A New Biometric Template Protection using Random Orthonormal Projection and Fuzzy Commitment

Biometric template protection is one of most essential parts in putting a biometric-based authentication system into practice. There have been many researches proposing different solutions to secure biometric templates of users. They can be categorized into two approaches: feature transformation and biometric cryptosystem. However, no one single template protection approach can satisfy all the requirements of a secure biometric-based authentication system. In this work, we will propose a novel hybrid biometric template protection which takes benefits of both approaches while preventing their limitations. The experiments demonstrate that the performance of the system can be maintained with the support of a new random orthonormal project technique, which reduces the computational complexity while preserving the accuracy. Meanwhile, the security of biometric templates is guaranteed by employing fuzzy commitment protocol.Comment: 11 pages, 6 figures, accepted for IMCOM 201

State of the Art in Biometric Key Binding and Key Generation Schemes

Direct storage of biometric templates in databases exposes the authentication system and legitimate users to numerous security and privacy challenges. Biometric cryptosystems or template protection schemes are used to overcome the security and privacy challenges associated with the use of biometrics as a means of authentication. This paper presents a review of previous works in biometric key binding and key generation schemes. The review focuses on key binding techniques such as biometric encryption, fuzzy commitment scheme, fuzzy vault and shielding function. Two categories of key generation schemes considered are private template and quantization schemes. The paper also discusses the modes of operations, strengths and weaknesses of various kinds of key-based template protection schemes. The goal is to provide the reader with a clear understanding of the current and emerging trends in key-based biometric cryptosystems

Modified shielding function for multi-biometric authentication and template protection / Abayomi Jegede... [et al.]

Biometrics provides a secure means of authentication because it is difficult to copy, forge, or steal biometric modalities. However, unprotected biometric data can be used to violate the security of the authentication system and the privacy of legitimate users. This paper proposes and implements a modified shielding function which provides multi-biometric authentication, template security and user privacy simultaneously. Experimental results based on face and iris datasets obtained from CASIA Near Infra-Red face database and CASIA Iris database version 2 respectively show that the approach has good recognition accuracy (false rejection rate of 0.65% and false acceptance rate of 0.035%). Security analysis shows that the method provides better security (key length of 120 bits) and user privacy compared to previous approaches based on the generic shielding function

Binary Biometric Representation through Pairwise Adaptive Phase Quantization

Extracting binary strings from real-valued biometric templates is a fundamental step in template compression and protection systems, such as fuzzy commitment, fuzzy extractor, secure sketch, and helper data systems. Quantization and coding is the straightforward way to extract binary representations from arbitrary real-valued biometric modalities. In this paper, we propose a pairwise adaptive phase quantization (APQ) method, together with a long-short (LS) pairing strategy, which aims to maximize the overall detection rate. Experimental results on the FVC2000 fingerprint and the FRGC face database show reasonably good verification performances.\ud \u

Anonymous subject identification and privacy information management in video surveillance

The widespread deployment of surveillance cameras has raised serious privacy concerns, and many privacy-enhancing schemes have been recently proposed to automatically redact images of selected individuals in the surveillance video for protection. Of equal importance are the privacy and efficiency of techniques to first, identify those individuals for privacy protection and second, provide access to original surveillance video contents for security analysis. In this paper, we propose an anonymous subject identification and privacy data management system to be used in privacy-aware video surveillance. The anonymous subject identification system uses iris patterns to identify individuals for privacy protection. Anonymity of the iris-matching process is guaranteed through the use of a garbled-circuit (GC)-based iris matching protocol. A novel GC complexity reduction scheme is proposed by simplifying the iris masking process in the protocol. A user-centric privacy information management system is also proposed that allows subjects to anonymously access their privacy information via their iris patterns. The system is composed of two encrypted-domain protocols: The privacy information encryption protocol encrypts the original video records using the iris pattern acquired during the subject identification phase; the privacy information retrieval protocol allows the video records to be anonymously retrieved through a GC-based iris pattern matching process. Experimental results on a public iris biometric database demonstrate the validity of our framework

