Relevant bibliographies by topics / Writer authentication

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Writer authentication'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 June 2025

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Journal articles on the topic "Writer authentication"

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Journal, Baghdad Science. "The Writer Authentication by Using Syllables Frequency." Baghdad Science Journal 5, no. 2 (2008): 318–23. http://dx.doi.org/10.21123/bsj.5.2.318-323.

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An approach is depended in the recent years to distinguish any author or writer from other by analyzing his writings or essays. This is done by analyzing the syllables of writings of an author. The syllable is composed of two letters; therefore the words of the writing are fragmented to syllables and extract the most frequency syllables to become trait of that author. The research work depend on analyzed the frequency syllables in two cases, the first, when there is a space between the words, the second, when these spaces are ignored. The results is obtained from a program which scan the syllables in the text file, the performance is best in the first case since the sequence of the selected syllables is higher than the same syllables in the second case.
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Sheikh, Aida, and Hassan Khotanlou. "Writer Identity Recognition and Confirmation Using Persian Handwritten Texts." International Journal of Advances in Applied Sciences 6, no. 2 (2017): 98. http://dx.doi.org/10.11591/ijaas.v6.i2.pp98-105.

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There are many ways to recognize the identity of individuals and authenticate them and the modern world still is looking for unique biometric features of humans. The recognition and authentication of individuals with the help of their handwriting is regarded as a research topic in recent years. It is widely used in the field of security, legal, access control to systems and financial activities. This thesis tries to examines the identification and authentication of individuals in Persian (Farsi) handwritten texts so that the identity of the author can be determined with a handwritten text, and in the authentication problem, with having two handwritten texts, it is determined that whether both manuscripts belong to a specific person or not. The proposed system for recognizing the identity of the author in this study can be divided into two main parts: one part is intended for training and the other for testing. To assess the performance of introduced characteristics, the Hidden Markov Model (HMM) is used as the classifier; thus, a model is defined for each angular characteristic. The defined angular models are connected by a specific chain network to form a comprehensive database for classification. This database is then used to determine and authenticate the author.
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Guo, Wen Zhuo. "An Optimized RFID Unidirectional Authentication Method." Applied Mechanics and Materials 490-491 (January 2014): 1734–38. http://dx.doi.org/10.4028/www.scientific.net/amm.490-491.1734.

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To solve the problems of consumers security and privacy, an optimized RFID unidirectional authentication method is proposed, comparing with other asymmetric cryptography, this method has stronger security, shorter key length, less computation and so on. This method achieves one-way authentication between tag and reader-writer, and allow the labels to automatically update the key to improve the performance of RFID authentication, and also can enhance security through updating keys. This method allows the label to update its own name and private key, so can prevent attackers tracking them, so as to solve the privacy problem of the tags.
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Fang, Lei, Xue Rao, Ling Li, and Huan Li. "A RFID-Based Security Authentication System Model for Electric Vehicle Charging Station." Applied Mechanics and Materials 741 (March 2015): 623–28. http://dx.doi.org/10.4028/www.scientific.net/amm.741.623.

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Improving the efficiency of RFID data storage and ensuring communication security is an effective way to improve the efficiency and safety of the identifying and authenticating process between charging stations and electric vehicles. Considering structure of electric vehicle charging station (EVCS) and the components of RFID system, this paper presents a charging station security authentication system model based on lightweight RFID security protocol using hybrid encryption technology. This protocol participates in the computation and storage through a reader-writer, so that it can store more data than other protocols using the same storage, meanwhile keeping lightweight. To enhance security, a hybrid encryption for RFID is proposed, which is based on public key signature encryption algorithm, hash function and symmetric key algorithm. Analysis demonstrates that this system has great calculating storage performance and security. In addition, it has the ability to resist several typical attacks. Moreover, gate circuits needed to achieve such encryption algorithm is far less than the one used in conventional SHA-256 algorithm.
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Kamal, Parves, Faisal Rahman, and Saad Mustafiz. "A Robust Authentication System Handwritten Documents using Local Features for Writer Identification." Journal of Computing Science and Engineering 8, no. 1 (2014): 11–16. http://dx.doi.org/10.5626/jcse.2014.8.1.11.

