196 research outputs found

    Process of Fingerprint Authentication using Cancelable Biohashed Template

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    Template protection using cancelable biometrics prevents data loss and hacking stored templates, by providing considerable privacy and security. Hashing and salting techniques are used to build resilient systems. Salted password method is employed to protect passwords against different types of attacks namely brute-force attack, dictionary attack, rainbow table attacks. Salting claims that random data can be added to input of hash function to ensure unique output. Hashing salts are speed bumps in an attacker’s road to breach user’s data. Research proposes a contemporary two factor authenticator called Biohashing. Biohashing procedure is implemented by recapitulated inner product over a pseudo random number generator key, as well as fingerprint features that are a network of minutiae. Cancelable template authentication used in fingerprint-based sales counter accelerates payment process. Fingerhash is code produced after applying biohashing on fingerprint. Fingerhash is a binary string procured by choosing individual bit of sign depending on a preset threshold. Experiment is carried using benchmark FVC 2002 DB1 dataset. Authentication accuracy is found to be nearly 97\%. Results compared with state-of art approaches finds promising

    Intelligent interface agents for biometric applications

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    This thesis investigates the benefits of applying the intelligent agent paradigm to biometric identity verification systems. Multimodal biometric systems, despite their additional complexity, hold the promise of providing a higher degree of accuracy and robustness. Multimodal biometric systems are examined in this work leading to the design and implementation of a novel distributed multi-modal identity verification system based on an intelligent agent framework. User interface design issues are also important in the domain of biometric systems and present an exceptional opportunity for employing adaptive interface agents. Through the use of such interface agents, system performance may be improved, leading to an increase in recognition rates over a non-adaptive system while producing a more robust and agreeable user experience. The investigation of such adaptive systems has been a focus of the work reported in this thesis. The research presented in this thesis is divided into two main parts. Firstly, the design, development and testing of a novel distributed multi-modal authentication system employing intelligent agents is presented. The second part details design and implementation of an adaptive interface layer based on interface agent technology and demonstrates its integration with a commercial fingerprint recognition system. The performance of these systems is then evaluated using databases of biometric samples gathered during the research. The results obtained from the experimental evaluation of the multi-modal system demonstrated a clear improvement in the accuracy of the system compared to a unimodal biometric approach. The adoption of the intelligent agent architecture at the interface level resulted in a system where false reject rates were reduced when compared to a system that did not employ an intelligent interface. The results obtained from both systems clearly express the benefits of combining an intelligent agent framework with a biometric system to provide a more robust and flexible application

    Fusion of fingerprint presentation attacks detection and matching: a real approach from the LivDet perspective

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    The liveness detection ability is explicitly required for current personal verification systems in many security applications. As a matter of fact, the project of any biometric verification system cannot ignore the vulnerability to spoofing or presentation attacks (PAs), which must be addressed by effective countermeasures from the beginning of the design process. However, despite significant improvements, especially by adopting deep learning approaches to fingerprint Presentation Attack Detectors (PADs), current research did not state much about their effectiveness when embedded in fingerprint verification systems. We believe that the lack of works is explained by the lack of instruments to investigate the problem, that is, modelling the cause-effect relationships when two systems (spoof detection and matching) with non-zero error rates are integrated. To solve this lack of investigations in the literature, we present in this PhD thesis a novel performance simulation model based on the probabilistic relationships between the Receiver Operating Characteristics (ROC) of the two systems when implemented sequentially. As a matter of fact, this is the most straightforward, flexible, and widespread approach. We carry out simulations on the PAD algorithms’ ROCs submitted to the editions of LivDet 2017-2019, the NIST Bozorth3, and the top-level VeriFinger 12.0 matchers. With the help of this simulator, the overall system performance can be predicted before actual implementation, thus simplifying the process of setting the best trade-off among error rates. In the second part of this thesis, we exploit this model to define a practical evaluation criterion to assess whether operational points of the PAD exist that do not alter the expected or previous performance given by the verification system alone. Experimental simulations coupled with the theoretical expectations confirm that this trade-off allows a complete view of the sequential embedding potentials worthy of being extended to other integration approaches

    Sequence Checking and Deduplication for Existing Fingerprint Databases

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    Biometric technology is a rapidly evolving field with applications that range from access to devices to border crossing and entry/exit processes. Large-scale applications to collect biometric data, such as border crossings result in multimodal biometric databases containing thousands of identities. However, due to human operator error, these databases often contain many instances of image labeling and classification; this is due to the lack of training and throughput pressure that comes with human error. Multiple entries from the same individual may be assigned to a different identity. Rolled fingerprints may be labeled as flat images, a face image entered into a fingerprint field or images entered in incorrect orientation (such as rotated face images, left or right iris, etc.) are common errors found large database records. Ultimately, these enrollment errors make it impossible to identify that individual upon subsequent identification encounters. Sorting through hundreds of images to check for classification errors is a tedious and time-consuming task, especially when several biometric databases are combined. Our goal is to correctly identify misclassified fingerprints using controlled embeddings and thresholds. This work provides a new perspective on image sorting as it focuses not on the traditional aspects of increasing accuracy metrics but provides a look into multiple factors through various embeddings and thresholds to provide a tool that can be used to scour large datasets with ease to provide what percentage of the images need manual correction. The proposed network provides various metric scores which allowed for analysis on the most effective embedding and thresholds to use, resulting in a proof-of-concept to be used for practical purposes in the real world

