A Survey of Machine Learning Techniques for Behavioral-Based Biometric User Authentication

Authentication is a way to enable an individual to be uniquely identified usually based on passwords and personal identification number (PIN). The main problems of such authentication techniques are the unwillingness of the users to remember long and challenging combinations of numbers, letters, and symbols that can be lost, forged, stolen, or forgotten. In this paper, we investigate the current advances in the use of behavioral-based biometrics for user authentication. The application of behavioral-based biometric authentication basically contains three major modules, namely, data capture, feature extraction, and classifier. This application is focusing on extracting the behavioral features related to the user and using these features for authentication measure. The objective is to determine the classifier techniques that mostly are used for data analysis during authentication process. From the comparison, we anticipate to discover the gap for improving the performance of behavioral-based biometric authentication. Additionally, we highlight the set of classifier techniques that are best performing for behavioral-based biometric authentication

Leveraging Expert Models for Training Deep Neural Networks in Scarce Data Domains: Application to Offline Handwritten Signature Verification

This paper introduces a novel approach to leverage the knowledge of existing expert models for training new Convolutional Neural Networks, on domains where task-specific data are limited or unavailable. The presented scheme is applied in offline handwritten signature verification (OffSV) which, akin to other biometric applications, suffers from inherent data limitations due to regulatory restrictions. The proposed Student-Teacher (S-T) configuration utilizes feature-based knowledge distillation (FKD), combining graph-based similarity for local activations with global similarity measures to supervise student's training, using only handwritten text data. Remarkably, the models trained using this technique exhibit comparable, if not superior, performance to the teacher model across three popular signature datasets. More importantly, these results are attained without employing any signatures during the feature extraction training process. This study demonstrates the efficacy of leveraging existing expert models to overcome data scarcity challenges in OffSV and potentially other related domains

An examination of quantitative methods for Forensic Signature Analysis and the admissibility of signature verification system as legal evidence.

The experiments described in this thesis deal with handwriting characteristics which are involved in the production of forged and genuine signatures and complexity of signatures. The objectives of this study were (1) to provide su?cient details on which of the signature characteristics are easier to forge, (2) to investigate the capabilities of the signature complexity formula given by Found et al. based on a different signature database provided by University of Kent. This database includes the writing movements of 10 writers producing their genuine signature and of 140 writers forging these sample signatures. Using the 150 genuine signatures without constrictions of the Kent’s database an evaluation of the complexity formula suggested in Found et al took place divided the signature in three categories low, medium and high graphical complexity. The results of the formula implementation were compared with the opinions of three leading professional forensic document examiners employed by Key Forensics in the UK. The analysis of data for Study I reveals that there is not ample evidence that high quality forgeries are possible after training. In addition, a closer view of the kinematics of the forging writers is responsible for our main conclusion, that forged signatures are widely different from genuine especially in the kinematic domain. From all the parameters used in this study 11 out of 15 experienced significant changes when the comparison of the two groups (genuine versus forged signature) took place and gave a clear picture of which parameters can assist forensic document examiners and can be used by them to examine the signatures forgeries. The movements of the majority of forgers are signi?cantly slower than those of authentic writers. It is also clearly recognizable that the majority of forgers perform higher levels of pressure when trying to forge the genuine signature. The results of Study II although limited and not entirely consistent with the study of Found that proposed this model, indicate that the model can provide valuable objective evidence (regarding complex signatures) in the forensic environment and justify its further investigation but more work is need to be done in order to use this type of models in the court of law. The model was able to predict correctly only 53% of the FDEs opinion regarding the complexity of the signatures. Apart from the above investigations in this study there will be also a reference at the debate which has started in recent years that is challenging the validity of forensic handwriting experts’ skills and at the effort which has begun by interested parties of this sector to validate and standardise the field of forensic handwriting examination and a discussion started. This effort reveals that forensic document analysis field meets all factors which were set by Daubert ruling in terms of theory proven, education, training, certification, falsifiability, error rate, peer review and publication, general acceptance. However innovative methods are needed for the development of forensic document analysis discipline. Most modern and effective solution in order to prevent observational and emotional bias would be the development of an automated handwriting or signature analysis system. This system will have many advantages in real cases scenario. In addition the significant role of computer-assisted handwriting analysis in the daily work of forensic document examiners (FDE) or the judicial system is in agreement with the assessment of the National Research Council of United States that “the scientific basis for handwriting comparison needs to be strengthened”, however it seems that further research is required in order to be able these systems to reach the accomplishment point of this objective and overcome legal obstacles presented in this study