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Kumari, Kamlesh, and Sanjeev Rana. "A Robust Approach to Authentication of Handwritten Signature Using Voting Classifier." Journal of Computational and Theoretical Nanoscience 17, no. 9 (2020): 4654–59. http://dx.doi.org/10.1166/jctn.2020.9294.

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This research paper’s main motive is to improve the recognition rate of Offline Signature Verification system. In our research, decisions of three classifiers i.e., Multilayer Perceptron, Random Forest Classifier and Naive Bayes are combined using voting classifier to determine the output. The softwares used for this research are WEKA and Matlab. Performance of this approach is tested on CEDAR dataset for writer dependent model. Overall recognition rate of whole dataset of 55 users is 91.25%. Out of the dataset, the recognition rate of 45 users is above 85%.
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Kerniakevych-Tanasiichuk, Yuliia V., Viktor S. Sezonov, Iryna M. Nychytailo, Maryna A. Savchuk, and Iryna V. Tsareva. "Problems of forensic identification of handwriting in forensic examination." Journal of the National Academy of Legal Sciences of Ukraine 28, no. 1 (2021): 195–204. http://dx.doi.org/10.37635/jnalsu.28(1).2021.195-204.

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The handwritten signature as a characteristic of authentication has been legally and publicly recognised for centuries and has been used in the forensic field for many decades to identify an author. Approaches to biometric user authentication developed in recent years are also based in part on handwriting characteristics, such as automatic signature verification. This article systematically identifies handwriting features published in forensics and analyses which of these properties can be adapted as biometrics to verify the user. A user verification procedure based on a set of 14 forensic characteristics is presented, which is integrated into the biometric verification procedure. The results of the verification of these forensic features are compared in detailed tests with the features of non-forensic data, and it is shown that significant improvements in false detection rates can be achieved by including forensics. For hundreds of years, handwritten signatures have been legally and socially recognised as authentication. The reason for this is the uniqueness of human handwriting. Although a forger with some practice may visually imitate another person’s text or signature, the typical traces resulting from the (studied) behaviour of a victim of forgery are difficult to copy. To check the record, the pressure force of all overlay points with a pen at the beginning or inside the word, written letters on the weight are used. In addition, the way a writer unconsciously or even consciously connects words, letters, or parts of letters to each other is a specific trait for that person. In a forensic examination, experts examine these and other features to prove or disprove the authenticity of signatures or documents. In the field of forensic science, there are many procedures offered based on physical handwriting samples to determine a writer
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Kurowski, Mariusz, Andrzej Sroczyński, Georgis Bogdanis, and Andrzej Czyżewski. "An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks." Electronics 10, no. 4 (2021): 456. http://dx.doi.org/10.3390/electronics10040456.

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Handwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated analysis method for the dynamic electronic representation of handwritten signature authentication was researched. The developed algorithms are based on the dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the designed electronic pen described in the paper. The triplet loss method was used to train a neural network suitable for writer-invariant signature verification. For each signature, the same neural network calculates a fixed-length latent space representation. The hand-corrected dataset containing 10,622 signatures was used in order to train and evaluate the proposed neural network. After learning, the network was tested and evaluated based on a comparison with the results found in the literature. The use of the triplet loss algorithm to teach the neural network to generate embeddings has proven to give good results in aggregating similar signatures and separating them from signatures representing different people.
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Kutzner, Tobias, Carlos Pazmiño-Zapatier, Matthias Gebhard, Ingrid Bönninger, Wolf-Dietrich Plath, and Carlos Travieso. "Writer Identification Using Handwritten Cursive Texts and Single Character Words." Electronics 8, no. 4 (2019): 391. http://dx.doi.org/10.3390/electronics8040391.

