals. Biometrics play a significant role in individualizing a person. Fingerprint, Palm print, Retina and Iris recognition are the most popular examples of it. Fingerprint and iris are generally considered to allow more accurate biometric recognition than the face, but the face is more easily used in surveillance scenarios where fingerprint and iris capture are not feasible. However, the face by itself is not yet as accurate and flexible as desired for this scenario due to expression changes, source of illumination, make-up, etc. Besides these limitations, ear images can be acquired in a similar manner to face images. A number of researchers have suggested that the human ear is unique enough to each individual to allow practical use as a biometric. In this article an attempt has been made to review all the recent researches of a decade made in the field of Ear Biometrics.
46
Porusu, Ramanaiah, and Kumar Rupak. "RFID BASED SECURITY SYSTEM FOR MARKING ATTENDANCE WITH CAMERA OPTION." International Journal of Advances in Engineering & Scientific Research 4, no. 4 (2017): 16–24. https://doi.org/10.5281/zenodo.10775986.
Full textAbstract:
<strong>Abstract: </strong> Biometrics manages computerized strategy for recognizing a man or checking the personality of a man in light of the physiological or way of acting, as is utilized for verification in a significant number of the exchanges which has been done on the web.Thebiometric for security that has been chosen for implementation isfingerprint, since fingerprint biometric is easily available andhighly reliable compared to many other biometrics. In theexisting biometric authentication system the fingerprinttemplate of a person is stored as such in the authenticationserver, person having age of 60 or more, matching of finger print is quite problematic, so we have suggested a solution in whichif the fingerprint doesn’t match our application prompted for otp, if the otp get matched our camera captured the image of a person and send it to authorized person via mail for authentication that who has entered the otp.If the otp doesn’t get matched an alarm is being triggered. <em> </em> <strong>Keywords- </strong>Fingerprint,Biometric,otp, rfid, webcam,SMTP, pc based
47
Porusu, Ramanaiah, and Kumar Rupak. "RFID BASED SECURITY SYSTEM FOR MARKING ATTENDANCE WITH CAMERA OPTION." International Journal of Advances in Engineering & Scientific Research Vol.4, Issue 4, Jun-2017 (2017): pp 16–24. https://doi.org/10.5281/zenodo.825088.
Full textAbstract:
<strong>Abstract: </strong> Biometrics manages computerized strategy for recognizing a man or checking the personality of a man in light of the physiological or way of acting, as is utilized for verification in a significant number of the exchanges which has been done on the web.Thebiometric for security that has been chosen for implementation isfingerprint, since fingerprint biometric is easily available andhighly reliable compared to many other biometrics. In theexisting biometric authentication system the fingerprinttemplate of a person is stored as such in the authenticationserver, person having age of 60 or more, matching of finger print is quite problematic, so we have suggested a solution in whichif the fingerprint doesn’t match our application prompted for otp, if the otp get matched our camera captured the image of a person and send it to authorized person via mail for authentication that who has entered the otp.If the otp doesn’t get matched an alarm is being triggered.
48
Sheena, S., and Mathew Sheena. "Multimodal Biometric Authentication : Secured Encryption of IRIS Using Fingerprint ID." International Journal on Cryptography and Information Security (IJCIS) 6, no. 3/4 (2018): 1–8. https://doi.org/10.5281/zenodo.1209169.
Full textAbstract:
ABSTRACT Securing data storage using biometrics is the current trend. Different physiological as well as behavioral biometrics like face, fingerprint, iris, Gait, voice etc.. is used in providing security to the data. The proposed work explains about the biometric encryption technology which will securely generate a digital key using two biometric modalities. Iris is encrypted using Fingerprint ID of 32-bit as the key in this work. For encryption Blowfish algorithm is used and the encrypted template is stored in the database and one is given to the user. During the authentication time user input the template and the fingerprint. This template is then decrypted and verified with the original template taken from the database to check whether the user is genuine or an imposter. Hamming distance is used to measure the matching of the templates. CASIA Iris database is used for experimentation and fingerprint images read through the R303 - fingerprint reader.
