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Journal articles on the topic 'BIOMETRIC FRAMEWORK'

Author: Grafiati
Published: 11 September 2023

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1

Srivastava, Prateek, and Rohit Srivastava. "A Multimodal Based Approach for Face and Unique Mark Based Combination for Confirmation of Human." International Journal of Business Analytics 6, no. 3 (July 2019): 16–28. http://dx.doi.org/10.4018/ijban.2019070102.

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Biometric processes are utilized for recognition and distinguishing a person for different applications. The procedure is made possible by utilizing single biometric highlight or a mix of biometric highlights. In the event that the distinguishing proof is finished by utilizing a solitary biometric highlight (confront, iris, finger, palm, and so forth) then the framework is called unimodal, and if a combnation of biometrics are utilized then it is called multimodal. In a multimodal framework compared to the different downsides of a unimodal framework (noisy data, multiple vectors and so forth) are evacuated. The fundamental objective of the proposed work is to outline a system that will give validation in view of three-level verification for a man. Prior works in this field are clarified in various factual models in view of various verification plans. In the proposed strategy, a system is created in which if one biometric attribute fails then the other biometic characteristics can be utilized for verification.
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Srivastava, Rohit, Ved Prakash Bhardwaj, Mohamed Tahar Ben Othman, Mukesh Pushkarna, Anushree, Arushi Mangla, Mohit Bajaj, Ateeq Ur Rehman, Muhammad Shafiq, and Habib Hamam. "Match-Level Fusion of Finger-Knuckle Print and Iris for Human Identity Validation Using Neuro-Fuzzy Classifier." Sensors 22, no. 10 (May 10, 2022): 3620. http://dx.doi.org/10.3390/s22103620.

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Biometrics is the term for measuring human characteristics. If the term is divided into two parts, bio means life, and metric means measurement. The measurement of humans through different computational methods is performed to authorize a person. This measurement can be performed via a single biometric or by using a combination of different biometric traits. The combination of multiple biometrics is termed biometric fusion. It provides a reliable and secure authentication of a person at a higher accuracy. It has been introduced in the UIDIA framework in India (AADHAR: Association for Development and Health Action in Rural) and in different nations to figure out which biometric characteristics are suitable enough to authenticate the human identity. Fusion in biometric frameworks, especially FKP (finger–knuckle print) and iris, demonstrated to be a solid multimodal as a secure framework. The proposed approach demonstrates a proficient and strong multimodal biometric framework that utilizes FKP and iris as biometric modalities for authentication, utilizing scale-invariant feature transform (SIFT) and speeded up robust features (SURF). Log Gabor wavelet is utilized to extricate the iris feature set. From the extracted region, features are computed using principal component analysis (PCA). Both biometric modalities, FKP and iris, are combined at the match score level. The matching is performed using a neuro-fuzzy neural network classifier. The execution and accuracy of the proposed framework are tested on the open database Poly-U, CASIA, and an accuracy of 99.68% is achieved. The accuracy is higher compared to a single biometric. The neuro-fuzzy approach is also tested in comparison to other classifiers, and the accuracy is 98%. Therefore, the fusion mechanism implemented using a neuro-fuzzy classifier provides the best accuracy compared to other classifiers. The framework is implemented in MATLAB 7.10.
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Sabharwal, Munish. "Multi-Modal Biometric Authentication and Secure Transaction Operation Framework for E-Banking." International Journal of Business Data Communications and Networking 13, no. 1 (January 2017): 102–16. http://dx.doi.org/10.4018/ijbdcn.2017010109.

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The rationale of the research work is to suggest a multi-modal biometric authentication and secure transaction operation framework for E-Banking. The literature survey identifies the various types of E-Banking Channels available as on-date, the various types of biometric technologies available as on-date as well the significant metrics affecting their performance while deploying them in various different e-banking channels. The performance analysis of various types of biometric technologies based on significant metrics for Biometrics Implementation further identifies the currently implementable biometric technologies for the various different e-banking channels. Subsequently a requirement analysis of potential e-banking channels is followed by System Suitability Analysis to identify which multi-biometrics and support mechanisms are suitable for particular e-banking channels. The final conclusion suggests a viable multi-modal biometric authentication and secure transaction operation framework for various e-banking channels.
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Sable, Harsh, and Divya Bajpai Tripathy. "A Review on Comparative Analysis on Different Sort of Physiological and Behavioral Biometric Framework." International Journal of Advance Research and Innovation 9, no. 2 (2021): 1–9. http://dx.doi.org/10.51976/ijari.922101.

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Biometrics as the investigation of seeing an individual ward on their physical or conduct characteristics, biometric have now been conveyed in diverse business, ordinary resident and national security applications. Customarily the usage of biometrics devices has improved our capacity to give approved entry to material foundations. Biometric is the usage of a person's novel physiological, lead, and morphological trademark to give valuable person distinguishing proof. Biometric structures that are starting at now available today break down fingerprints, engravings, iris and retina models, and face. Mechanisms that are similar to biometrics anyway are not named such are lead systems, for instance, voice, imprint and keystroke mechanisms. These days biometrics is in effect effectively executed in numerous fields like measurable, security, recognizable proof and approval frameworks.
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Omar, Bayan, Hamsa D. Majeed, Siti Zaiton Mohd Hashim, and Muzhir Al-Ani. "New Feature-level Algorithm for a Face-fingerprint Integral Multi-biometrics Identification System." UHD Journal of Science and Technology 6, no. 1 (February 11, 2022): 12–20. http://dx.doi.org/10.21928/uhdjst.v6n1y2022.pp12-20.

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This article delves into the power of multi-biometric fusion for individual identification. a new feature-level algorithm is proposed that is the Dis-Eigen algorithm. Here, a feature-fusion framework is proposed for attaining better accuracy when identifying individuals for multiple biometrics. The framework, therefore, underpins the new multi-biometric system as it guides multi-biometric fusion applications at the feature phase for identifying individuals. In this regard, the Face-fingerprints of 20 individuals represented by 160 images were used in this framework . Experimental resultants of the proposed approach show 93.70 % identification rate with feature-level fusion multi-biometric individual identification.
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Musambo, Lubasi Kakwete, and Jackson Phiri. "A Framework for Civil Registration in Developing Countries Based on Biometrics and ISO Standards." International Journal of ICT Research in Africa and the Middle East 8, no. 2 (July 2019): 32–74. http://dx.doi.org/10.4018/ijictrame.2019070103.

