A New Biocryptosystem-Oriented Security Analysis Framework and Implementation of Multibiometric Cryptosystems Based on Decision Level Fusion

BIOFUSE: A framework for multi-biometric fusion on biocryptosystem level

Template-Protection-Techniken stellen eine wichtige Ergänzung zu biometrischen Systemen, um das gewünschte Sicherheitsniveau zu erreichen und die Anforderungen an den Schutz der Privatsphäre zu erfüllen. Diese Techniken ermöglichen Erneuerung und Widerruf der Referenzendaten in biometrischen Systemen. In dieser Arbeit wird ein systematisches Evaluierungsframework entwickelt, das sich an die wesentlichen Kriterien und Anforderungen an biometrische Template-Protection-Verfahren festhält. Seine Anwendbarkeit wird durch die Analyse der verschiedenen Algorithmen demonstriert. Die in dieser Arbeit präsentierte Evaluierung ist grundlegend für eine vollständige Analyse. Darüber hinaus ermöglicht es einen Nachweis der Sicherheit und Einhaltung der Privatsphäre. Es schafft eine Basis für Zertifizierung und Benchmark der Template-Protection-Verfahren.

In a biometric authentication system using protected templates, a pseudonymous identifier is the part of a protected template that can be directly compared. Each compared pair of pseudonymous identifiers results in a decision testing whether both identifiers are derived from the same biometric characteristic. Compared to an unprotected system, most existing biometric template protection methods cause to a certain extent degradation in biometric performance. Fusion is therefore a promising way to enhance the biometric performance in template-protected biometric systems. Compared to feature level fusion and score level fusion, decision level fusion has not only the least fusion complexity, but also the maximum interoperability across different biometric features, template protection and recognition algorithms, templates formats, and comparison score rules. However, performance improvement via decision level fusion is not obvious. It is influenced by both the dependency and the performance gap among the conducted tests for fusion. We investigate in this paper several fusion scenarios (multi-sample, multi-instance, multi-sensor, multi-algorithm, and their combinations) on the binary decision level, and evaluate their biometric performance and fusion efficiency on a multi-sensor fingerprint database with 71,994 samples.

Security analysis and improvement of some biometric protected templates based on Bloom filters

The need for fool proof authentication procedures away from traditional authentication mechanisms like passwords, security PINS has led to the advent of biometric authentication in information systems. Biometric data extracted from physiological features of a person including but not limited to fingerprints, palm prints, face or retina for purpose of verification & identification is saved as biometric templates. The inception of biometrics in access control systems has not been without its own hitches & like other systems it has its fair share of challenges. Biometric fingerprints being the most mature of all biometric spheres are the most widely adopted biometric authentication systems. Biometric systems effectiveness lies on how secure they are at preventing inadvertent disclosure of biometric templates in an information system’s archive. This however has not been the case as biometric templates have been fraudulently accessed to gain unauthorized access in identification and verification systems. In order to achieve strong and secure biometric systems, biometric systems developers need to build biometric systems that properly secure biometric templates. Several biometric template protection schemes and approaches have been proposed and used to safeguard stored biometric templates. Despite there being various biometric template protection schemes and approaches in existence, none of them has provided the most authentic, reliable, efficient and deterrent means to totally secure biometric fingerprint templates. This research sought to establish status of the current biometric template protection techniques and methods by conducting a survey and analyzing data gathered from a sample of seventy-eight (78) respondents. We will report these results and give our conclusion based on findings of the survey in this paper.

Hash functions, which can extract message digest from input messages as output, play an important role in digital signature and authentication. Meanwhile, Hash functions are essential in many cryptographic protocols and regimes. With the research becoming more and more in depth, a series of Hash functions is proposed, such as MD series and SHA series. At the same time, the security analysis and attacks against Hash functions are carried out. The security of Hash functions is threatened. In this case, how to improve the security of the Hash functions becomes the primary concern. In this paper, an optical Hash function based on the interaction between light and multiple scattering media is proposed. Unlike most of the traditional Hash functions which are based on mathematical transformations or complex logic operations, this method innovatively takes advantage of the natural random scattering effect of multiple scattering media on coherently modulated light, and realizes the “confusion” and “diffusion” of modulated light, which satisfies the core functional requirement of the Hash function: one-way encoding/encryption with strong security. The photoelectric hybrid system designed by this method can effectively simulate the "compression function" in the Hash function. Combined with the Sobel filter with feature extraction function, the input data of arbitrary length can be compressed and encrypted into the output with a fixed length of 256-bit (Hash value). The principle of the proposed optical Hash function can be described as follows. 1) Two 8-bit images with a size of 16×16 pixels are loaded in SLM<sub>1</sub> (amplitude-only spatial modulator) and SLM<sub>2</sub> (phase-only spatial modulator) respectively. 2) The coherent wavefront is modulated by SLM<sub>1</sub> and SLM<sub>2</sub>, and then propagates on multiple scattering media. 3) A speckle pattern is recorded by CCD because of the confusion of multiple scattering media. 4) The features of the speckle pattern, which is extracted by Sobel filter, serve as the input of the next compression function. For the unpredicted and non-duplicated disorder multiple scattering media, it is tremendously difficult to determine the internal state of the multiple scattering media. Therefore, the proposed optical Hash function is considered to have a high security. A series of simulation results shows that the proposed optical Hash function has a good “avalanche effect” and “collision resistance”, and its security performance is comparable to that of the most widely used traditional Hash functions (MD5 and SHA-1).