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One of the biometric methods in authentication systems is the writer verification/identification using password handwriting. The main objective of this paper is to present a robust writer verification system by using cursive texts as well as block letter words. To evaluate the system, two datasets have been used. One of them is called Secure Password DB 150, which is composed of 150 users with 18 samples of single character words per user. Another dataset is public and called IAM online handwriting database, and it is composed of 220 users of cursive text samples. Each sample has been defined by a set of features, composed of 67 geometrical, statistical, and temporal features. In order to get more discriminative information, two feature reduction methods have been applied, Fisher Score and Info Gain Attribute Evaluation. Finally, the classification system has been implemented by hold-out cross validation and k-folds cross validation strategies for three different classifiers, K-NN, Naïve Bayes and Bayes Net classifiers. Besides, it has been applied for verification and identification approaches. The best results of 95.38% correct classification are achieved by using the k-nearest neighbor classifier for single character DB. A feature reduction by Info Gain Attribute Evaluation improves the results for Naïve Bayes Classifier to 98.34% for IAM online handwriting DB. It is concluded that the set of features and its reduction are a strong selection for the based-password handwritten writer identification in comparison with the state-of-the-art.
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Begum, Nasima, Md Azim Hossain Akash, Sayma Rahman, Jungpil Shin, Md Rashedul Islam, and Md Ezharul Islam. "User Authentication Based on Handwriting Analysis of Pen-Tablet Sensor Data Using Optimal Feature Selection Model." Future Internet 13, no. 9 (2021): 231. http://dx.doi.org/10.3390/fi13090231.

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Handwriting analysis is playing an important role in user authentication or online writer identification for more than a decade. It has a significant role in different applications such as e-security, signature biometrics, e-health, gesture analysis, diagnosis system of Parkinson’s disease, Attention-deficit/hyperactivity disorders, analysis of vulnerable people (stressed, elderly, or drugged), prediction of gender, handedness and so on. Classical authentication systems are image-based, text-dependent, and password or fingerprint-based where the former one has the risk of information leakage. Alternatively, image processing and pattern-analysis-based systems are vulnerable to camera attributes, camera frames, light effect, and the quality of the image or pattern. Thus, in this paper, we concentrate on real-time and context-free handwriting data analysis for robust user authentication systems using digital pen-tablet sensor data. Most of the state-of-the-art authentication models show suboptimal performance for improper features. This research proposed a robust and efficient user identification system using an optimal feature selection technique based on the features from the sensor’s signal of pen and tablet devices. The proposed system includes more genuine and accurate numerical data which are used for features extraction model based on both the kinematic and statistical features of individual handwritings. Sensor data of digital pen-tablet devices generate high dimensional feature vectors for user identification. However, all the features do not play equal contribution to identify a user. Hence, to find out the optimal features, we utilized a hybrid feature selection model. Extracted features are then fed to the popular machine learning (ML) algorithms to generate a nonlinear classifier through training and testing phases. The experimental result analysis shows that the proposed model achieves more accurate and satisfactory results which ensure the practicality of our system for user identification with low computational cost.
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Dissertations / Theses on the topic "Writer authentication"

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Hagström, Adrian, and Rustam Stanikzai. "Writer identification using semi-supervised GAN and LSR method on offline block characters." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-43316.

