Biometrics for internet‐of‐things security: A review

The large number of Internet‐of‐Things (IoT) devices that need interaction between smart devices and consumers makes security critical to an IoT environment. Biometrics offers an interesting window of opportunity to improve the usability and security of IoT and can play a significant role in securing a wide range of emerging IoT devices to address security challenges. The purpose of this review is to provide a comprehensive survey on the current biometrics research in IoT security, especially focusing on two important aspects, authentication and encryption. Regarding authentication, contemporary biometric‐based authentication systems for IoT are discussed and classified based on different biometric traits and the number of biometric traits employed in the system. As for encryption, biometric‐cryptographic systems, which integrate biometrics with cryptography and take advantage of both to provide enhanced security for IoT, are thoroughly reviewed and discussed. Moreover, challenges arising from applying biometrics to IoT and potential solutions are identified and analyzed. With an insight into the state‐of‐the‐art research in biometrics for IoT security, this review paper helps advance the study in the field and assists researchers in gaining a good understanding of forward‐looking issues and future research directions

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

Fuzzy vault scheme for fingerprint verification: implementation, analysis and improvements

Fuzzy vault is a well-known technique that is used in biometric authentication applications. This thesis handles the fuzzy vault scheme and improves it to strengthen against previously suggested attacks while analyzing the effects of these improvements on the performance. We compare the performances of two different methods used in the implementation of fuzzy vault, namely brute force and Reed Solomon decoding with fingerprint biometric data. We show that the locations of fake (chaff) points leak some valuable information and propose a new chaff point placement technique that prevents that information leakage. A novel method for chaff point creation that decreases the success rate of the brute force attack from 100% to less than 3.3% is also proposed in this work. Moreover, a special hash function that allows us to perform matching in the hash space which protects the biometric information against the 'correlation attack' is proposed. Security analysis of this method is also presented in this thesis. We implemented the scheme with and without the hash function to calculate false accept and false reject rates in different settings

Developing an Algorithm for Securing the Biometric Data Template in the Database

This research article published by the International Journal of Advanced Computer Science and Applications, Vol. 10, No. 10, 2019In the current technology advancement, biometric template provides a dependable solution to the problem of user verification in an identity control system. The template is saved in the database during the enrollment and compared with query information in the verification stage. Serious security and privacy concerns can arise, if raw, unprotected data template is saved in the database. An attacker can hack the template information in the database to gain illicit access. A novel approach of encryption-decryption algorithm utilizing a design pattern of Model View Template (MVT) is developed to secure the biometric data template. The model manages information logically, the view shows the visualization of the data, and the template addresses the data migration into pattern object. The established algorithm is based on the cryptographic module of the Fernet key instance. The Fernet keys are combined to generate a multiFernet key to produce two encrypted files (byte and text file). These files are incorporated with Twilio message and securely preserved in the database. In the event where an attacker tries to access the biometric data template in the database, the system alerts the user and stops the attacker from unauthorized access, and cross-verify the impersonator based on the validation of the ownership. Thus, helps inform the users and the authority of, how secure the individual biometric data template is, and provided a high level of the security pertaining the individual data privac

Machinic Eyes: New and Post-Digital Aesthetics, Surveillance, and Resistance

This work concerns the rise of the New Aesthetic, an art project developed by James Bridle in 2012. The New Aesthetic, as envisioned by Bridle, was chiefly concerned with the overlapping of physical and digital realities through both the artifacts produced by this overlapping and the systems involved therein. I introduce the advent of the New Aesthetic and present the major criticisms: the lack of a robust theoretical and scholarly framework, the lack of a historical framework, the privileging of artifacts over systems as new Aesthetic, and the fragmented scholarly outlook on the New Aesthetic. Upon further examination, I discovered that the New Aesthetic is less of an art project but a metaphor for a global surveillance apparatus that is the result of clandestine partnerships between multinational technology corporations and intelligence agencies associated the Five Eyes consortium. In this dissertation, I critique the New Aesthetic from a scholarly viewpoint, offer a historical precedent of how the New Aesthetic came to be from cultural and technological perspectives, examine the rise of the global surveillance apparatus within the New Aesthetic, and offer ideas of how to resist surveillance as a result of our reliance upon computational technologies

Biometric Cryptosystems : Authentication, Encryption and Signature for Biometric Identities