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Most developing countries in Africa have civil registration processes with inherent challenges that inhibit their efficiency and accuracy. Attempts at modernization and improvement are on-going. In this article, a biometric framework that can be used to mitigate the challenges inherent in biometric data management for the civil registration system in Zambia is presented. The proposed framework presented is based on ISO models and adapted for most developing countries with low Information and Communication Technologies. A baseline study was undertaken to assess the understanding and appreciation of biometrics within the Zambian community and how this data might be stored or managed. A study of the Zambian civil registration business process has been undertaken and the authors propose an automated civil registration business process. Results obtained show that currently, Zambia does NOT have a biometric framework that supervises use of biometric data. The proposed model once adopted would form a secure framework for civil registration based on biometrics and ISO standards.
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Jovanovic, Bojan, Ivan Milenkovic, Marija Bogicevic-Sretenovic, and Dejan Simic. "Extending identity management system with multimodal biometric authentication." Computer Science and Information Systems 13, no. 2 (2016): 313–34. http://dx.doi.org/10.2298/csis141030003j.

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Techniques for authentication that are used in today's identity management systems are vulnerable when they are used over the network. In order to prevent fraud and unauthorized data access, it is important to ensure the identity of the person who submitted authentication credentials. The authentication process can be additionally secured by using biometric data for user verification. Moreover, precision of biometric authentication can be improved by the use of multimodal biometrics. This paper presents a system which has been designed for identity management based on FreeIPA solution for digital identity management and MMBio framework for multimodal biometrics. Proposed system provides multifactor authentication, where MMBio framework is used for handling user biometric data. Developed prototype confirms possible integration of identity management and multimodal biometric systems.
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Jacobsen, Katja Lindskov. "Biometric data flows and unintended consequences of counterterrorism." International Review of the Red Cross 103, no. 916-917 (April 2021): 619–52. http://dx.doi.org/10.1017/s1816383121000928.

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AbstractExamining unintended consequences of the makings and processing of biometric data in counterterrorism and humanitarian contexts, this article introduces a two-fold framework through which it analyzes biometric data-makings and flows in Afghanistan and Somalia. It combines Tilley's notion of “living laboratory” and Larkin's notion of infrastructure into a framework that attends to the conditions under which biometric data is made and to subsequent flows of such data through data-sharing agreements or unplanned access. Exploring such unintended consequences, attention needs to be paid to the variety of actors using biometrics for different purposes yet with data flows across such differences. Accordingly, the article introduces the notion of digital intervention infrastructures, with biometric databases as one dimension.
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Srivastava, Rohit. "Score-Level Multimodal Biometric Authentication of Humans Using Retina, Fingerprint, and Fingervein." International Journal of Applied Evolutionary Computation 11, no. 3 (July 2020): 20–30. http://dx.doi.org/10.4018/ijaec.2020070102.

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This paper characterizes a multi-modular framework for confirmation, dependent on the biometric combination of retina, finger vein, and unique mark acknowledgment. The authors have proposed feature extraction in retina acknowledgment model by utilizing SIFT and MINUTIA. Security is the fundamental idea in ATM (Automated Teller Machines) today. The use of multi-modular biometrics can be ATM. The work includes three biometric attributes of a client to be specific retina, unique mark, and finger veins. These are pre-prepared and joined (fused) together for score level combination approach. Retina is chosen as a biometric attribute as there are no parallel retina feature matches except if they are of the comparative client; likewise, retina has a decent vessel design making it a decent confirming methodology when contrasted with other biometric attributes. Security is found in the framework by multi-modular biometric combination of retina with finger vein and unique finger impression. Feature extraction approach and cryptography are utilized so as to accomplish security. The element extraction is finished with the assistance of MINUTIA and SIFT calculation, which are at that point characterized utilizing deep neural network (DNN). The element key focuses are intertwined at score level utilizing separation normal and later matched. The test result assessed utilizing MATLAB delineates the significant improvement in the presentation of multi-modular biometric frameworks with higher qualities in GAR and FAR rates.
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Yaman, Mehmet, Abdulhamit Subasi, and Frank Rattay. "Comparison of Random Subspace and Voting Ensemble Machine Learning Methods for Face Recognition." Symmetry 10, no. 11 (November 19, 2018): 651. http://dx.doi.org/10.3390/sym10110651.

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Biometry based authentication and recognition have attracted greater attention due to numerous applications for security-conscious societies, since biometrics brings accurate and consistent identification. Face biometry possesses the merits of low intrusiveness and high precision. Despite the presence of several biometric methods, like iris scan, fingerprints, and hand geometry, the most effective and broadly utilized method is face recognition, because it is reasonable, natural, and non-intrusive. Face recognition is a part of the pattern recognition that is applied for identifying or authenticating a person that is extracted from a digital image or a video automatically. Moreover, current innovations in big data analysis, cloud computing, social networks, and machine learning have allowed for a straightforward understanding of how different challenging issues in face recognition might be solved. Effective face recognition in the enormous data concept is a crucial and challenging task. This study develops an intelligent face recognition framework that recognizes faces through efficient ensemble learning techniques, which are Random Subspace and Voting, in order to improve the performance of biometric systems. Furthermore, several methods including skin color detection, histogram feature extraction, and ensemble learner-based face recognition are presented. The proposed framework, which has a symmetric structure, is found to have high potential for biometrics. Hence, the proposed framework utilizing histogram feature extraction with Random Subspace and Voting ensemble learners have presented their superiority over two different databases as compared with state-of-art face recognition. This proposed method has reached an accuracy of 99.25% with random forest, combined with both ensemble learners on the FERET face database.
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NAZAR, AKIF, ISSA TRAORÉ, and AHMED AWAD E. AHMED. "INVERSE BIOMETRICS FOR MOUSE DYNAMICS." International Journal of Pattern Recognition and Artificial Intelligence 22, no. 03 (May 2008): 461–95. http://dx.doi.org/10.1142/s0218001408006363.

