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Artykuły w czasopismach na temat „Online forgery”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Bhatia, Shalini, Pratik Bhatia, Dheeraj Nagpal, and Sandhya Nayak. "Online Signature Forgery Prevention." International Journal of Computer Applications 75, no. 13 (2013): 21–29. http://dx.doi.org/10.5120/13172-0849.

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Gaharwar, Gaurav, V. V. Nath, and Raina Gaharwar. "Neuro-Fuzzy Based First Responder for Image Forgery Identification." Oriental journal of computer science and technology 9, no. 1 (2016): 12–16. http://dx.doi.org/10.13005/ojcst/901.03.

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Image forgery is always been sought after field of digital forensics, as it becomes very convenient now to edit/forge any image with many desktop based and online tools available. Also, to prove authenticity of any image in the court of law, there is a need of algorithm which can used to check forgery of any image, irrespective of its forgery type. Proposed model in the paper aims to provide neuro-fuzzy based algorithm which utilizes capabilities of best algorithms for each type and provides accurate result about the forgery in the image. It also provides analysis about type of forgery in the

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Sarhan, M. Musa1. "DIGITAL FORGERY." International Journal of Advances In Scientific Research and Engineering (IJASRE) 3, no. 4 (2017): 26–29. https://doi.org/10.5281/zenodo.581732.

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<em>Forgery is the criminal act that provides misleading information about a product or service. It is the process of making, adapting, or imitating documents or objects with the intent to deceive. Digital forgery (or digital tampering) is the process of manipulating documents or images for the intent of financial, social or political gain. This paper provides a brief introduction to the digital forgery.</em>

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Parashar, Amrita, Dr Arvind Kumar Upadhyay, and Dr Kamlesh Gupta. "A Novel Machine Learning Approach for Forgery Detection and Verification in Digital Image." ECS Transactions 107, no. 1 (2022): 11791–98. http://dx.doi.org/10.1149/10701.11791ecst.

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Image manipulation can cause many ethical, economical, and political issues for everyone. It can be used to create fake information, fake ids, fake online profiles, fake news. A proper technique for image detection and verification is thus, a hot research area, which helps the affected people to overcome the forgery attacks. Due to the increased interaction among people through social networking sites, image forgery is prevalent and it is an essential activity to detect any forged image. This paper’s main objective is to identify fraud or tampered images effectively. By using the methods of co

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Houmani, Nesma, Sonia Garcia-Salicetti, and Bernadette Dorizzi. "On measuring forgery quality in online signatures." Pattern Recognition 45, no. 3 (2012): 1004–18. http://dx.doi.org/10.1016/j.patcog.2011.08.019.

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Chetry, Bhimraj Prasai, and Biswajit Kar. "Kruskal Wallis and mRMR Feature Selection based Online Signature Verification System using Multiple SVM and KNN." International Journal of Experimental Research and Review 42 (August 30, 2024): 298–311. http://dx.doi.org/10.52756/ijerr.2024.v42.026.

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Signature verification is a very important research area. Signature has been widely accepted as a person authentication method for centuries. It is mostly used in financial transactions, document authentication and agreements. It is more susceptible to being forged than any other biometrics. Online signature verification is used in real-time applications like e-commerce, online resource access, online financial transactions, physical access into a restricted area and many more. In order to achieve high efficiency in online signature verification systems, feature extraction and feature selectio

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C, Raghavendra, Ratnam Dodda, Madhu Sake, and Satyanarayana Nimmala. "Advancements in CNN-Based Techniques for Robust Image Forgery Detection: Challenges and Future Directions." E3S Web of Conferences 616 (2025): 02009. https://doi.org/10.1051/e3sconf/202561602009.

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In response to the rise of manipulated images online, which are often obscured by compression and resizing, effective forgery detection systems have become essential. These systems address both social challenges on platforms like Facebook and legal issues stemming from image manipulation. A common form of image tampering, known as copy-move forgery, involves duplicating a part of an image and pasting it elsewhere within the same image. This study presents a novel approach utilizing block processing and feature extraction to tackle the detection challenges posed by such forgeries. By analyzing

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Chen, Guorong, Chongling Du, Yuan Yu, Hong Hu, Hongjun Duan, and Huazheng Zhu. "A Deepfake Image Detection Method Based on a Multi-Graph Attention Network." Electronics 14, no. 3 (2025): 482. https://doi.org/10.3390/electronics14030482.