Biometrics have been used for secure identification and authentication for more than two decades since biometric data is unique, non-transferable, unforgettable, and always with us. Recently, biometrics has pervaded other aspects of security applications that can be listed under the topic of ``Biometric Cryptosystems''. Although the security of some of these systems is questionable when they are utilized alone, integration with other technologies such as digital signatures or Identity Based Encryption (IBE) schemes results in cryptographically secure applications of biometrics. It is exactly this field of biometric cryptosystems that we focused in this thesis. In particular, our goal is to design cryptographic protocols for biometrics in the framework of a realistic security model with a security reduction. Our protocols are designed for biometric based encryption, signature and remote authentication. We first analyze the recently introduced biometric remote authentication schemes designed according to the security model of Bringer et al.. In this model, we show that one can improve the database storage cost significantly by designing a new architecture, which is a two-factor authentication protocol. This construction is also secure against the new attacks we present, which disprove the claimed security of remote authentication schemes, in particular the ones requiring a secure sketch. Thus, we introduce a new notion called ``Weak-identity Privacy'' and propose a new construction by combining cancelable biometrics and distributed remote authentication in order to obtain a highly secure biometric authentication system. We continue our research on biometric remote authentication by analyzing the security issues of multi-factor biometric authentication (MFBA). We formally describe the security model for MFBA that captures simultaneous attacks against these systems and define the notion of user privacy, where the goal of the adversary is to impersonate a client to the server. We design a new protocol by combining bipartite biotokens, homomorphic encryption and zero-knowledge proofs and provide a security reduction to achieve user privacy. The main difference of this MFBA protocol is that the server-side computations are performed in the encrypted domain but without requiring a decryption key for the authentication decision of the server. Thus, leakage of the secret key of any system component does not affect the security of the scheme as opposed to the current biometric systems involving cryptographic techniques. We also show that there is a tradeoff between the security level the scheme achieves and the requirement for making the authentication decision without using any secret key. In the second part of the thesis, we delve into biometric-based signature and encryption schemes. We start by designing a new biometric IBS system that is based on the currently most efficient pairing based signature scheme in the literature. We prove the security of our new scheme in the framework of a stronger model compared to existing adversarial models for fuzzy IBS, which basically simulates the leakage of partial secret key components of the challenge identity. In accordance with the novel features of this scheme, we describe a new biometric IBE system called as BIO-IBE. BIO-IBE differs from the current fuzzy systems with its key generation method that not only allows for a larger set of encryption systems to function for biometric identities, but also provides a better accuracy/identification of the users in the system. In this context, BIO-IBE is the first scheme that allows for the use of multi-modal biometrics to avoid collision attacks. Finally, BIO-IBE outperforms the current schemes and for small-universe of attributes, it is secure in the standard model with a better efficiency compared to its counterpart. Another contribution of this thesis is the design of biometric IBE systems without using pairings. In fact, current fuzzy IBE schemes are secure under (stronger) bilinear assumptions and the decryption of each message requires pairing computations almost equal to the number of attributes defining the user. Thus, fuzzy IBE makes error-tolerant encryption possible at the expense of efficiency and security. Hence, we design a completely new construction for biometric IBE based on error-correcting codes, generic conversion schemes and weakly secure anonymous IBE schemes that encrypt a message bit by bit. The resulting scheme is anonymous, highly secure and more efficient compared to pairing-based biometric IBE, especially for the decryption phase. The security of our generic construction is reduced to the security of the anonymous IBE scheme, which is based on the Quadratic Residuosity assumption. The binding of biometric features to the user's identity is achieved similar to BIO-IBE, thus, preserving the advantages of its key generation procedure

Information Theoretic-Based Privacy Protection on Data Publishing and Biometric Authentication

Ph.DDOCTOR OF PHILOSOPH

Development of secured algorithm to enhance the privacy and security template of biometric technology

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Mathematical and Computer Science and Engineering of the Nelson Mandela African Institution of Science and TechnologyThe security of information and personal privacy are the growing concerns in today’s human life worldwide. The storage of biometric data in the database has raised the prospect of compromising the database leading to grave risks and misuse of the person’s privacy such as growth in terrorism and identity fraud. When a person’s biometric data stored is revealed, their security and privacy are being compromised. This research described a detailed evaluation on several outbreaks and threats associated with the biometric technology. It analyzed the user’s fear and intimidations to the biometric technology alongside the protection steps for securing the biometric data template in the database. It is known that, when somebody’s biometric data template is compromised from the database that consequently might indicate proof of identity robbery of that person. Mixed method to compute and articulate the results as well as a new tactic of encryption-decryption algorithm with a design pattern of Model View Template (MVT) are used for securing the biometric data template in the database. The model managed information logically, the view indicated the visualization of the data, and the template directed the data migration into pattern object. Factors influencing fear of biometric technology such as an exposer of personal information, improper data transfer, and data misuse are found. Strong knowledge of the ideal technology like the private skills of the biometric technology, data secrecy and perceived helpfulness are established. The fears and attacks along the technology like a counterfeit of documents and brute-force attack are known. The designed algorithm based on the cryptographic module of the Fernet keys instance are utilized. The Fernet keys are combined to generate a multiFernet key, integrated with biometric data to produce two encrypted files (byte and text file). These files are incorporated with Twilio message and firmly stored in the database. The storage database has security measures that guard against an impostor’s attack. The database system can block the attacker from unauthorized access. Thus, significantly increased individual data privacy and integrity