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Various techniques have been proposed in different literature to analyze biometric samples collected from individuals. However, not a lot of attention has been paid to the inverse problem, which consists of synthesizing artificial biometric samples that can be used for testing existing biometric systems or protecting them against forgeries. In this paper, we present a framework for mouse dynamics biometrics synthesis. Mouse dynamics biometric is a behavioral biometric technology, which allows user recognition based on the actions received from the mouse input device while interacting with a graphical user interface. The proposed inverse biometric model learns from random raw samples collected from real users and then creates synthetic mouse actions for fake users. The generated mouse actions have unique behavioral properties separate from the real mouse actions. This is shown through various comparisons of behavioral metrics as well as a Kolmogorov–Smirnov test. We also show through a two-fold cross-validation test that by submitting sample synthetic data to an existing mouse biometrics analysis model we achieve comparable performance results as when the model is applied to real mouse data.
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Singh, Bhanu, and Nirvisha Singh. "MoLaBSS: Server-Specific Add-On Biometric Security Layer Model to Enhance the Usage of Biometrics." Information 11, no. 6 (June 8, 2020): 308. http://dx.doi.org/10.3390/info11060308.

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With high-paced growth in biometrics, and its easy availability to capture various biometric features, it is emerging as one of the most valuable technologies for multifactor authentication to verify a user’s identity, for data security. Organizations encourage their members to use biometrics, but they are hesitant to use them due to perceived security risks. Because of its low usage rate, many medium and small segment organizations find it unfeasible to deploy robust biometric systems. We propose a server-specific add-on biometric security layer model (MoLaBSS) to enhance confidence in the usage of biometrics. We tested this model via a biometric mobile app, and the survey showed a favorable response of 80%. The innovative mobile app was tested for its usability and got a score of more than 71%. For test tool reliability, we examined the equal error rate (EER) of the app and got a reasonably low score of 6%. The results show good potential of this framework to enhance users’ confidence level in the usage of biometrics. Higher usage rates may make deployment of biometrics more cost-effective for many organizations to decrease their information security risk.
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Tait, Bobby L. "The biometric landscape - towards a sustainable biometric terminology framework." International Journal of Electronic Security and Digital Forensics 6, no. 2 (2014): 147. http://dx.doi.org/10.1504/ijesdf.2014.063110.

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14

Manikis, Georgios C., Marios Spanakis, and Emmanouil G. Spanakis. "Personalized Mobile eHealth Services for Secure User Access Through a Multi Feature Biometric Framework." International Journal of Reliable and Quality E-Healthcare 8, no. 1 (January 2019): 40–51. http://dx.doi.org/10.4018/ijrqeh.2019010104.

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Humans have various features that differentiates one person from another which can be used to identify an individual for security purposes. These biometrics can authenticate or verify a person's identity and can be sorted in two classes, physiological and behavioural. In this article, the authors present their results of experimentation on publicly available facial images and the efficiency of a prototype version of SpeechXRays, a multi-modal biometric system that uses audio-visual characteristics for user authentication in eHealth platforms. Using the privacy and security mechanism provided, based on audio and video biometrics, medical personnel are able to be verified and subsequently identified for two different eHealth applications. These verified persons are then able to access control, identification, workforce management or patient record storage. In this work, the authors argue how a biometric identification system can greatly benefit healthcare, due to the increased accuracy of identification procedures.
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Ćosić, Zoran, Jasmin Ćosić, and Miroslav Bača. "Biometric System Reliability Evaluation Framework." British Journal of Mathematics & Computer Science 12, no. 6 (January 10, 2016): 1–13. http://dx.doi.org/10.9734/bjmcs/2016/21701.

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Baig, Asim, Ahmed Bouridane, Fatih Kurugollu, and Badr Albesher. "Cascaded multimodal biometric recognition framework." IET Biometrics 3, no. 1 (March 2014): 16–28. http://dx.doi.org/10.1049/iet-bmt.2012.0043.

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Bukola, Makinde. "A framework for Modified Firefly Algorithm in Multimodal Biometric Authentication System." International Journal of Engineering and Computer Science 12, no. 07 (July 7, 2023): 25735–62. http://dx.doi.org/10.18535/ijecs/v12i07.4741.

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Many end users are turning to multimodal biometric systems as a result of the limitations of conventional authentication techniques and unimodal biometric systems for offering a high level of accurate authentication. When high accuracy and security are required, multimodal biometrics are the best choice because to the utilization of numerous identification modalities. It is difficult to identify the best features that contribute to the recognition rate/accuracy and have a high redundancy of features since different features are acquired at the feature level fusion from a variety of physiological or behavioral variables. At the feature selection level, the utilization of meta-heuristic algorithms will reduce the number of redundant features while keeping critical feature sets that are important to biometric performance, accuracy, and efficiency. The study demonstrated a multimodal biometric authentication system that used the features of the face and both irises. In order to avoid being stuck at the local optimum and hasten convergence, the Firefly Algorithm (FFA) was modified by including a chaotic sinusoidal map function and a roulette wheel selection mechanism as deterministic processes. The results of the study demonstrated that in terms of sensitivity, precision, recognition accuracy, and time, the proposed MFFA with multimodal outperformed the MFFA for unimodal, bi-modal, and bi-instance. In addition to being computationally faster, more accurate, and suitable for real-time applications, the modified method, known as MFFA, proved effective in integrating multimodal data sets.
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Chandra, Akhilesh, and Thomas G. Calderon. "Toward a Biometric Security Layer in Accounting Systems." Journal of Information Systems 17, no. 2 (September 1, 2003): 51–70. http://dx.doi.org/10.2308/jis.2003.17.2.51.

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This paper discusses theoretical and practical issues related to the use of a biometric-enabled security layer in accounting systems aimed at enhancing user authentication and reducing control risk. Originating in criminology, biometric technology has matured over the years with applications in diverse disciplines. However, its use in business and accounting is still in its infancy, and many issues about its role in information systems security are unresolved. The paper proposes an access decision framework that draws from the strategy and risk assessment literature to model processes where biometrics might be used to reduce control risk. Despite its potential strengths, biometric technology is not a panacea and represents one element in a portfolio of security mechanisms needed to protect information resources. The paper discusses challenges in implementing biometric technology and identifies avenues for future research.
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Herbadji, Abderrahmane, Zahid Akhtar, Kamran Siddique, Noubeil Guermat, Lahcene Ziet, Mohamed Cheniti, and Khan Muhammad. "Combining Multiple Biometric Traits Using Asymmetric Aggregation Operators for Improved Person Recognition." Symmetry 12, no. 3 (March 10, 2020): 444. http://dx.doi.org/10.3390/sym12030444.