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Block characters are often used when filling out forms, for example when writing ones personal number. The question of whether or not there is recoverable, biometric (identity related) information within individual digits of hand written personal numbers is then relevant. This thesis investigates the question by using both handcrafted features and extracting features via Deep learning (DL) models, and successively limiting the amount of available training samples. Some recent works using DL have presented semi-supervised methods using Generative adveserial network (GAN) generated data together with a modified Label smoothing regularization (LSR) function. Using this training method might improve performance on a baseline fully supervised model when doing authentication. This work additionally proposes a novel modified LSR function named Bootstrap label smooting regularizer (BLSR) designed to mitigate some of the problems of previous methods, and is compared to the others. The DL feature extraction is done by training a ResNet50 model to recognize writers of a personal numbers and then extracting the feature vector from the second to last layer of the network.Results show a clear indication of recoverable identity related information within the hand written (personal number) digits in boxes. Our results indicate an authentication performance, expressed in Equal error rate (EER), of around 25% with handcrafted features. The same performance measured in EER was between 20-30% when using the features extracted from the DL model. The DL methods, while showing potential for greater performance than the handcrafted, seem to suffer from fluctuation (noisiness) of results, making conclusions on their use in practice hard to draw. Additionally when using 1-2 training samples the handcrafted features easily beat the DL methods.When using the LSR variant semi-supervised methods there is no noticeable performance boost and BLSR gets the second best results among the alternatives.
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Olander, Sahlén Simon. "Feature Analysis in Online Signature Verification on Digital Whiteboard : An analysis on the performance of handwritten signature authentication using local and global features with Hidden Markov models." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-224661.

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The usage of signatures for authentication is widely accepted, and remains one of the most familiar biometric in our society. Efforts to digitalise and automate the verification of these signatures are hot topics in the field of Machine Learning, and a plethora of different tools and methods have been developed and adapted for this purpose. The intention of this report is to study the authentication of handwritten signatures on digital whiteboards, and how to most effectively set up a dual verification system based on Hidden Markov models (HMMs) and global aggregate features such as average speed. The aim is to gauge which features are Suitable for determining that a signature is in fact genuine Suitable for rejecting forgeries Unsuitable for gauging the authenticity of a signature all together In addition, we take a look at the configuration of the HMMs themselves, in order to find good configurations for The number of components used in the model What type of covariance to use The best threshold to draw the line between a genuine signature and a forgery For the research, we collected a total of 200 signatures and 400 forgeries, gathered from 10 different people on digital whiteboards. We concluded that the best configurations of our HMMs had 11 components, used a full covariance model, and observed about five features, where pressure, angle and speed were the most important. Among the global features, we discarded 11 out of 35 due to either strong correlation with other features, or contained too little discriminatory information. The strongest global features were the ones pertaining to speed, acceleration, direction, and curvature. Using the combined verification we obtained an EER of 7 %, which is in the typical range of contemporary studies. We conclude that the best way to combine global feature verification with local HMM verification is to perform both separately, and only accept signatures that are admissible by both, with a tolerance level for the global and local verifications of 1.2 and 2.5 standard deviations, respectively.<br>Användandet av signaturer för autentisering är allmänt accepterat, och är fortfarande den mest använda biometriken i vårt samhälle. Arbetet med att digitalisera och automatisera verifieringen av dessa signaturer är ett populärt ämne inom maskininlärning, och en uppsjö av olika verktyg och metoder har utvecklats och anpassats för detta ändamål. Avsikten med denna studie är att bestämma hur man mest framgångsrikt kan inrätta ett verifikationssystem för handskrivna signatures på digitala whiteboards baserat på dolda Markovmodeller (HMMs) och globalt aggregerade attribut. Syftet är att bedöma vilka features som är Lämpliga för att bestämma huruvida en signatur är äkta Lämpliga för att avvisa förfalskningar Olämpliga för att mäta äktheten hos en signatur över huvud taget Utöver detta studerar vi HMM-konfigurationen själv, i syfte att hitta bra konfigurationer för Antalet komponenter som används i modellen Vilken typ av kovarians som ger bäst resultat Det bästa tröskelvärdet vid vilken att dra gränsen för huruvida en signatur är äkta eller förfalskad För forskningen samlade vi totalt in 200 signaturer och 400 förfalskningar från 10 olika personer med hjälp av digitala whiteboards. Vi drog slutsatsen att de bästa konfigurationerna hade 11 komponenter, använde komplett kovarians, och använde cirka fem features, där tryck, vinkel och hastighet var det viktigaste. Bland våra globala features kastade vi 11 av 35 på grund av att de antingen korrelerade för starkt med andra features, eller på grund av att de innehöll för lite information för att utröna huruvida en signatur var äkta eller ej. Våra bästa globala features var de som hänförde sig till hastighet, acceleration, riktning och krökning. Genom att använda den kombinerade verifieraren fick vi en EER på 7 %, vilket är i linje med liknande studier. Vi drog även slutsatsen att det bästa sättet att kombinera global verifiering med lokal HMM-verifiering är att utföra dem separat och endast acceptera signaturer som godkänns av bägge två. Den bästa toleransnivån för den globala och lokala verifieraren var 1,2 och 2,5 standardavvikelser, respektive.
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Bengtsson, Johnny. "Forensisk hårddiskkloning och undersökning av hårddiskskrivskydd." Thesis, Linköping University, Department of Science and Technology, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2378.