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Deep forgery detection plays a crucial role in addressing the challenges posed by the rapid spread of deeply generated content that significantly erodes public trust in online information and media. Deeply forged images typically present subtle but significant artifacts in multiple regions, such as in the background, lighting, and localized details. These artifacts manifest as unnatural visual distortions, inconsistent lighting, or irregularities in subtle features that break the natural coherence of the real image. To address these features of forged images, we propose a novel and efficient d

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E, Arun, Deepak S, Prakash T, and K. Ashok kumar. "Video Forgery Detection with Deep Learning Using RESNET and CNN Algorithm." International Research Journal of Computer Science 11, no. 04 (2024): 234–41. http://dx.doi.org/10.26562/irjcs.2024.v1104.17.

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Video forgery is continuously increasing in the digital world due to breaches of information security, consequently establishing a scenario for image and video content monitoring for forgery identification. The spread of fake videos raises security risks and anarchy in society. The reason for video forgery is to the augmentation in the malware, which has facilitated user (anyone) to upload, download, or share objects online comprising audio, images, or video. With the development of technology and ease of creation of fake content, the manipulation of media is carried out on a large scale in re

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GUO, JINHONG KATHERINE, DAVID DOERMANN, and AZRIEL ROSENFELD. "FORGERY DETECTION BY LOCAL CORRESPONDENCE." International Journal of Pattern Recognition and Artificial Intelligence 15, no. 04 (2001): 579–641. http://dx.doi.org/10.1142/s0218001401001088.

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Signatures may be stylish or unconventional and have many personal characteristics that are challenging to reproduce by anyone other than the original author. For this reason, signatures are used and accepted as proof of authorship or consent on personal checks, credit purchases and legal documents. Currently signatures are verified only informally in many environments, but the rapid development of computer technology has stimulated great interest in research on automated signature verification and forgery detection. In this paper, we focus on forgery detection of offline signatures. Although

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Shaik, Bushra, Jyothi Manohar Katikireddy, Vamsidhar Kambham, and K. Sravani. "Offline Signature Verification Using Image Processing." E3S Web of Conferences 391 (2023): 01074. http://dx.doi.org/10.1051/e3sconf/202339101074.

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A person’s signature is merely a handwritten sign that closely resembles his/her name, frequently stylized and distinctive, and that expresses the person’s identity, intent, and consent. Two types of verifications are present. They are online signature verification and offline signature verification. Generally, Offline Signature verification is less efficient and slower process compare to online verification when come to the situation having larger number of documents and files to verify with in less time. Over the years, many researchers have developed so many methods for signature verificati

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S, Gayathri K., and Deepthi P. S. "An Overview of Copy Move Forgery Detection Approaches." Computer Science & Engineering: An International Journal 12, no. 6 (2022): 81–94. http://dx.doi.org/10.5121/cseij.2022.12609.

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Images have greater expressive power than any other forms of documents. With the Internet, images are widespread in several applications. But the availability of efficient open-source online photo editing tools has made editing these images easy. The fake images look more appealing and original than the real image itself, which makes them indistinguishable and hence difficult to detect. The authenticity of digital images like medical reports, scan images, financial data, crime evidence, legal evidence, etc. is of high importance. Detecting the forgery of images is therefore a major research ar

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Xia, Xinghua, and Shuang Wang. "Research on online signature verification based on anomaly detection." Journal of Physics: Conference Series 2031, no. 1 (2021): 012042. http://dx.doi.org/10.1088/1742-6596/2031/1/012042.

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Abstract With the advancement of modern information technology, personal information security has become the focus of social attention. As a biological behavior feature, online signatures have been trained for a long time, have very personal characteristics, and are collected as a real-time sequence. In view of this characteristic, we can know that it is difficult for forgers to imitate the intrinsic and essential characteristics of the signer. In addition, a signature is a rapid writing process driven by the central nervous system and personal writing habits. Even the signer himself may write

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Wu, Haiwei, Jiantao Zhou, Jinyu Tian, Jun Liu, and Yu Qiao. "Robust Image Forgery Detection Against Transmission Over Online Social Networks." IEEE Transactions on Information Forensics and Security 17 (2022): 443–56. http://dx.doi.org/10.1109/tifs.2022.3144878.