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Biometrics is a scientific technology to recognize a person using their physical, behavior or chemical attributes. Biometrics is nowadays widely being used in several daily applications ranging from smart device user authentication to border crossing. A system that uses a single source of biometric information (e.g., single fingerprint) to recognize people is known as unimodal or unibiometrics system. Whereas, the system that consolidates data from multiple biometric sources of information (e.g., face and fingerprint) is called multimodal or multibiometrics system. Multibiometrics systems can alleviate the error rates and some inherent weaknesses of unibiometrics systems. Therefore, we present, in this study, a novel score level fusion-based scheme for multibiometric user recognition system. The proposed framework is hinged on Asymmetric Aggregation Operators (Asym-AOs). In particular, Asym-AOs are estimated via the generator functions of triangular norms (t-norms). The extensive set of experiments using seven publicly available benchmark databases, namely, National Institute of Standards and Technology (NIST)-Face, NIST-Multimodal, IIT Delhi Palmprint V1, IIT Delhi Ear, Hong Kong PolyU Contactless Hand Dorsal Images, Mobile Biometry (MOBIO) face, and Visible light mobile Ocular Biometric (VISOB) iPhone Day Light Ocular Mobile databases have been reported to show efficacy of the proposed scheme. The experimental results demonstrate that Asym-AOs based score fusion schemes not only are able to increase authentication rates compared to existing score level fusion methods (e.g., min, max, t-norms, symmetric-sum) but also is computationally fast.
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Algarni, Abeer D., Ghada M. El Banby, Naglaa F. Soliman, Fathi E. Abd El-Samie, and Abdullah M. Iliyasu. "Efficient Implementation of Homomorphic and Fuzzy Transforms in Random-Projection Encryption Frameworks for Cancellable Face Recognition." Electronics 9, no. 6 (June 24, 2020): 1046. http://dx.doi.org/10.3390/electronics9061046.

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To circumvent problems associated with dependence on traditional security systems on passwords, Personal Identification Numbers (PINs) and tokens, modern security systems adopt biometric traits that are inimitable to each individual for identification and verification. This study presents two different frameworks for secure person identification using cancellable face recognition (CFR) schemes. Exploiting its ability to guarantee irrevocability and rich diversity, both frameworks utilise Random Projection (RP) to encrypt the biometric traits. In the first framework, a hybrid structure combining Intuitionistic Fuzzy Logic (IFL) with RP is used to accomplish full distortion and encryption of the original biometric traits to be saved in the database, which helps to prevent unauthorised access of the biometric data. The framework involves transformation of spatial-domain greyscale pixel information to a fuzzy domain where the original biometric images are disfigured and further distorted via random projections that generate the final cancellable traits. In the second framework, cancellable biometric traits are similarly generated via homomorphic transforms that use random projections to encrypt the reflectance components of the biometric traits. Here, the use of reflectance properties is motivated by its ability to retain most image details, while the guarantee of the non-invertibility of the cancellable biometric traits supports the rationale behind our utilisation of another RP stage in both frameworks, since independent outcomes of both the IFL stage and the reflectance component of the homomorphic transform are not enough to recover the original biometric trait. Our CFR schemes are validated on different datasets that exhibit properties expected in actual application settings such as varying backgrounds, lightings, and motion. Outcomes in terms standard metrics, including structural similarity index metric (SSIM) and area under the receiver operating characteristic curve (AROC), suggest the efficacy of our proposed schemes across many applications that require person identification and verification.
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Shrivastava, Rajeev, Mohammad Javeed, and G. Mallesham. "Field Programmable Gate Array Implementation for Highly Secured Palm Print Authentication." Journal of Computational and Theoretical Nanoscience 17, no. 9 (July 1, 2020): 4565–70. http://dx.doi.org/10.1166/jctn.2020.9281.

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To guarantee individual ID and profoundly secure recognizable proof issues, biometric innovations will give more prominent security while improving precision. This new innovation has been done lately because of exchange misrepresentation, security breaks, individual ID, and so on. The excellence of biometric innovation is that it gives an exceptional code to every individual and can’t be duplicated or manufactured by others. So as to conquer the withdrawal of finger impression frameworks, this paper proposed a palm-based individual distinguishing proof framework, a promising and new research region in biometric recognizable proof frameworks in light of their uniqueness, adaptability and a quicker and wide scope of high speeds. It gives higher security on biometric unique mark frameworks with rich highlights, for example, wrinkles, constant brushes, mainlines, details focuses and single focuses. The fundamental motivation behind the proposed palm unique finger impression framework is to actualize a framework with higher exactness and speed up palm unique finger impression acknowledgment for some clients. Here, in this we presented an exceptionally ensured palm print recognizable proof framework with intrigue extraction territory (ROI) with a morphological procedure utilizing a two-way un-crushed or course vector (UDBW) change to separate low-level palm fingerprints enrolled capacities for its vector work (FV) and afterward after correlation is by estimating the separation between the palm transporters and the capacity of the palm and the capacity of the enlisted transport line and palm control. The after effects of the recreation show that the proposed biometric recognizable proof framework gives more noteworthy precision and solid distinguishing proof speed.
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Shao, Huikai, Dexing Zhong, and Xuefeng Du. "A deep biometric hash learning framework for three advanced hand‐based biometrics." IET Biometrics 10, no. 3 (March 16, 2021): 246–59. http://dx.doi.org/10.1049/bme2.12014.

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Rassolov, I. M., S. G. Chubukova, and I. V. Mikurova. "Biometrics in the Context of Personal Data and Genetic Information: Legal Issues." Lex Russica, no. 1 (January 1, 2019): 108–18. http://dx.doi.org/10.17803/1729-5920.2019.146.1.108-118.