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<p>Detta examensarbete reder ut arbetsprinciperna för olika typer av hårddiskskrivskydd; hårdvaruskrivskydd, mjukvaruskrivskydd, hybridskrivskydd och bygelskrivskydd. Slutsatsen av utredningen är att endast hårdvaruskrivskydd Detta examensarbete reder ut arbetsprinciperna för olika typer av hårddiskskrivskydd; hårdvaruskrivskydd, mjukvaruskrivskydd, hybridskrivskydd och bygelskrivskydd. Slutsatsen av utredningen är att endast hårdvaruskrivskydd bedöms ha tillräckligt pålitliga skyddsprinciper, vilket motiveras av dess oberoende från både hårdvara och operativsystem. </p><p>Vidare undersöks hårdvaruskrivskyddet Image MASSter(TM) Drive Lock från Intelligent Computer Solutions (ICS). Några egentliga slutsatser gick inte dra av kretskonstruktionen, bortsett från att den är uppbyggd kring en FPGA (Xilinx Spartan-II, XC2S15) med tillhörande PROM (XC17S15APC). </p><p>En egenutvecklad idé till autenticieringsmetod för hårddiskkloner föreslås som ett tillägg till arbetet. Principen bygger på att komplettera hårddiskklonen med unik information om hårddisk såväl kloningsomständigheter, vilka sammanflätas genom XOR-operation av komponenternas hashsummor.Autenticieringsmetoden kan vid sjösättning möjligen öka rättsäkerheten för både utredarna och den som står misstänkt vid en brottsutredning. </p><p>Arbetet är till stora delar utfört vid och på uppdrag av Statens kriminaltekniska laboratorium (SKL) i Linköping.</p>
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Books on the topic "Writer authentication"

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French, Derek. 19. Acting for a company: agency and attribution. Oxford University Press, 2018. http://dx.doi.org/10.1093/he/9780198815105.003.0019.

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This chapter deals with the legal relationship of agency that exists between the company and the agent, explaining the process involved in an agent’s authentication and the execution of documents for the company he or she represents. It then considers two ways in which a company may become contractually bound to another person (a ‘contractor’) under the provisions of the Companies Act 2006: through a written contract to which the company’s common seal is affixed, or when someone has made a contract on behalf of the company. It also discusses the company’s capacity to enter into contracts, with emphasis on the ultra vires rule, and attribution by a court so as to impose criminal liability on a company. A number of court cases relevant to the discussion are cited.
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Hinton, David A. Symbols of Power. Edited by Christopher Gerrard and Alejandra Gutiérrez. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744719.013.59.