The offline digital currency puzzle solved by a local blockchain

A major drawback in deploying central bank digital currencies (CDBC) is the offline puzzle, which requires that a CBDC must keep the provision given by cash, and, simultaneously, avoid double-spending, counterfeiting, and other issues. The puzzle is solved by minting the coins in serials, which are stored on a local blockchain (e.g. smartphone). The local blockchain is secured by keys embedded in the hardware and can be continuously mined by the wallet to enhance security. The coins can be either minted as hot coins, which can be retrieved in case of loss, or minted as cold coins, like physical cash.Comment: 20 pages, 2 tables and 2 figure

Building a Strong Undergraduate Research Culture in African Universities

Africa had a late start in the race to setting up and obtaining universities with research quality fundamentals. According to Mamdani [5], the first colonial universities were few and far between: Makerere in East Africa, Ibadan and Legon in West Africa. This last place in the race, compared to other continents, has had tremendous implications in the development plans for the continent. For Africa, the race has been difficult from a late start to an insurmountable litany of problems that include difficulty in equipment acquisition, lack of capacity, limited research and development resources and lack of investments in local universities. In fact most of these universities are very recent with many less than 50 years in business except a few. To help reduce the labor costs incurred by the colonial masters of shipping Europeans to Africa to do mere clerical jobs, they started training ―workshops‖ calling them technical or business colleges. According to Mamdani, meeting colonial needs was to be achieved while avoiding the ―Indian disease‖ in Africa -- that is, the development of an educated middle class, a group most likely to carry the virus of nationalism. Upon independence, most of these ―workshops‖ were turned into national ―universities‖, but with no clear role in national development. These national ―universities‖ were catering for children of the new African political elites. Through the seventies and eighties, most African universities were still without development agendas and were still doing business as usual. Meanwhile, governments strapped with lack of money saw no need of putting more scarce resources into big white elephants. By mid-eighties, even the UN and IMF were calling for a limit on funding African universities. In today‘s African university, the traditional curiosity driven research model has been replaced by a market-driven model dominated by a consultancy culture according to Mamdani (Mamdani, Mail and Guardian Online). The prevailing research culture as intellectual life in universities has been reduced to bare-bones classroom activity, seminars and workshops have migrated to hotels and workshop attendance going with transport allowances and per diems (Mamdani, Mail and Guardian Online). There is need to remedy this situation and that is the focus of this paper

Future Security Approaches and Biometrics

Threats to information security are proliferating rapidly, placing demanding requirements on protecting tangible and intangible business and individual assets. Biometrics can improve security by replacing or complementing traditional security technologies. This tutorial discusses the strengths and weaknesses of biometrics and traditional security approaches, current and future applications of biometrics, performance evaluation measures of biometric systems, and privacy issues surrounding the new technology

Dynamic signatures: A review of dynamic feature variation and forensic methodology

This article focuses on dynamic signatures and their features. It provides a detailed and critical review of dynamic feature variations and circumstantial parameters affecting dynamic signatures. The state of the art summarizes available knowledge, meant to assist the forensic practitioner in cases presenting extraordinary writing conditions. The studied parameters include hardware-related issues, aging and the influence of time, as well as physical and mental states of the writer. Some parameters, such as drug and alcohol abuse or medication, have very strong effects on handwriting and signature dynamics. Other conditions such as the writer’s posture and fatigue have been found to affect feature variation less severely. The need for further research about the influence of these parameters, as well as handwriting dynamics in general is highlighted. These factors are relevant to the examiner in the assessment of the probative value of the reported features. Additionally, methodology for forensic examination of dynamic signatures is discussed. Available methodology and procedures are reviewed, while pointing out major technical and methodological advances in the field of forensic handwriting examination. The need for sharing the best practice manuals, standard operating procedures and methodologies to favor further progress is accentuated