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In modern society, methods of identification of persons on the basis of their physical, biological or behavioral characteristics are actively developing. European countries are in the process of developing a holistic doctrine on biometric control and are clarifying their position on situations where biometric data are used by individuals.From the position of information law, the paper presents a new author’s approach to the problem of processing biometric data and genetic information. The division of biometrics into “trace” and “non-trace” is losing its meaning. A new classification of biometrics into digital and analog is proposed.Biometric access control should not become a routine phenomenon in the framework of the organization of the company and without any reason to replace other existing types of control. The interested person can be entrusted with the storage of their own biometric data to reduce the risks of leakage and the consequences of exposure to them. Biometric data must be stored on the company’s servers in encrypted form, which makes it impossible to use them without the consent of the person concerned.Biometric data should be protected by a special legal regime. The analysis of the European and Russian legislation made it possible to draw the following conclusions: biometric data is a special type of personal data, a special legal regime and regulation should be established; digital biometrics needs special legal regulation, since it is the most vulnerable type; genetic information does not fully correspond to the concept of personal data, as it can relate to an unlimited number of persons. This determines the need to develop a special law “on genetic information”.
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Arunachalamand, MuthuKumar, and Kavipriya Amuthan. "Finger Knuckle Print Recognition using MMDA with Fuzzy Vault." International Arab Journal of Information Technology 17, no. 4 (July 1, 2020): 554–61. http://dx.doi.org/10.34028/iajit/17/4/14.

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Currently frequent biometric scientific research such as with biometric applications like face, iris, voice, hand-based biometrics traits like palm print and fingerprint technique are utilized for spotting out the persons. These specific biometrics habits have their own improvement and weakness so that no particular biometrics can adequately opt for all terms like the accuracy and cost of all applications. In recent times, in addition, to distinct with the hand-based biometrics technique, Finger Knuckle Print (FKP) has been appealed to boom the attention among biometric researchers. The image template pattern formation of FKP embraces the report that is suitable for spotting the uniqueness of individuality. This FKP trait observes a person based on the knuckle print and the framework in the outer finger surface. This FKP feature determines the line anatomy and finger structures which are well established and persistent throughout the life of an individual. In this paper, a novel method for personal identification will be introduced, along with that data to be stored in a secure way has also been proposed. The authentication process includes the transformation of features using 2D Log Gabor filter and Eigen value representation of Multi-Manifold Discriminant Analysis (MMDA) of FKP. Finally, these features are grouped using k-means clustering for both identification and verification process. This proposed system is initialized based on the FKP framework without a template based on the fuzzy vault. The key idea of fuzzy vault storing is utilized to safeguard the secret key in the existence of random numbers as chaff pints
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Kim, Jeongmin, and Nayeon Kim. "Quantifying Emotions in Architectural Environments Using Biometrics." Applied Sciences 12, no. 19 (October 5, 2022): 9998. http://dx.doi.org/10.3390/app12199998.

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This paper reviews studies that have quantified humans’ emotions in architectural environments using biometrics. We analyzed the design variables that induced positive emotions and compared the study conditions for each result, including the biometric tools utilized. The objective was to analyze the design characteristics of the architectural environment, biometric tools, and study conditions that measure emotional responses in design research, their limitations, and future uses of biometric devices. Twenty papers were selected using the preferred reporting items for systematic reviews and meta-analyses. The population, intervention, control, outcome, and setting study design were used as an analysis framework. The reviewed papers used biometric tools such as electroencephalography, functional near-infrared spectroscopy, functional magnetic resonance imaging, galvanic skin response, electromyography, electrocardiography, and eye-tracking to analyze emotions. Environmental factors that produce positive emotional responses in the architectural spaces included form, layout, material, color, furniture, and lighting. The findings from methodology using biometric tools have the potential to develop an evidence-based design to produce positive emotions in architectural environments that improve our mental health and well-being.
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Joyce, S., and S. Veni. "Iris Biometric Watermarking for Authentication Using Multiband Discrete Wavelet Transform and Singular-Value Decomposition." International journal of electrical and computer engineering systems 14, no. 3 (March 28, 2023): 259–66. http://dx.doi.org/10.32985/ijeces.14.3.3.

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The most advanced technology, watermarking enables intruders to access the database. Various techniques have been developed for information security. Watermarks and histories are linked to many biometric techniques such as fingerprints, palm positions, gait, iris and speech are recommended. Digital watermarking is the utmost successful approaches among the methods available. In this paper the multiband wavelet transforms and singular value decomposition are discussed to establish a watermarking strategy rather than biometric information. The use of biometrics instead of conservative watermarks can enhance information protection. The biometric technology being used is iris. The iris template can be viewed as a watermark, while an iris mode of communication may be used to help information security with the addition of a watermark to the image of the iris. The research involves verifying authentication against different attacks such as no attacks, Jpeg Compression, Gaussian, Median Filtering and Blurring. The Algorithm increases durability and resilience when exposed to geometric and frequency attacks. Finally, the proposed framework can be applied not only to the assessment of iris biometrics, but also to other areas where privacy is critical.
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Reddy, Manjunath, Nur Mohammad Ali Chisty, and Anusha Bodepudi. "A Review of Cybersecurity and Biometric Authentication in Cloud Network." Engineering International 10, no. 1 (May 30, 2022): 9–18. http://dx.doi.org/10.18034/ei.v10i1.652.

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Cloud computing uses few resources to give customers complete distant services via the internet. Data privacy, security, and reliability are major issues with cloud computing. Security is the biggest issue. This study discusses the biometrics framework and safe cloud computing identity management method. This paper discusses cloud computing security challenges and reviews cloud access framework approaches. It describes a novel fingerprint access-based authentication system to protect cloud services from DOS and DDoS attacks. This biometrics-based system can secure cloud services from illegal access. This study addresses cloud security and privacy via biometric face recognition. Cloud users' security and privacy are protected via biometrics recognition. This article discusses CPS and its applications, technologies, and standards. SIGNIFICANT DIFFICULTIES AND CHALLENGES ARE FOUND IN reviewing CPS security weaknesses, threats, and attacks. Presenting and analyzing current security measures and their key drawbacks. Finally, this extensive examination yields various recommendations.
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Boubakeur, Meriem Romaissa, and Guoyin Wang. "Self-Relative Evaluation Framework for EEG-Based Biometric Systems." Sensors 21, no. 6 (March 17, 2021): 2097. http://dx.doi.org/10.3390/s21062097.

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In recent years, electroencephalogram (EEG) signals have been used as a biometric modality, and EEG-based biometric systems have received increasing attention. However, due to the sensitive nature of EEG signals, the extraction of identity information through processing techniques may lead to some loss in the extracted identity information. This may impact the distinctiveness between subjects in the system. In this context, we propose a new self-relative evaluation framework for EEG-based biometric systems. The proposed framework aims at selecting a more accurate identity information when the biometric system is open to the enrollment of novel subjects. The experiments were conducted on publicly available EEG datasets collected from 108 subjects in a resting state with closed eyes. The results show that the openness condition is useful for selecting more accurate identity information.
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Klochko, Alyona, and Natalia Volchenko. "Biometric technologies for security of banking operations in Ukraine and foreign countrie." Law Review of Kyiv University of Law, no. 1 (May 5, 2021): 299–304. http://dx.doi.org/10.36695/2219-5521.1.2021.59.