A hybrid biometric template protection algorithm in fingerprint biometric system

Biometric recognition has achieved a considerable popularity in recent years due its various properties and widespread application in various sectors. These include very top priority sectors like countries boundary security, military, space missions, banks etc. Due to these reasons the stealing of biometric information is a critical issue. To protect this user biometric template information there should be efficient biometric template transformation technique and thereby the privacy of user is preserved. Non-invertible transformation can keep the user template based transformed information maximum secure against the regeneration. But the performance of non-invertible template protection mechanism will be reduced by the increase in security. This limitation of non-invertible biometric transformation should be solved. This research aims to develop a hybrid biometric template protection algorithm to keep up a balance between security and performance in fingerprint biometric system. The hybrid biometric template protection algorithm is developed from the combination of non-invertible biometric transformation and biometric key generation techniques. To meet the research objective this proposed framework composed of three phases: First phase focus on the extraction of fingerprint minutiae and formation of vector table, while second phase focus on develop a hybrid biometric template protection algorithm and finally the third phase focus on evaluation of performance of the proposed algorithm

Digest: A Biometric Authentication Protocol in Wireless Sensor Network

Since the security of biometric information may be threatened by network attacks, presenting individual’s information without a suitable protection is not suitable for authorization. In traditional cryptographic systems, security was done using individual’s password(s) or driving some other data from primary information as secret key(s). However, encryption and decryption algorithms are slow and contain time-consuming operations for transferring data in network. Thus, it is better that we have no need to decrypt an encrypted trait of an enrolled person, and the system can encrypt the user trait with the user’s passwords and then compare the results with the enrolled persons’ encrypted data stored in database. In this chapter, by considering wireless sensor networks and authenticating server, we introduce a new concept called “digest” and deal with its efficiency in dealing with the security problem. A “digest” can be derived from any kind of information trait through which nobody can capture any information of primary biometric traits. We show that this concept leads to the increase of the accuracy and accessibility of a biometric system

Strong authentication based on mobile application

The user authentication in online services has evolved over time from the old username and password-based approaches to current strong authentication methodologies. Especially, the smartphone app has become one of the most important forms to perform the authentication. This thesis describes various authentication methods used previously and discusses about possible factors that generated the demand for the current strong authentication approach. We present the concepts and architectures of mobile application based authentication systems. Furthermore, we take closer look into the security of the mobile application based authentication approach. Mobile apps have various attack vectors that need to be taken under consideration when designing an authentication system. Fortunately, various generic software protection mechanisms have been developed during the last decades. We discuss how these mechanisms can be utilized in mobile app environment and in the authentication context. The main idea of this thesis is to gather relevant information about the authentication history and to be able to build a view of strong authentication evolution. This history and the aspects of the evolution are used to state hypothesis about the future research and development. We predict that the authentication systems in the future may be based on a holistic view of the behavioral patterns and physical properties of the user. Machine learning may be used in the future to implement an autonomous authentication concept that enables users to be authenticated with minimal physical or cognitive effort

Security Features in Fingerprint Biometric System

Nowadays, embedded systems run in every setting all around the globe. Recent advances in technology have created many sophisticated applications rich with functionality we have never seen. Nonetheless, security and privacy were a common issue for these systems, whether or not sensitive data can be protected from malicious attacks. These concerns are justified on the grounds that the past of security breaches and the resulting consequences narrate horrific stories concerning embedded systems. The attacks are now evolving, becoming more complex with technological advancements. Therefore, a new way of implementing security in embedded systems must be pursued. This paper attempts to demonstrate the incorporation of security features in fingerprint biometric system in the requirements analysis phase, ensuring the same throughout the system life cycle of embedded systems based on case study. The comparison of various biometric technologies such as face, fingerprint, iris, palm print, hand geometry gait, signature, and keystroke is presented. The aim of this paper includes analyzing, decomposing and transforming the threats and counter-measures identified during the requirements analysis using the abuse case into more specific safety requirements or functions. Furthermore, we have shown that the incorporation of security features into the biometric fingerprint system by analyzing the requirements of the system and providing the main steps for the protection of the biometric system in this paper