    An enhanced fuzzy commitment scheme in biometric template protection

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    Biometric template protection consists of two approaches; Feature Transformation (FT) and Biometric Cryptography (BC). This research focuses on Key-Binding Technique based on Fuzzy Commitment Scheme (FCS) under BC approach. In FCS, the helper data should not disclose any information about the biometric data. However, literatures showed that it had dependency issue in its helper data which jeopardize security and privacy. Moreover, this also increases the probability of privacy leakage which lead to attacks such as brute-force and cross-matching attack. Thus, the aim of this research is to reduce the dependency of helper data that can caused privacy leakage. Three objectives have been set such as (1) to identify the factors that cause dependency on biometric features (2) to enhance FCS by proposing an approach that reduces this dependency, and (3) to evaluate the proposed approach based on parameters such as security, privacy, and biometric performance. This research involved four phases. Phase one, involved research review and analysis, followed by designing conceptual model and algorithm development in phase two and three respectively. Phase four, involved with the evaluation of the proposed approach. The security and privacy analysis shows that with the additional hash function, it is difficult for adversary to perform brute‐force attack on information stored in database. Furthermore, the proposed approach has enhanced the aspect of unlinkability and prevents cross-matching attack. The proposed approach has achieved high accuracy of 95.31% with Equal Error Rate (EER) of 1.54% which performs slightly better by 1.42% compared to the existing approach. This research has contributed towards the key-binding technique of biometric fingerprint template protection, based on FCS. In particular, this research was designed to create a secret binary feature that can be used in other state-of-the-art cryptographic systems by using an appropriate error-correcting approach that meets security standards

    Finger Vein Template Protection with Directional Bloom Filter

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    Biometrics has become a widely accepted solution for secure user authentication. However, the use of biometric traits raises serious concerns about the protection of personal data and privacy. Traditional biometric systems are vulnerable to attacks due to the storage of original biometric data in the system. Because biometric data cannot be changed once it has been compromised, the use of a biometric system is limited by the security of its template. To protect biometric templates, this paper proposes the use of directional bloom filters as a cancellable biometric approach to transform the biometric data into a non-invertible template for user authentication purposes. Recently, Bloom filter has been used for template protection due to its efficiency with small template size, alignment invariance, and irreversibility. Directional Bloom Filter improves on the original bloom filter. It generates hash vectors with directional subblocks rather than only a single-column subblock in the original bloom filter. Besides, we make use of multiple fingers to generate a biometric template, which is termed multi-instance biometrics. It helps to improve the performance of the method by providing more information through the use of multiple fingers. The proposed method is tested on three public datasets and achieves an equal error rate (EER) as low as 5.28% in the stolen or constant key scenario. Analysis shows that the proposed method meets the four properties of biometric template protection. Doi: 10.28991/HIJ-2023-04-02-013 Full Text: PD

    Cancer Biomarker Research and Personalized Medicine

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    Biomarkers are measures of a biological state. The treatment of individual patients based on particular factors, such as biomarkers, distinguishes standard, generalized treatment plans from personalized medicine. Even though personalized medicine is applicable to most branches of medicine, the field of oncology is perhaps where it is most easily employed. Cancer is a heterogeneous disease; although patients may be diagnosed histologically with the same cancer type, their tumors can comprise varying tumor microenvironments and molecular characteristics that can impact treatment response and prognosis. There has been a major drive over the past decade to try and realize personalized cancer medicine through the discovery and use of disease-specific biomarkers. This book, entitled “Cancer Biomarker Research and Personalized Medicine”, encompasses 22 publications from colleagues working on a diverse range of cancers, including prostate, breast, ovarian, head and neck, liver, gastric, bladder, colorectal, and kidney. The biomarkers assessed in these studies include genes, intracellular or secreted proteins, exosomes, DNA, RNA, miRNA, circulating tumor cells, circulating immune cells, in addition to radiomic features

    Jedna klasa biometrijskog kriptosistema zasnovanog na konvolucionim neuronskim mrežama

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    U ovoj doktorskoj disertaciji predložen je novi biometrijski kriptosistem otisaka prstiju baziran na sistemu fazi povezivanja i dubokih konvolucionih neuronskih mreža. Centralni doprinos rada predstavlja novi pristup automatskom izdvajanju obeležja fiksne dužine iz otisaka prstiju, u potpunosti zasnovanom na konvolucionim neuronskim mrežama. Predloženom kvantizacijom obeležja kodovanjem sa dva bita, biometrijski šabloni su prevedeni u binarni domen, što je omogućilo primenu XOR biometrije i razvoj biometrijskog kriptosistema koji se može koristiti za upravljanje ključevima (engl. key-release) ili za zaštitu šablona. Problem varijabilnosti biometrijskih podataka marginalizovan je primenom BCH koda za korekciju grešaka, koji radi na nivou bloka što ga čini otpornim na poznate statističke napade. Predloženi biometrijski kriptosistem sistem može upravljati dužinom ključeva od 265 bita, što zadovoljava potrebe savremenih kriptografskih sistema, uz prihvatljivu marginu EER greške od 1%. Evaluacija eksperimentalnih rezultata potvrđuje značajan napredak u odnosu na druge biometrijske kriptosisteme i sisteme za poređenje otisaka na osnovu njihove teksture

    Identification and Security Implications of Biometrics

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    The usage of biometrics has become more frequent over the past couple of decades, notably due to technological advancements. Evolving technology in the field of biometrics has also led to increased accuracy of associated software, which have provided the opportunity to use a multitude of different human characteristics for identification and/or verification purposes. The current study assessed the usage of biometrics in casinos, hospitals, and law enforcement agencies using a survey methodology. Results indicated that privacy concerns related to the use of biometrics may not be as prevalent as indicated in the literature. Additionally, results indicated that the utilization of biometrics has led to increased accuracy in identification and verification processes, led to enhanced security, and would be highly recommended to other institutions. Information obtained from the literature notes the racial bias in facial recognition technologies due to algorithmic development based solely upon features of Caucasian individuals. Efforts need to be made to create facial recognition algorithms that are more racially and ethnically diverse
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