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The issue of introduction of innovative means of consumer protection against illegal actions in the field of banking is becomingrelevant in connection with the expansion of the range of banking services in Ukraine. The article summarizes the status and prospects of using biometric identification methods in the banking sector in Ukraine and abroad. Analysis and systematization of scientific publicationsand legal framework revealed that a potential direction of the concept of customer orientation of banks is the use of biometrictechnologies in the provision of services that ensure high-quality preservation of personal data of customers. It is stated that in Ukrainethere is a need to strengthen both technological and legal mechanisms for the protection of biometric data for the needs of the bankingsector. One of the factors that significantly complicates the implementation of biometrics in banks is the lack of technical capabilities.However, there is a gradual dynamics contained in the testing of various methods of biometric identification in banking institutions.Contradictions that arise between the actual needs of the use of biometric technologies in the field of banking by the state of regu -latory and legal support in Ukraine slow down the use of effective security tools with a high degree of reliability in the banking sector.Appropriate regulatory regulation of the use of biometric technologies for identification purposes will promote the development of thesetechnologies by strengthening the confidence of consumers of banking services, as well as competition of biometric algorithms in thepresence of unified standards and requirements. Factors that shape the conditions for committing criminal offenses using biometric datacan be neutralized by effective legal means, as well as by the relevant actors in combating these offenses. It is concluded that the introductionof biometrics for the banking sector in the future in Ukraine requires taking into account the leading international experienceon these issues and an integrated approach.
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Bahri, Mohammad Thoriq. "Immigration Biometric Data Exchange Among Asean Member States: Opportunities and Challenges in Legislations." Jurnal Ilmiah Kebijakan Hukum 16, no. 3 (November 30, 2022): 433. http://dx.doi.org/10.30641/kebijakan.2022.v16.433-456.

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Biometric data can be described as data containing human physical characteristics. They can be in the form of fingerprint data, retina scans, and voice recognition. The application of biometrics for immigration purposes reduce the number of terrorism case and illegal migrants in the European Union (EU) territory and the United States. In 2013, biometric data exchange in ASEAN was made possible with the Bali Process Protocol. By a qualitative research methodology, using the CIPP (Context, Input, Process, and Product) analysis, this research attempts to find the legal obstacles as the main barriers in implementing biometric data exchange in the ASEAN region. This study finds that not all ASEAN countries have laws on personal data protection, which affect the Standard Operating Procedures (SOP) related to how the biometric data will be retrieved, processed, and managed, as well as the actions required if there is a violation of the law related to the SOP. This study suggests that ASEAN can accommodate the EU’s framework, by using the General Data Protection Regulation (GDPR) as a single standard in the application of Data Protection regulations for the biometric data exchange system in ASEAN.
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Kim, Min-Gu, Hae-Min Moon, Yongwha Chung, and Sung Bum Pan. "A Survey and Proposed Framework on the Soft Biometrics Technique for Human Identification in Intelligent Video Surveillance System." Journal of Biomedicine and Biotechnology 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/614146.

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Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperation. Soft biometrics, although featuring less accuracy, can be used much more freely though. Recently, many researchers have been made on human identification using soft biometrics data collected from a distance. In this paper, we use both traditional and soft biometrics for human identification and propose a framework for solving such problems as lighting, occlusion, and shadowing.
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Minchev, Zlatogor. "Multiple Human Biometrics Fusion in Support of Cyberthreats Identification." Cybernetics and Information Technologies 15, no. 7 (December 1, 2015): 67–76. http://dx.doi.org/10.1515/cait-2015-0090.

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Abstract The paper is outlining an experimentally created framework for multiple human biometrics fusion in support to constantly evolving complex cyberthreats landscape identification. A “scenario method” approach, in combination with experts’ based decision support and users’ biometric “validation-in-advance”, are considered. Practical examples are also given to the proposed ideas, providing a comprehensive outlook to the problem.
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Arunarani, S., and R. Gobinath. "Literature review on multimodal biometrics." International Journal of Engineering & Technology 7, no. 2.26 (May 7, 2018): 31. http://dx.doi.org/10.14419/ijet.v7i2.26.12529.

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As technological reformation is widen, biometric systems substitute knowledge based and token based recognition systems. Confidential data are accessed by the user after the user is recognized by biometric systems. Efforts have been made to acquire more suitable prototype for recognizing human as multimodal biometrics has more severe concern because of noise in the sample and malfunctioning sensing devices. This paper gives a dual study related to multimodal biometrics, including a literature review of the prior work in authentication and the proposed evaluation approaches. First, we classify few epitome studies considered in last decades to show how this problem has been solved until now. Second, the paper gives a introduction about basic principles of the associated evaluation approaches, and then provide an extended evaluation framework based on the enrollment selection and also statistically convincing measures for evaluating quality metrics.
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Anikin, I. V., and E. S. Anisimova. "DYNAMIC HANDWRITTEN SIGNATURE BASED BIOMETRIC AUTHENTICATION FRAMEWORK." Mathematical Methods in Technologies and Technics, no. 1 (2021): 92–97. http://dx.doi.org/10.52348/2712-8873_mmtt_2021_1_92.

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Sivasubramaniyam, Jayanthi, and C. Chandrasekar. "A Biometric-Secured Neighborhood Vector Relational Coefficient Framework for Social Network Communication." International Journal of Cooperative Information Systems 27, no. 02 (June 2018): 1850004. http://dx.doi.org/10.1142/s0218843018500041.