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Bakhteev, D. V. "Features of Signature Verification By a Person as a Primary Criteria for Developing an Artificial Intelligence System." Siberian Law Review 17, no. 4 (2020): 514–22. http://dx.doi.org/10.19073/2658-7602-2020-17-4-514-522.

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The modern capabilities of computers have returned interest in artificial intelligence technologies. A particular area of application of these technologies is pattern recognition, which can be applied to the traditional forensic task – identification of signs of forgery (imitation) of a signature. The results of forgery are differentiated into three types: auto-forgery, simple and skilled forgeries. Only skilled forgeries are considered in this study. The online and offline approaches to the study of signatures and other handwriting material are described. The developed artificial intelligence

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Bakhteev, D. V. "Features of Signature Verification By a Person as a Primary Criteria for Developing an Artificial Intelligence System." Siberian Law Review 17, no. 4 (2020): 514–22. http://dx.doi.org/10.19073/2658-7602-2020-17-4-514-522.

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The modern capabilities of computers have returned interest in artificial intelligence technologies. A particular area of application of these technologies is pattern recognition, which can be applied to the traditional forensic task – identification of signs of forgery (imitation) of a signature. The results of forgery are differentiated into three types: auto-forgery, simple and skilled forgeries. Only skilled forgeries are considered in this study. The online and offline approaches to the study of signatures and other handwriting material are described. The developed artificial intelligence

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Nidhi, Gajimwar Ashmi Dahiwale Isha Walde Shyamal Dhabarde Prof. Monika Walde. "Automated Image Forgery Detection With Python." International Journal of Advanced Innovative Technology in Engineering 9, no. 3 (2024): 133–38. https://doi.org/10.5281/zenodo.12516039.

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Fake image detection has become increasingly important due to the widespread use of image editing software and the proliferation of fake images on social media and other online platforms. In this project, we propose a Python-based approach for detecting fake images using deep learning techniques. Our method involves preprocessing the images, extracting relevant features using convolutional neural networks (CNNs), and training a classifier to distinguish between real and fake images. We leverage state-of-the-art deep learning frameworks such as TensorFlow or PyTorch for model development and ev

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Manoj Chavan. "Handwritten online signature verification and Forgery Detection for Online Handwritten Signature using Hybrid Wavelet Transform-1 with HMM classifier." Journal of Electrical Systems 20, no. 4s (2024): 2471–78. http://dx.doi.org/10.52783/jes.2800.

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Online signature verification employs a distinctive biometric trait by utilizing both static and dynamic features extracted from 2D signature images. A hybrid wavelet transform, denoted as HWT-1 with a size of 256, is formed through the Kronecker product of two orthogonal transforms, such as DCT, DHT, Haar, Hadamard, and Kekre, each with sizes 4 and 64. This HWT facilitates signal analysis at both global and local levels, akin to traditional wavelet transforms. Specifically, HWT-1 processes the 256 samples of online handwritten signatures, yielding 128 samples that constitute the feature vecto

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Sohaib, Muhammad, and Samabia Tehseen. "Forgery detection of low quality deepfake videos." Neural Network World 33, no. 2 (2023): 85–99. http://dx.doi.org/10.14311/nnw.2023.33.006.

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The rapid growth of online media over different social media platforms or over the internet along with many benefits have some negative effects as well. Deep learning has many positive applications like medical, animations and cybersecurity etc. But over the past few years, it is observed that it is been used for negative aspects as well such as defaming, black-mailing and creating privacy concerns for the general public. Deepfake is common terminology used for facial forgery of a person in media like images or videos.The advancement in the forgery creation area have challenged the researchers

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CHA, SUNG-HYUK, CHARLES C. TAPPERT, MICHAEL GIBBONS, and YI-MIN CHEE. "AUTOMATIC DETECTION OF HANDWRITING FORGERY USING A FRACTAL NUMBER ESTIMATE OF WRINKLINESS." International Journal of Pattern Recognition and Artificial Intelligence 18, no. 07 (2004): 1361–71. http://dx.doi.org/10.1142/s0218001404003642.

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We investigate the detection of handwriting forged by novices. To facilitate document examination it is important to develop an automated system to identify forgeries, or at least to identify those handwritings that are likely to be forged. Because forgers often carefully copy or trace genuine handwriting, we hypothesize that good forgeries — those that retain the shape and size of genuine writing — are usually written more slowly and are therefore wrinklier (less smooth) than genuine writing. From online handwriting samples we find that the writing speed of the good forgeries is significantly

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Gautam, Shikha, and Anand Singh Jalal. "An Image Forgery Detection Approach Based on Camera's Intrinsic Noise Properties." International Journal of Computer Vision and Image Processing 8, no. 1 (2018): 92–101. http://dx.doi.org/10.4018/ijcvip.2018010106.