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Medieval people who had authority acquired it through lineage and success in battle; they symbolized their social positions by display of costume, jewellery, gold and silver plate, weapons, buildings, and funeral monuments. Some of these represented portable wealth that could be used as gifts to create and confirm alliances, and as pledges against loans. Royal power was bestowed at coronations, for which appropriate regalia were needed. Heraldry and coats of arms became increasingly important for those high in the social structure or aspiring to it. Those of lower status might own things made in base metal, pottery, and stone, but whether any of those expressed symbols of resistance to the power of authority is debatable. The need to exercise that authority through the permanency of written documents led to increased use of seals for authentication.
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French, Derek, Stephen W. Mayson, and Christopher L. Ryan. 19. Acting for a company: agency and attribution. Oxford University Press, 2016. http://dx.doi.org/10.1093/he/9780198778301.003.0019.

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This chapter deals with the legal relationship of agency that exists between the company and the agent, explaining the process involved in an agent’s authentication and the execution of documents for the company he or she represents. It then considers two ways in which a company may become contractually bound to another person (a ‘contractor’) under the provisions of the Companies Act 2006: through a written contract to which the company’s common seal is affixed, or when someone has made a contract on behalf of the company. It also discusses the company’s capacity to enter into contracts, with emphasis on the ultra vires rule, and attribution by a court so as to impose criminal liability on a company. A number of court cases relevant to the discussion are cited.
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Book chapters on the topic "Writer authentication"

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Yu, Kun, Yunhong Wang, and Tieniu Tan. "Writer Identification Using Dynamic Features." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_70.

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Tapiador, Marino, and Juan A. Sigüenza. "Writer Identification Method Based on Forensic Knowledge." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_76.

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Hangai, Seiichiro, and Takeshi Higuchi. "Writer Identification Using Finger-Bend in Writing Signature." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25976-3_21.

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Meng, Ming, ZhongCheng Wu, Ping Fang, YunJian Ge, and Yong Yu. "On-line Writer Verification Using Force Features of Basic Strokes." In Advances in Biometric Person Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30548-4_74.

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Jin, Wenfeng, Yunhong Wang, and Tieniu Tan. "Text-Independent Writer Identification Based on Fusion of Dynamic and Static Features." In Advances in Biometric Person Authentication. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11569947_25.

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Brouillette, Sarah. "Zulfikar Ghose and Cosmopolitan Authentication." In Postcolonial Writers in the Global Literary Marketplace. Palgrave Macmillan UK, 2007. http://dx.doi.org/10.1057/9780230288171_6.

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Al-Hamad, Abu Malik Shayba. "Jumbled Words and Authentication for the Important Period Prior to Shaykh Al-Shekawi’s Allegiance Which Made the Umma Happy." In The Boko Haram Reader. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190908300.003.0064.

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(27 MARCH 2015) [Trans.: David Cook] Posted at: https://twitter.com/ifRk23 (suspended) This document is presented as reminiscences by Abu Malik Shayba al-Hamad (@ shaiba_ha) of the Tunisian-based Anṣār al-Sharī‘a, who claims to have facilitated the union between Boko Haram and ISIS. Hamad appears to have been something of a clearing-house in connection with a wide range of West African and European groups, probably because Tunisia during the period 2011–14 allowed freedom to Salafi-jihadis. The document is placed here out of chronological order because it describes events that occurred in 2014 and early 2015. Only selections of the seven-page document are translated here, as the bulk of it concerns other groups in Africa. Note that it was the capture of the Chibok girls which provoked the admiration of the writer, and made him realize that Boko Haram is a truly jihadi group...
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Ayoade, John, and Judith Symonds. "An Evaluation of the RFID Security Benefits of the APF System." In Emerging Pervasive and Ubiquitous Aspects of Information Systems. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-60960-487-5.ch003.