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Multimodal Biometric has been widely researched to improve social network user communication. Appropriate modeling of authentication and access control is highly required to perform precise system analysis in a social network framework. In this work, a Multimodal Biometric Secured (MBSec) Social Network User Communication framework to provide user authentic social communication in a safe environment is investigated. The multimodal user biometric features (i.e. face and fingerprint) with neighborhood feature pixel dominancy stored in a spatial vector are gene encoded to generate biometric identity keys. The authenticity of user is validated by decoding gene encoded biometric features with biometric identity keys. User relational coefficient is calculated for users, using prior knowledge instances shared between different social users. The social network user’s relational coefficient is sequenced in a matrix to identify the occurrence of authentic user relational social communication. Experiments were conducted using face and fingerprint images collected from BioSecure dataset. Our results demonstrate that the proposed social network user communication framework is able to significantly improve the true positive rate of authenticated users, compared to conventional FR approaches that only make use of a single model. Further, we demonstrate that our MBSec framework has a low social network authentication time and access control time.
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Shi, Quan. "Guardians of Privacy: Understanding the European Union's Framework for Biometric Data Protection." International Journal of Biology and Life Sciences 3, no. 1 (May 30, 2023): 59–61. http://dx.doi.org/10.54097/ijbls.v3i1.9669.

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With the growing prevalence of biometric technology, individual traits are being stored in an increasing number of databases. Users must maintain a high degree of awareness regarding biometric data security. It's important not to provide biometric details without thorough consideration of its necessity, scrutinizing the existing security measures, and understanding the track record of any entity requesting such information. The laws and regulations concerning this matter vary widely depending on the user's location. The European Union is renowned for its stringent personal data protection laws and robust security standards, imposing reporting responsibilities on any entity that collects and requests user data. This article will delve into the regulations and policies surrounding biometric data protection within the European Union.
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Tiwari, Nitin. "An Overview and Analysis Based on Biometric Framework Technique and Fingerprint Biometric Technology." International Journal of Scientific Research in Computer Science and Engineering 5, no. 6 (December 31, 2017): 69–74. http://dx.doi.org/10.26438/ijsrcse/v5i6.6974.

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Nita, Stefania, Marius Mihailescu, and Valentin Pau. "Security and Cryptographic Challenges for Authentication Based on Biometrics Data." Cryptography 2, no. 4 (December 6, 2018): 39. http://dx.doi.org/10.3390/cryptography2040039.

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Authentication systems based on biometrics characteristics and data represents one of the most important trend in the evolution of the society, e.g., Smart City, Internet-of-Things (IoT), Cloud Computing, Big Data. In the near future, biometrics systems will be everywhere in the society, such as government, education, smart cities, banks etc. Due to its uniqueness, characteristic, biometrics systems will become more and more vulnerable, privacy being one of the most important challenges. The classic cryptographic primitives are not sufficient to assure a strong level of secureness for privacy. The current paper has several objectives. The main objective consists in creating a framework based on cryptographic modules which can be applied in systems with biometric authentication methods. The technologies used in creating the framework are: C#, Java, C++, Python, and Haskell. The wide range of technologies for developing the algorithms give the readers the possibility and not only, to choose the proper modules for their own research or business direction. The cryptographic modules contain algorithms based on machine learning and modern cryptographic algorithms: AES (Advanced Encryption System), SHA-256, RC4, RC5, RC6, MARS, BLOWFISH, TWOFISH, THREEFISH, RSA (Rivest-Shamir-Adleman), Elliptic Curve, and Diffie Hellman. As methods for implementing with success the cryptographic modules, we will propose a methodology which can be used as a how-to guide. The article will focus only on the first category, machine learning, and data clustering, algorithms with applicability in the cloud computing environment. For tests we have used a virtual machine (Virtual Box) with Apache Hadoop and a Biometric Analysis Tool. The weakness of the algorithms and methods implemented within the framework will be evaluated and presented in order for the reader to acknowledge the latest status of the security analysis and the vulnerabilities founded in the mentioned algorithms. Another important result of the authors consists in creating a scheme for biometric enrollment (in Results). The purpose of the scheme is to give a big overview on how to use it, step by step, in real life, and how to use the algorithms. In the end, as a conclusion, the current work paper gives a comprehensive background on the most important and challenging aspects on how to design and implement an authentication system based on biometrics characteristics.
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Kurylo, Mykola, Alyona Klochko, Nataliia Volchenko, Nataliia Klietsova, and Anna Bolotina. "The use of biometric technologies for bank transaction security management against the background of the international experience: Evidence from Ukraine." Banks and Bank Systems 16, no. 2 (May 11, 2021): 47–58. http://dx.doi.org/10.21511/bbs.16(2).2021.05.

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In view of the expanding range of banking services in Ukraine, the issue of introducing innovative means of protecting consumers against illegal actions in the field of banking becomes relevant. This paper aims to determine the effectiveness of biometric technologies for customer identification during banking transactions, the legality of their use, and to identify areas for the development of state policy focused on the legal use of biometric data in order to protect the rights and legitimate interests of individuals and legal entities. Based on analysis and systematization of scientific publications and regulatory framework, it was found that a potential direction for banks to implement the customer focus concept in their services to establish the appropriate level of security is the use of biometric technologies that ensure the proper storage of personal data. The summarized information on the actual application of biometric identification methods in the banking sector allows stating that the factors stipulating the criminal offenses using biometric data can be neutralized by the subjects of counteracting such offenses and through effective legal remedies. Contradictions arising between the state of regulatory support and the actual needs for the use of biometric technologies in the field of banking in Ukraine decelerate the use of effective security tools with a high degree of reliability in the banking sector. It is concluded that further implementation of biometrics in the banking sector in Ukraine requires a comprehensive approach and consideration of the best world practices.
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Kalyan Chakravathy, P., K. Vasavi Devi, T. Sai Sri, and SK Abu Saleha. "An efficient and secured approach for sequential and transparent identity validation of user in internet services." International Journal of Engineering & Technology 7, no. 1.1 (December 21, 2017): 664. http://dx.doi.org/10.14419/ijet.v7i1.1.10823.

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These days, it ends up noticeably genuine worry to give greater security to web administrations. Along these lines, secure client verification is the central assignment in security frameworks. Generally, a large portion of the frameworks depend on sets of username and secret key which checks the personality of client just at authentication stage. Once the client accesses with username and secret key, no checks are performed and encourages amid working sessions. Be that as it may, rising biometric arrangements gives the username and secret key using biometric information of client. In such approach, single shot check is less proficient in light of the fact that personality of client is perpetually amid entire session. Consequently, an important arrangement is to utilize brief time of timeouts for every session and occasionally ask the client to enter his or her qualifications again and again. In any case, this isn't a legitimate arrangement since it vigorously influences the administration convenience and eventually the fulfilment of clients. This paper investigates the framework for nonstop verification of client utilizing his accreditations, for example, biometric qualities. The utilization of consistent biometric verification framework procures certifications without expressly telling the client or requiring client communication that is, straightforwardly which is essential to ensure for better execution and administration ease of use.
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Thanki, Rohit, Surekha Borra, and Ashish Kothari. "Fragile Watermarking Framework for Tamper Detection of Color Biometric Images." International Journal of Digital Crime and Forensics 13, no. 2 (March 2021): 35–56. http://dx.doi.org/10.4018/ijdcf.2021030103.