Key management, particularly, biometric cryptosystem is an exciting field in the system security domain. The challenges associated with this domain need to be addressed in detail since the security of the biometric template is itself a big challenge. Biometric template once lost or copied cannot be changed like simple password. This paper summarizes and discusses major challenges of biometric cryptosystem; categorization of the attacks and their known remedies has also been highlighted.

Nowadays, biometric recognition represents an integral component of identity management and access control systems, replacing PINs or passwords. However, the wide deployment of biometric recognition systems in the past decades has raised numerous privacy concerns regarding the storage and use of biometric data. Due to the fact that the link between individuals and their biometric characteristics, e.g. fingerprints or iris, is strong and permanent, biometric reference data (templates) need to be protected in order to safeguard individuals' privacy and biometric systems' security. In particular, unprotected biometric templates can be abused to crossmatch biometric databases, i.e. tracking individuals without consent, and to launch presentation attacks employing specific inversion techniques. Technologies of biometric template protection offer solutions to privacy preserving biometric authentication, which improves the public confidence and acceptance of biometric systems. While biometric template protection has been an active research topic over the last 20 years, proposed solutions are still far from gaining practical acceptance. The existing gap between theory and practice, which results in a trade-off between privacy protection and recognition accuracy, is caused by numerous factors. To facilitate a standardized design and application of biometric template protection schemes, researchers have to solve several open problems. This chapter provides an overview of state-of-the-art technologies of biometric template protection and discusses main issues and challenges.

The widespread deployment of biometric systems has raised public concern about security and privacy of personal data. In this paper, we present a novel framework for biometric template security in multimodal biometric authentication systems based on error correcting codes. Biometric recognition is formulated as a channel coding problem with noisy side information at the decoder based on distributed source coding principles. It is shown that the proposed method binds the biometric template in a cryptographic key which does not reveal any information about the original biometric data even if it is compromised by an attacker. Furthermore, the advantages of the proposed method in terms of security and impact on matching accuracy are discussed. We assess the performance of the proposed method in the context of HUMABIO, an EU Specific Targeted Research Project, where face and gait biometrics are employed in an unobtrusive application scenario for human authentication. Experimental evaluation on a multimodal biometric database demonstrates the validity of the proposed method.

In this paper, we clarify the security of practical cryptosystems with hash functions based on key derivation functions (KDFs). We use the indifferentiability framework in order to discuss the security because the indifferentiability from Random Oracle (and its variants) guarantees that cryptosystems remain secure even if Random Oracles (ROs) are instantiated with hash functions. Though previous works on the indifferentiability of Merkle-Damgård (MD) hash functions focus on stand-alone hash functions, there is no work which focuses on MD hash functions with KDFs. Many cryptosystems need longer output lengths of hash functions than stand-alone hash functions and KDFs are used to generate longer digests as specified in PKCS #1 v2.1 and IEEE P1363. Specifically, we obtain the following results. We denote the MD hash function using Stam’s type-II compression function by MD-SCFII and MD-SCFII with KDFs by KDF-MD-SCFII. Cryptosystems secure in the pub-RO model (FDH, PSS, Fiat-Shamir, and so on): Dodis et al. proposed the indifferentiability from pub-RO to prove the security of these cryptosystems using MD-SCFII while did not consider the KDF structures. So we propose a different framework, indifferentiability from privleak-RO. Using this framework and their result, we show that these cryptosystems using KDF-MD-SCFIIs are secure. Encryption schemes secure in the RO model (OAEP, RSA-KEM, PSEC-KEM, ECIES-KEM and so on): The encryption schemes are secure in the “fixed inputl length” RO model because the input lengths of ROs from the encryption schemes are fixed. We show that this fact guarantees the security of the encryption schemes using KDF-MD-SCFII. KeywordsHash FunctionEncryption SchemeRandom OracleCompression FunctionRandom Oracle ModelThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Data privacy is crucial when dealing with biometric data. Accounting for the latest European data privacy regulation and payment service directive, biometric template protection is essential for any commercial application. Ensuring unlinkability across biometric service operators, irreversibility of leaked encrypted templates, and renewability of e.g., voice models following the i-vector paradigm, biometric voice-based systems are prepared for the latest EU data privacy legislation. Employing Paillier cryptosystems, Euclidean and cosine comparators are known to ensure data privacy demands, without loss of discrimination nor calibration performance. Bridging gaps from template protection to speaker recognition, two architectures are proposed for the two-covariance comparator, serving as a generative model in this study. The first architecture preserves privacy of biometric data capture subjects. In the second architecture, model parameters of the comparator are encrypted as well, such that biometric service providers can supply the same comparison modules employing different key pairs to multiple biometric service operators. An experimental proof-of-concept and complexity analysis is carried out on the data from the 2013-2014 NIST i-vector machine learning challenge.