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Digital images are found everywhere from cell phones to the pages of online news sites. With the rapid growth of the Internet and the popularity of digital image capturing devices, images have become major source of information. Now-a-days fudge of images has become easy due to powerful advanced photo-editing software and high-resolution cameras. In this article, the authors present a method for detecting forgery, which is detected by estimating camera's intrinsic noise properties. Differences in noise parameters of the image are used as evidence of Image tampering. The method works in two ste

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Kurniasih, Nuning. "Literasi Media Sosial: Upaya Pencegahan Pemalsuan Identitas Digital." JPM: Jurnal Pengabdian Masyarakat 4, no. 1 (2023): 7–13. http://dx.doi.org/10.47065/jpm.v4i1.1051.

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The increase in internet usage has led to an increase in cybercrime. One of the crimes in cyberspace is caused by online impersonation. In these conditions, it is important to socialize social media literacy, especially in an effort to prevent digital identity fraud. The purpose of this community service activity is to equip the community with social media literacy in order to avoid the dangers of social media misuse, especially those caused by impersonation or digital identity forgery. The problem was analyzed by reviewing phenomena, news and research findings on social media misuse and crime

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Alisultanova, Izaura A., and Deni Kh Dzhabrailov. "WEB APPLICATION SECURITY AND METHODS FOR PREVENTING HACKER ATTACKS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 3/3, no. 156 (2025): 35–42. https://doi.org/10.36871/ek.up.p.r.2025.03.03.005.

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The article discusses key issues of web application security and methods of protection against hacker attacks. With businesses increasingly dependent on online services, web application security is becoming one of the top priorities for organizations. Sufficient attention should be paid to security measures to protect user data from unwanted access and malicious use. This article reviewed the main types of hacker attacks on web applications, such as SQL injection (SQLi), Cross-site scripting (XSS), Cross-site request forgery (CSRF), Server-side request forgery (SSRF) and file attacks, as well

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Gadekar,, Supriya S. "Roadmap for Digital Image Forgery Detection Using Deep Learning." Tuijin Jishu/Journal of Propulsion Technology 44, no. 5 (2023): 1732–48. http://dx.doi.org/10.52783/tjjpt.v44.i5.2849.

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Technology advances are prominent today while influencing all aspects of our lives. Misuse of information has also increased as a result of technical improvements. As a result, investigators have the enormous task of recognizing modified information and distinguishing this from genuine data. Among the most prevalent techniques for electronic image alteration is splicing, which includes replicating a specific section using the same or different photograph and transferring it to a new image. In the wake of this issue, picture identification of forgeries has arisen as a viable approach for confir

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Patil, Sonal Pramod, and K. N. Jariwala. "Improving the Efficiency of Image and Video Forgery Detection Using Hybrid Convolutional Neural Networks." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 29, Supp01 (2021): 101–17. http://dx.doi.org/10.1142/s0218488521400067.

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Recently, on the internet, the level of image and video forgery has augmented due to the augmentation in the malware, which has facilitated user (anyone) to upload, download, or share objects online comprising audio, images, or video. Recently, Convolution Neural Network (CNN) has turn into a de-facto technique for classification of multi-dimensional data and it renders standard and also highly effectual network layer arrangements. But these architectures are limited by the speed due to massive number of calculations needed for training in addition to testing the network and also, it might ren

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Haval Sadiq, Bareen. "Image Splicing Forgery Detection using Standard Division-Local Binary Pattern Features." Academic Journal of Nawroz University 12, no. 3 (2023): 35–41. http://dx.doi.org/10.25007/ajnu.v12n3a1839.

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Numerous aspects of daily life contribute to societal stability, and the security of people's perceptions of the world online is one target of various malicious attacks. Professional forgers can now quickly create copy-move, splice, or retouch photos with the use of today's advanced tools. It has been determined that splicing, is a widespread method of manipulating images. Image forgery can also lead to substantial setbacks and challenges, some of which may have significant ethical, moral, or legal consequences. Thus, the paper proposes a system that combines SD-LBP (Standard Devision-Local Bi

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Cherniavskyi, Serhii, Viktoria Babanina, Inna Vartyletska, and Oleksandr Mykytchyk. "Peculiarities of The Economic Crimes Committed with the Use of Information Technologies." European Journal of Sustainable Development 10, no. 1 (2021): 420. http://dx.doi.org/10.14207/ejsd.2021.v10n1p420.