Secret-key rates and privacy leakage in biometric systems

In this thesis both the generation of secret keys from biometric data and the binding of secret keys to biometric data are investigated. These secret keys can be used to regulate access to sensitive data, services, and environments. In a biometric secrecy system a secret key is generated or chosen during an enrollment procedure in which biometric data are observed for the first time. This key is to be reconstructed after these biometric data are observed for the second time when authentication is required. Since biometric measurements are typically noisy, reliable biometric secrecy systems also extract so-called helper data from the biometric observation at the time of enrollment. These helper data facilitate reliable reconstruction of the secret key in the authentication process. Since the helper data are assumed to be public, they should not contain information about the secret key. We say that the secrecy leakage should be negligible. Important parameters of biometric key-generation and key-binding systems include the size of the generated or chosen secret key and the information that the helper data contain (leak) about the biometric observation. This latter parameter is called privacy leakage. Ideally the privacy leakage should be small, to prevent the biometric data of an individual from being compromised. Moreover, the secret-key length (also characterized by the secret-key rate) should be large to minimize the probability that the secret key is guessed and unauthorized access is granted. The first part of this thesis mainly focuses on the fundamental trade-off between the secret-key rate and the privacy-leakage rate in biometric secret-generation and secretbinding systems. This trade-off is studied from an information-theoretical perspective for four biometric settings. The first setting is the classical secret-generation setting as proposed by Maurer [1993] and Ahlswede and Csiszár [1993]. For this setting the achievable secret-key vs. privacy-leakage rate region is determined in this thesis. In the second setting the secret key is not generated by the terminals, but independently chosen during enrollment (key binding). Also for this setting the region of achievable secret-key vs. privacy-leakage rate pairs is determined. In settings three and four zero-leakage systems are considered. In these systems the public message should contain only a negligible amount of information about both the secret key and the biometric enrollment sequence. To achieve this, a private key is needed, which can be observed only by the two terminals. Again both the secret generation setting and chosen secret setting are considered. For these two cases the regions of achievable secret-key vs. private-key rate pairs are determined. For all four settings two notions of leakage are considered. Depending on whether one looks at secrecy and privacy leakage separately or in combination, unconditional or conditional privacy leakage is considered. Here unconditional leakage corresponds to the mutual information between the helper data and the biometric enrollment sequence, while the conditional leakage relates to the conditional version of this mutual information, given the secret. The second part of the thesis focuses on the privacy- and secrecy-leakage analysis of the fuzzy commitment scheme. Fuzzy commitment, proposed by Juels and Wattenberg [1999], is, in fact, a particular realization of a binary biometric secrecy system with a chosen secret key. In this scheme the helper data are constructed as a codeword from an error-correcting code, used to encode a chosen secret, masked with the biometric sequence that has been observed during enrollment. Since this scheme is not privacy preserving in the conditional privacy-leakage sense, the unconditional privacy-leakage case is investigated. Four cases of biometric sources are considered, i.e. memoryless and totally-symmetric biometric sources, memoryless and input-symmetric biometric sources, memoryless biometric sources, and stationary and ergodic biometric sources. For the first two cases the achievable rate-leakage regions are determined. In these cases the secrecy leakage rate need not be positive. For the other two cases only outer bounds on achievable rate-leakage regions are found. These bounds, moreover, are sharpened for fuzzy commitment based on systematic parity-check codes. Using the fundamental trade-offs found in the first part of this thesis, it is shown that fuzzy commitment is only optimal for memoryless totally-symmetric biometric sources and only at the maximum secret-key rate. Moreover, it is demonstrated that for memoryless and stationary ergodic biometric sources, which are not input-symmetric, the fuzzy commitment scheme leaks information on both the secret key and the biometric data. Biometric sequences have an often unknown statistical structure (model) that can be quite complex. The last part of this dissertation addresses the problem of finding the maximum a posteriori (MAP) model for a pair of observed biometric sequences and the problem of estimating the maximum secret-key rate from these sequences. A universal source coding procedure called the Context-TreeWeighting (CTW) method [1995] can be used to find this MAP model. In this thesis a procedure that determines the MAP model, based on the so-called beta-implementation of the CTW method, is proposed. Moreover, CTW methods are used to compress the biometric sequences and sequence pairs in order to estimate the mutual information between the sequences. However, CTW methods were primarily developed for compressing onedimensional sources, while biometric data are often modeled as two-dimensional processes. Therefore it is proved here that the entropy of a stationary two-dimensional source can be expressed as a limit of a series of conditional entropies. This result is also extended to the conditional entropy of one two-dimensional source given another one. As a consequence entropy and mutual information estimates can be obtained from CTW methods using properly-chosen templates. Using such techniques estimates of the maximum secret-key rate for physical unclonable functions (PUFs) are determined from a data-set of observed sequences. PUFs can be regarded as inanimate analogues of biometrics