Due to the enormous usage of the internet for transmission of data over a network, security and authenticity become major risks. Major challenges encountered in biometric system are the misuse of enrolled biometric templates stored in database server. To describe these issues various algorithms are implemented to deliver better protection to biometric traits such as physical (Face, fingerprint, Ear etc.) and behavioural (Gesture, Voice, tying etc.) by means of matching and verification process. In this work, biometric security system with fuzzy extractor and convolutional neural networks using face attribute is proposed which provides different choices for supporting cryptographic processes to the confidential data. The proposed system not only offers security but also enhances the system execution by discrepancy conservation of binary templates. Here Face Attribute Convolutional Neural Network (FACNN) is used to generate binary codes from nodal points which act as a key to encrypt and decrypt the entire data for further processing. Implementing Artificial Intelligence (AI) into the proposed system, automatically upgrades and replaces the previously stored biometric template after certain time period to reduce the risk of ageing difference while processing. Binary codes generated from face templates are used not only for cryptographic approach is also used for biometric process of enrolment and verification. Three main face data sets are taken into the evaluation to attain system performance by improving the efficiency of matching performance to verify authenticity. This system enhances the system performance by 8% matching and verification and minimizes the False Acceptance Rate (FAR), False Rejection Rate (FRR) and Equal Error Rate (EER) by 6 times and increases the data privacy through the biometric cryptosystem by 98.2% while compared to other work.

In this paper, we propose a new hash function based on RC4 and we call it RC4-Hash. This proposed hash function produces variable length hash output from 16 bytes to 64 bytes. Our RC4-Hash has several advantages over many popularly known hash functions. Its efficiency is comparable with widely used known hash function (e.g., SHA-1). Seen in the light of recent attacks on MD4, MD5, SHA-0, SHA-1 and on RIPEMD, there is a serious need to consider other hash function design strategies. We present a concrete hash function design with completely new internal structure. The security analysis of RC4-Hash can be made in the view of the security analysis of RC4 (which is well studied) as well as the attacks on different hash functions. Our hash function is very simple and rules out all possible generic attacks. To the best of our knowledge, the design criteria of our hash function is different from all previously known hash functions. We believe our hash function to be secure and will appreciate security analysis and any other comments.

Secure multiparty computation is a research focus in the international cryptographic community and a key privacy preserving technology in cyberspaces. Secure multiparty computation for the weighted average problem has great significance, and there are a wide range of applications for this problem. However, there are only a few solutions to this problem at present. In addition, to the best of our knowledge, most of the existing secure multiparty computation schemes for weighted average cannot exclude the influence of invalid data on the weighted average. To address this challenge, in this paper, we propose a corresponding solution to eliminate the influence of invalid data on the final result, and specific number of participants who give invalid datas will not be revealed. A new secure multiparty computation protocol for weighted average are designed to effectively resist different levels of collusion attacks, and the security analysis and performance analysis of the protocol is given. Finally, secure multiparty computation protocol for the weighted average problem is applied to solve secure data aggregation problem, secure weighted voting problem, and privacy-preserving location proximity detection.

The fuzzy vault is an innovative way to share secret keys, combining traditional cryptography with biometrics and biometric template protection. This method forms the basis for the reliable operation of unmanned aerial vehicles (UAVs) through anonymizing drone operators and safely using their data and onboard information. However, due to the inherent instability of biometrics, traditional fuzzy vault schemes face challenges, such as reduced recognition rates with increased chaff points, impractical runtimes due to high-order polynomial reconstruction, and susceptibility to correlation attacks. This paper proposes an efficient fuzzy vault scheme to address these challenges. We generate two secret keys based on biometrics: the first key is produced from the operator’s unique features like the face and iris, using a confidence interval; the second key, used to construct a polynomial, is based on what the operator remembers. These dual-key fuzzy vaults enable the stable generation of genuine points during encoding, easy extraction during decoding, and effective operator authentication while maintaining anonymity. Our experimental results demonstrate improved security and secret acquisition accuracy using the AR face database. These results are achieved regardless of increased false vaults, enabling real-time polynomial reconstruction and resilience against correlation attacks. Importantly, our enhanced fuzzy vault scheme allows the application of this secure, real-time authentication process, safeguarding the anonymity of drone operators.