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The article looks into peculiarities of the economic crimes committed using information technologies. Different approaches to the concept of the economic crime are analyzed to reveal types of economic crimes, which can be committed with the use of information technologies. It is stated that mostly two types of economic crimes could be committed using information technologies – online fraud and forgery. Subjects and objects of a forgery committed with the use of information technologies are analyzed. Close attention is paid to the online fraud and its specific features. The classification of ty

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DAVID, Mihail, and Igor SOROCEANU. "Negative effects of legal forgery on legal sciences." Anale ştiinţifice ale Academiei "Ştefan cel Mare" a MAI al Republicii Moldova. Ştiinţe juridice=Scientific Annals of the Academy "Stefan cel Mare" of MIA of the Republic of Moldova. Legal Sciences 17 (September 6, 2023): 228–38. https://doi.org/10.5281/zenodo.8321004.

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The phenomenon of plagiarism is a current and common one in the scientific-academic community. It has a different weight of manifestation in each person. Sometimes, with regret, the author of an ,,allegedly new” work directly or indirectly appeals to this activity for vast reasons. The current legislation does not provide for a legal norm that would directly sanction the form of manifestation of plagiarism actions. However, currently, there are numerous methods and tools, some even online and free, to detect plagiarism, but some authors continue to tolerate these illegalities. The one wh

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Manoj Chavan. "Handwritten Online Signature Verification and Forgery Detection Using Hybrid Wavelet Transform-2 with HMM Classifier." Journal of Electrical Systems 20, no. 4s (2024): 2463–70. http://dx.doi.org/10.52783/jes.2799.

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Online signature verification stands out as a distinctive biometric feature, offering both static and dynamic attributes within 2D signature images. A Hybrid Wavelet Transform-2 (HWT-2) with a size of 256 is constructed by employing the Kronecker product of two orthogonal transforms: DCT, DHT, Haar, Hadamard, and Kekre, each with sizes of 4 and 64. The HWT enables the analysis of signals at both global and local levels, akin to wavelet transforms. HWT-2 is applied to 256 samples of online handwritten signatures, and the first 128 samples of the output are utilized as feature vectors for the ve

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Y. F. Al_Sahlani, Ahmed, and Songfeng Lu. "Lightweight Communication Overhead Authentication Scheme Using Smart Card." Indonesian Journal of Electrical Engineering and Computer Science 1, no. 3 (2016): 597. http://dx.doi.org/10.11591/ijeecs.v1.i3.pp597-606.

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<p>Authentication takes its place to grant authorized user a remote access to certain online resources. As well, prevent unauthorized user from accessing that resources. Unforyunatly most of authentication schemes consider only security factors without taking in consideration the communication resources required. Recently, Li et. al. proposed an enhanced smart card based remote user password authentication scheme. We analyzed their scheme and we pointed out that, their scheme required high communication overhead. Furthermore, their scheme suffer from forgery, user impersonation and serve

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Rabpreet, Singh Keer Rabpreet Singh Keer. "Handwriting generation using recurrent neural networks (LSTM)." International Journal of Scientific Development and Research 8, no. 9 (2023): 1085–109. https://doi.org/10.5281/zenodo.10446335.

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Handwriting is a skill developed by humans from a very early stage in order to represent his/her thoughts visually using letters and making meaningful words and sentences. Every person improves this skill by practicing and developing his/her own style of writing. Because of the distinctiveness of handwriting style, it is frequently used as a measure to identify a forgery.  Even though the applications of synthesizing handwriting is less, this problem can be generalized and can be functionally applied to other more practical problems. Mimicking or imitating a specific handwriting style can

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Zhang, Yihui. "Empowering college students with personal privacy protection and anti-fraud on the internet: A comprehensive learning approach." Applied and Computational Engineering 74, no. 1 (2024): 7–12. http://dx.doi.org/10.54254/2755-2721/74/20240421.