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Application of fragile watermarking on biometric images stored at a server or cloud ensures proper authentication and tamper detection when access to the servers was shared. In this paper, a hybrid domain fragile watermarking technique for authenticity of color biometric images, using hybridization of various transforms such as discrete cosine transform (DCT), fast discrete curvelet transform (FDCuT), and singular value decomposition (SVD) is proposed. The hybrid transform coefficients are modified according to the scrambled color watermark to obtain watermarked color biometric image. The security of this technique is strengthened with the usage of Arnold scrambling, and by using multiple secret keys. The proposed technique is analyzed on FEI Brazilian face database. The experimental results show that this technique performs better than the existing fragile watermarking techniques.
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42

Alpar, Orcan. "Biometric keystroke barcoding: A next-gen authentication framework." Expert Systems with Applications 177 (September 2021): 114980. http://dx.doi.org/10.1016/j.eswa.2021.114980.

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43

FENG, Quan. "Framework of biometric authentication applied in open network." Journal of Computer Applications 28, no. 5 (October 17, 2008): 1149–51. http://dx.doi.org/10.3724/sp.j.1087.2008.01149.

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Im, Jong-Hyuk, Hee-Yong Kwon, and Mun-Kyu Lee. "Framework for Secure Biometric System Design on Smartphones." KIPS Transactions on Computer and Communication Systems 5, no. 2 (February 29, 2016): 41–46. http://dx.doi.org/10.3745/ktccs.2016.5.2.41.

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45

Bharadwaj, Samarth, Himanshu S. Bhatt, Richa Singh, Mayank Vatsa, and Afzel Noore. "QFuse: Online learning framework for adaptive biometric system." Pattern Recognition 48, no. 11 (November 2015): 3428–39. http://dx.doi.org/10.1016/j.patcog.2015.05.002.

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46

Das, Srijan, Khan Muhammad, Sambit Bakshi, Imon Mukherjee, Pankaj K Sa, Arun Kumar Sangaiah, and Andrea Bruno. "Lip biometric template security framework using spatial steganography." Pattern Recognition Letters 126 (September 2019): 102–10. http://dx.doi.org/10.1016/j.patrec.2018.06.026.

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47

Palaniappan, Ramaswamy, and Danilo P. Mandic. "EEG Based Biometric Framework for Automatic Identity Verification." Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology 49, no. 2 (June 28, 2007): 243–50. http://dx.doi.org/10.1007/s11265-007-0078-1.

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48

Farid, Farnaz, Mahmoud Elkhodr, Fariza Sabrina, Farhad Ahamed, and Ergun Gide. "A Smart Biometric Identity Management Framework for Personalised IoT and Cloud Computing-Based Healthcare Services." Sensors 21, no. 2 (January 14, 2021): 552. http://dx.doi.org/10.3390/s21020552.

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This paper proposes a novel identity management framework for Internet of Things (IoT) and cloud computing-based personalized healthcare systems. The proposed framework uses multimodal encrypted biometric traits to perform authentication. It employs a combination of centralized and federated identity access techniques along with biometric based continuous authentication. The framework uses a fusion of electrocardiogram (ECG) and photoplethysmogram (PPG) signals when performing authentication. In addition to relying on the unique identification characteristics of the users’ biometric traits, the security of the framework is empowered by the use of Homomorphic Encryption (HE). The use of HE allows patients’ data to stay encrypted when being processed or analyzed in the cloud. Thus, providing not only a fast and reliable authentication mechanism, but also closing the door to many traditional security attacks. The framework’s performance was evaluated and validated using a machine learning (ML) model that tested the framework using a dataset of 25 users in seating positions. Compared to using just ECG or PPG signals, the results of using the proposed fused-based biometric framework showed that it was successful in identifying and authenticating all 25 users with 100% accuracy. Hence, offering some significant improvements to the overall security and privacy of personalized healthcare systems.
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Harby, Fahad AL, Rami Qahwajim, and Mumtaz Kamala. "Towards an Understanding of User Acceptance to Use Biometrics Authentication Systems in E-commerce." International Journal of E-Business Research 6, no. 3 (July 2010): 34–55. http://dx.doi.org/10.4018/jebr.2010070103.

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Security is an increasingly important issue for business, and with it, the need for authentication. The use of biometric systems for personal authentication is a response to the rising issue of authentication and security. As with any new technology, user acceptance is often hard to measure, thus, in this work, a study of user acceptance of a biometrics authentication system in e-commerce, such as online banking within the Saudi society, was conducted. The study examined whether Saudis are practically willing to accept this technology by involving 306 participants in a large scale laboratory experiment that actively tested a biometric authentication system in combination of a survey. The Technology Acceptance Model (TAM) was adopted as the theoretical basis to develop the research framework in which the model has proven its efficiency as a good predictor for the study’s application.
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Mala, R. Parimala, and C. Jayakumar Kumar. "Providing Authentication by Using Biometric Multimodal Framework for Cloud Computing." TELKOMNIKA Indonesian Journal of Electrical Engineering 15, no. 3 (September 1, 2015): 591. http://dx.doi.org/10.11591/tijee.v15i3.1578.

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Secret knowledge, like remembering password or token based authentication systems are deemed inconvenience and difficult to use for users such as password may be forgotten or token may be lost. So burdens like remembering password and stolen or forged token based authentication have raised a current trend of biometric authentication system. Now in this current tech world, everyone needs security everywhere to protect our personal gadgets. So to keep it secured, biometric based approach can be applied for better convenience and ease of use for the user. In this paper, a novel hybrid multimodal approach for ear recognition and finger print recognition has been presented for better robustness and efficiency which can be applied in various fields of applications like authentication in banking transactions. Biometric based human recognition is rapidly gaining popularity due to breached of traditional security systems and the lowering cost of sensors. This paper comprehensively reviews multimodal recognition using ear pattern and finger print data, it is concluded that further research should investigate fast and fully automatic ear-finger print multimodal systems robust to occlusions and deformations.
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