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The main features of RFID are the ability to identify objects without a line of sight between reader and tag, read/write capability and ability of readers to read many tags at the same time. The read/write capability allows information to be stored in the tags embedded in the objects as it travels through a system. Some applications require information to be stored in the tag and be retrieved by the readers. This paper discusses the security and privacy challenges involve in such applications and how the proposed and implemented prototype system Authentication Processing Framework (APF) would be a solution to protect hospital patient data. The deployment of the APF provides mutual authentication for both tags and readers and the mutual authentication process in the APF provides security for the information stored in the tags. A prototype solution for hospital patient data protection for information stored on RFID bracelets is offered.
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Ayoade, John, and Judith Symonds. "An Evaluation of the RFID Security Benefits of the APF System." In Ubiquitous and Pervasive Computing. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-960-1.ch085.

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The main features of RFID are the ability to identify objects without a line of sight between reader and tag, read/write capability and ability of readers to read many tags at the same time. The read/write capability allows information to be stored in the tags embedded in the objects as it travels through a system. Some applications require information to be stored in the tag and be retrieved by the readers. This paper discusses the security and privacy challenges involve in such applications and how the proposed and implemented prototype system Authentication Processing Framework (APF) would be a solution to protect hospital patient data. The deployment of the APF provides mutual authentication for both tags and readers and the mutual authentication process in the APF provides security for the information stored in the tags. A prototype solution for hospital patient data protection for information stored on RFID bracelets is offered.
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Yahya Ebrahim, Anwar, and Hoshang Kolivand. "New Attributes Extraction System for Arabic Autograph as Genuine and Forged through a Classification Techniques." In Pattern Recognition [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.96561.

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The authentication of writers, handwritten autograph is widely realized throughout the world, the thorough check of the autograph is important before going to the outcome about the signer. The Arabic autograph has unique characteristics; it includes lines, and overlapping. It will be more difficult to realize higher achievement accuracy. This project attention the above difficulty by achieved selected best characteristics of Arabic autograph authentication, characterized by the number of attributes representing for each autograph. Where the objective is to differentiate if an obtain autograph is genuine, or a forgery. The planned method is based on Discrete Cosine Transform (DCT) to extract feature, then Spars Principal Component Analysis (SPCA) to selection significant attributes for Arabic autograph handwritten recognition to aid the authentication step. Finally, decision tree classifier was achieved for signature authentication. The suggested method DCT with SPCA achieves good outcomes for Arabic autograph dataset when we have verified on various techniques.
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Conference papers on the topic "Writer authentication"

1

Yu, Kun, Yunhong Wang, and Tieniu Tan. "Writer authentication based on the analysis of strokes." In Defense and Security, edited by Anil K. Jain and Nalini K. Ratha. SPIE, 2004. http://dx.doi.org/10.1117/12.541917.

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2

Al-Shamaileh, Mohammad Z., Ahmad B. Hassanat, Ahmad S. Tarawneh, M. Sohel Rahman, Ceyhun Celik, and Moohanad Jawthari. "New Online/Offline text-dependent Arabic Handwriting dataset for Writer Authentication and Identification." In 2019 10th International Conference on Information and Communication Systems (ICICS). IEEE, 2019. http://dx.doi.org/10.1109/iacs.2019.8809080.

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3

Renuka R, Suganya V, and Arun Kumar B. "Online hand written character recognition using Digital Pen for static authentication." In 2014 International Conference on Computer Communication and Informatics (ICCCI). IEEE, 2014. http://dx.doi.org/10.1109/iccci.2014.6921792.

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4

Radhika, K. R., G. N. Sekhar, and M. K. Venkatesha. "Server-side reconstruction trajectory generation methods for hand written objects authentication - A comparative review." In 2009 International Conference on Multimedia Computing and Systems (ICMCS). IEEE, 2009. http://dx.doi.org/10.1109/mmcs.2009.5256700.

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5

Yang, Jianguo, Xing Li, Tao Wang, et al. "A Physically Unclonable Function with BER < 0.35% for Secure Chip Authentication Using Write Speed Variation of RRAM." In 48th European Solid-State Device Research Conference (ESSDERC 2018). IEEE, 2018. http://dx.doi.org/10.1109/essderc.2018.8486888.

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