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As college students increasingly navigate their academic pursuits and social lives through the digital realm, safeguarding personal privacy on the internet becomes a pressing concern. For example, deep forgery technology has further increased personal privacy concerns. This technique can produce fake videos, pictures, and sounds that are highly realistic, making it a tool for the misuse of personal and sound data. Several artificial intelligences (AI) systems require large amounts of data for training and improvement, which can involve collecting and storing sensitive personal information. If

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V K, Vishwanath. "Advanced Algorithms for Offline Signature Recognition and Enhanced Forgery Detection Mechanisms." International Journal for Research in Applied Science and Engineering Technology 12, no. 10 (2024): 573–77. http://dx.doi.org/10.22214/ijraset.2024.64585.

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In contemporary society, signatures hold significant importance in various critical documents such as bank cheques, passports, and driver's licenses. Unfortunately, they can be counterfeited through various means, giving rise to issues like fraudulent identifications, identity theft, and cyber-attacks. To mitigate this problem, our project is centered around the development of a system that discerns the authenticity of a signature, distinguishing between genuine and forged signatures within a dataset. We have employed Convolutional Neural Networks (CNN) and deep learning for this purpose. This

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Manoj Chavan. "Comparative Analysis of Handwritten Online Signature Verification and Forgery Detection Using Hybrid Wavelet Transform-1 and 2 with HMM Classifier." Journal of Electrical Systems 20, no. 4s (2024): 2453–62. http://dx.doi.org/10.52783/jes.2798.

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Online signature verification is a unique biometric feature. Provides static and dynamic features for 2D signature images. Hybrid wavelet transform -1 and 2 (HWT-1 and HWT-2) of size 256 is created using the Kronecker product of two orthogonal transforms such as DCT, DHT, Haar, Hadamard and Kekre with size 4 and 64. HWT has the ability to analyze signals such as wavelet transform at global and local levels. HWT-1 and HWT-2 are used for the 256 samples of the online Handwritten signature and the first 128 samples of the output are used as feature vectors for handwritten online signature verific

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Lu, Jiaxin, Hengnian Qi, Xiaoping Wu, Chu Zhang, and Qizhe Tang. "Research on Authentic Signature Identification Method Integrating Dynamic and Static Features." Applied Sciences 12, no. 19 (2022): 9904. http://dx.doi.org/10.3390/app12199904.

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In many fields of social life, such as justice, finance, communication and so on, signatures are used for identity recognition. The increasingly convenient and extensive application of technology increases the opportunity for forged signatures. How to effectively identify a forged signature is still a challenge to be tackled by research. Offline static handwriting has a unique structure and strong interpretability, while online handwriting contains dynamic information, such as timing and pressure. Therefore, this paper proposes an authentic signature identification method, integrating dynamic

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Yassen A. AlKarem, Wijdan, Eman Thabet Khalid, and Khawla H. Ali. "Handwritten Signature Verification Method Using Convolutional Neural Network." Iraqi Journal for Electrical and Electronic Engineering 20, no. 2 (2024): 77–84. http://dx.doi.org/10.37917/ijeee.20.2.7.

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Automatic signature verification methods play a significant role in providing a secure and authenticated handwritten signature in many applications, to prevent forgery problems, specifically institutions of finance, and transections of legal papers, etc. There are two types of handwritten signature verification methods: online verification (dynamic) and offline verification (static) methods. Besides, signature verification approaches can be categorized into two styles: writer dependent (WD), and writer independent (WI) styles. Offline signature verification methods demands a high representatio

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Ibtisam, Ibtisam, Sharifah Mumtazah Syed Ahmad, Syamsiah Bt Mashohor, and Marsyita Bt Hanafi. "A Review of Online Signature Recognition system." Fusion: Practice and Applications 18, no. 1 (2025): 130–44. https://doi.org/10.54216/fpa.180111.

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Biometrics has reached an important place in the field of authentication for both financial transactions and document verification. Signatures can be broadly classified into online and offline types, depending on how they are acquired. Captured through devices like tablets and digital pens, online signatures contain rich features concerning position, velocity, and acceleration; hence, they offer a better resistance to forgery compared to offline, more traditionally taken signatures. The review summarized the current research in online signature verification systems. There are methodologies and

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Wardhana, Andhika Wisnu, and Henki Bayu Seta. "Analisis Keamanan Sistem Pembelajaran Online Menggunakan Metode ISSAF pada Website Universitas XYZ." Informatik : Jurnal Ilmu Komputer 17, no. 3 (2021): 226. http://dx.doi.org/10.52958/iftk.v17i3.3653.