49
Mashagba, Eman Fares Al. "Human Identification Based on Geometric Feature Extraction Using a Number of Biometric Systems Available: Review." Computer and Information Science 9, no. 2 (2016): 140. http://dx.doi.org/10.5539/cis.v9n2p140.
Full textAbstract:
<span style="font-size: 10.5pt; font-family: 'Times New Roman','serif'; mso-ansi-language: EN-US; mso-bidi-font-size: 12.0pt; mso-fareast-font-family: 宋体; mso-font-kerning: 1.0pt; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">Biometric technology has attracted much attention in biometric recognition. Significant online and offline applications satisfy security and human identification based on this technology. Biometric technology identifies a human based on unique features possessed by a person. Biometric features may be physiological or behavioral. A physiological feature is based on the direct measurement of a part of the human body such as a fingerprint, face, iris, blood vessel pattern at the back of the eye, vascular patterns, DNA, and hand or palm scan recognition. A behavioral feature is based on data derived from an action performed by the user. Thus, this feature measures the characteristics of the human body such as signature/handwriting, gait, voice, gesture, and keystroke dynamics. A biometric system is performed as follows: acquisition, comparison, feature extraction, and matching. The most important step is feature extraction, which determines the performance of human identification. Different methods are used for extraction, namely, appearance- and geometry-based methods. This paper reports on a review of human identification based on geometric feature extraction using several biometric systems available. We compared the different biometrics in biometric technology based on the geometric features extracted in different studies. Several biometric approaches have more geometric features, such as hand, gait, face, fingerprint, and signature features, compared with other biometric technology. Thus, geometry-based method with different biometrics can be applied simply and efficiently. The eye region extracted from the face is mainly used in face recognition. In addition, the extracted eye region has more details as the iris features.</span>
50
Daley, M. S., D. H. Gever, K. H. Chon, H. Posada-Quintero, and J. B. Bolkhovsky. "0055 Physiological Based Predictive Models of Vigilance." Sleep 43, Supplement_1 (2020): A22. http://dx.doi.org/10.1093/sleep/zsaa056.053.
Full textAbstract:
Abstract Introduction The Naval Submarine Medical Research Laboratory (NSMRL) is developing predictive models to examine how non-invasive, non-disruptive physiological monitoring can be used to track performance decrements due to sleep deficiency. Utilizing biometrics extracted from physiological measures to track performance changes would allow for automated tracking of fatigue and alleviate the overhead necessary to monitor individual schedules and sleep patterns. Methods NSMRL collaborated with the University of Connecticut to run a sleep deprivation study that deprived 20 participants of sleep for a period of up to 25 hours. During this time, subjects completed multiple tasks, including the Psychomotor Vigilance Test (PVT) every few hours. A non-invasive monitoring system collected physiological data from participants, which includes eye tracking, electrocardiography, electrodermal activity, and facial tracking (e.g., blink metrics, heart rate variability, skin conductance levels, facial action units). Using this multimodal approach, biometrics were extracted and evaluated to determine their predictive power on PVT performance. Multiple linear regression, using predictors selected via sequential forward selection, was used to develop a model of performance at an individual level based on a subset of these metrics chosen using principal component regression. Results Thirty-eight biometrics were extracted from the collected data and used to produce a predictive model of PVT performance. Sequential forward selection was used to select 11 primary biometrics. The criteria for primary metric inclusion in the model was minimization of root mean squared error. The resultant model had a correlation coefficient (r) of 0.71 (p &lt; 0.001) with a root mean squared error (RMSE) of 49.8 ms between the predicted reaction time and true reaction time for each subject. Conclusion Non-invasive, non-disruptive monitoring could be used to track individual cognitive performance decrement due to sleep deficiency. This study examined the capability of combining the data from four physiological monitors that can be contained within a wrist worn device and a desk or helmet mounted camera. Utilizing 11 biometrics obtained from these monitors a stepwise regression model was developed that significantly correlates with PVT reaction time at both an individual and group level. Support This work was supported by the Military Operational Medicine Research Program.