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Website e-learning Universitas XYZ adalah suatu aplikasi yang mudah digunakan dimanapun dan kapanpun hanya dengan menggunakan browser, baik melalui smartphone maupun komputer. E-learning menyimpan data-data mahasiswa berupa tugas, quiz, dan lain-lain. Dikarenakan krusialnya penggunaan website tersebut, untuk mengantisipasi ancaman-ancaman terhadap website e-learning Universitas XYZ, maka peneliti akan melakukan pengujian terhadap keamanan website e-learning Universitas XYZ. Pengujian keamanan website dilakukan dengan menggunakan metode Web Penetration Testing. Framework yang digunakan dalam pe

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Damini, Singh*1 Neeti Misra2 &. Farman Ali3. "ANALYSIS OF DMAT A/C & ONLINE TRADING OF INDIABULLS LTD. IN DEHRADUN." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 6, no. 4 (2019): 481–84. https://doi.org/10.5281/zenodo.2657670.

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Dematerialization is the process of converting the physical form of shares into electronic form. Prior to dematerialization the Indian stock markets have faced several problems like delay in the Transfer of certificates, forgery of certificates etc. Dematerialization helps to overcome these problems as well as reduces the transaction time as compared to the physical segment. The article discusses the procedures, advantages and problems of dematerialization. The Indian Stock markets have seen a major change with the introduction of depository system and scrip less trading mechanism. In India, s

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Safitri, Nandila Puspavidya. "Application of the Precautionary Principle of Notary in Making Authentic Deed Against the Use of False Identity." As-Syar'i: Jurnal Bimbingan & Konseling Keluarga 6, no. 2 (2024): 2165–79. http://dx.doi.org/10.47467/as.v6i2.6986.

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The increase in cases of identity forgery in notarial deeds is due to the lack of caution and thoroughness on the part of the notary regarding the identity submitted by the confrontants, thus providing opportunities for other parties who have bad intentions to manipulate information. The occurrence of identity forgery cases shows that the notary lacks careful and thorough examination of the information provided by the notary. Weaknesses in the identity verification process can result in the cancellation of the deed and harm the parties involved in the agreement, including the notary as the dee

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Mehta, Rachna, Karan Aggarwal, Deepika Koundal, Adi Alhudhaif, and Kemal Polat. "Markov features based DTCWS algorithm for online image forgery detection using ensemble classifier in the pandemic." Expert Systems with Applications 185 (December 2021): 115630. http://dx.doi.org/10.1016/j.eswa.2021.115630.

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Kim, Seong-Kyu. "Blockchain Smart Contract to Prevent Forgery of Degree Certificates: Artificial Intelligence Consensus Algorithm." Electronics 11, no. 14 (2022): 2112. http://dx.doi.org/10.3390/electronics11142112.

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Certificates are often falsified, such as fake diplomas and forged transcripts. As such, many schools and educational institutions have begun to issue diplomas online. Although diplomas can be issued conveniently anytime, anywhere, there are many cases wherein diplomas are forged through hacking and forgery. This paper deals with the required Blockchain diploma. In addition, we use an automatic translation system, which incorporates natural language processing, to perform verification work that does not require an existing public certificate. The hash algorithm is used to authenticate security

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I, Gusti Ayu Andara Yadnya Sangaswary, Kasta Arya Wijaya Ketut, and Ayu Sriasih Wesna Putu. "Authentication of Electronic Signatures in Online Business Transactions." International Journal of Social Science and Human Research 08, no. 05 (2025): 2664–69. https://doi.org/10.5281/zenodo.15347797.

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Technological developments have driven digitalization in online business transactions, including the use of electronic signatures (ETS) as a substitute for conventional signatures. Although ETS have been legally recognized in the Electronic Information and Transactions Law (UU ITE), there is still debate regarding their authentication, legal force, and legal protection. This study aims to analyze the authentication regulations and legal force of ETS from the perspective of positive Indonesian law using normative methods through legislative and conceptual approaches. The results of the study sh

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Ahmed, Ahmed. "Development of an Approach for Image Forgery Detection Using Machine Learning Algorithms." Journal of Intelligent Systems and Internet of Things 12, no. 2 (2024): 166–77. http://dx.doi.org/10.54216/jisiot.120212.

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Digital picture fraud detection is an increasing societal necessity due to the importance of verified images. The detection of picture copying, splicing, retouching, and re-sampling forgeries is included. In the absence of digital signatures or watermarks, passive picture authentication may serve as an alternative to active authentication. Passive techniques, every so often recognized as blind techniques, could take place without preceding knowledge of the picture or its reference. Identifying counterfeiting picture or tampering was a research field for long a period of time, triggered via the

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Vishal, Vadgama. "A Novel Approach for E-Payment Using Virtual Password System." International Journal on Cryptography and Information Security(IJCIS) 1, no. 1 (2020): 1–11. https://doi.org/10.5281/zenodo.3901134.

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In today's world of E-Commerce everything comes online like Music,E-Books, Shopping all most everything is online. If you are using some service or buying things online then you have to pay for that. For that you have to do Net Banking or you have to use Credit card which will do online payment for you. In today's environment when everything is online, the service you are using for E-Payment must be secure and you must protect your banking information like debit card or credit card information from possible threat of hacking. There were lots way to threat like Key logger, Forgery Detec

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Yagvalya, Gaurav. "A Novel Method of Fake Signature Detection Using Deep Learning Techniques." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem33985.

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In today's digital world, making sure signatures are real is super important. Sometimes, though, people fake signatures, causing problems for money and legal stuff. This research looks into fixing this issue by finding a new way to catch fake signatures. We know that nowadays, a lot of things happen online, like signing documents and doing money stuff, and we need to make sure signatures are real. This paper introduces a fresh perspective by leveraging Convolutional Neural Networks (CNN), a deep learning technique. The objective is to enable the CNN model to autonomously learn and distinguish

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Guo, Jianbang, Peng Sun, and Sang-Bing Tsai. "A Study on the Optimization Simulation of Big Data Video Image Keyframes in Motion Models." Wireless Communications and Mobile Computing 2022 (March 16, 2022): 1–12. http://dx.doi.org/10.1155/2022/2508174.

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In this paper, the signal of athletic sports video image frames is processed and studied according to the technology of big data. The sports video image-multiprocessing technology achieves interference-free research and analysis of sports technology and can meet multiple visual needs of sports technology analysis and evaluation through key technologies such as split-screen synchronous comparison, superimposed synchronous comparison, and video trajectory tracking. The sports video image-processing technology realizes the rapid extraction of key technical parameters of the sports scene, the pano

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Satybaldy, Abylay, Anushka Subedi, and Mariusz Nowostawski. "A Framework for Online Document Verification Using Self-Sovereign Identity Technology." Sensors 22, no. 21 (2022): 8408. http://dx.doi.org/10.3390/s22218408.

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As the world is gradually moving towards digitization, forgery of vital digital documents has become relatively easy. Therefore, the need for efficient and secure verification and authentication practices of digital documents is also increasing. Self-sovereign identity (SSI) is a set of technologies that build on core concepts in identity management, blockchain technology, and cryptography. SSI enables entities to create fraud-proof verifiable credentials and instantly verify the authenticity of a digital credential. The online document verification solutions must deal with a myriad of issues

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Liu, Rui, Jun Song, Zhiming Huang, and Jianping Pan. "EQRC: A secure QR code-based E-coupon framework supporting online and offline transactions1." Journal of Computer Security 28, no. 5 (2020): 577–605. http://dx.doi.org/10.3233/jcs-191416.

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In recent years, with the rapid development and popularization of e-commerce, the applications of e-coupons have become a market trend. As a typical bar code technique, QR codes can be well adopted in e-coupon-based payment services. However, there are many security threats to QR codes, including the QR code tempering, forgery, privacy information leakage and so on. To address these security problems for real situations, in this paper, we introduce a novel fragment coding-based approach for QR codes using the idea of visual cryptography. Then, we propose a QR code scheme with high security by

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Al-Rawy, Mahmoud, and Atilla Elci. "Secure i-Voting Scheme with Blockchain Technology and Blind Signature." Journal of Digital Science, no. 1 (December 22, 2019): 3–14. http://dx.doi.org/10.33847/2686-8296.1.1_1.

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In the last four years, blockchain technology affected largely all aspects of our lives. Blockchain started to launch a new technological revolution of storing digital transactions over the Internet, verifying the authenticity, licensing and providing the highest degree of security and encryption. Blockchain usage started with digital currency then its implementation extended to many industries such as voting, health records, copywriters, real estates and so on. However, it is time to upgrade the election scenario from practicing paper-based elections to use modern technologies in order to fac

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