Linkable Ring Signature Scheme Using Biometric Cryptosystem and NIZK and Its Application

Biometric encryption, especially based on fingerprint, plays an important role in privacy protection and identity authentication. In this paper, we construct a privacy-preserving linkable ring signature scheme. In our scheme, we utilize a fuzzy symmetric encryption scheme called symmetric keyring encryption (SKE) to hide the secret key and use non-interactive zero-knowledge (NIZK) protocol to ensure that we do not leak any information about the message. Unlike the blind signature, we use NIZK protocol to cancel the interaction between the signer (the prover) and the verifier. The security proof shows that our scheme is secure under the random oracle model. Finally, we implement it on a personal computer and analyze the performance of the constructed scheme in practical terms. Based on the constructed scheme and demo, we give an anonymous cryptocurrency transaction model as well as mobile demonstration.

Sequential subspace estimator for an efficient multibiometrics authentication and encryption.

The principal challenge in biometric authentication is to mitigate the effects of any noise while extracting biometric features for biometric template generation. Most biometric systems are developed under the assumption that the extracted biometrics and the nature of their associated interferences are linear, stationary, and homogeneous. When these assumptions are violated due to nonlinear, nonstationary, and heterogeneous noise, the authentication performance deteriorates. As well, demands for biometric templates are on the rise in the field of information technology, leading to an increase in the vulnerability of stored and dynamic information. Thus, the development of a sophisticated authentication and encryption method is necessary to address these challenges. This dissertation proposes a new Sequential Subspace Estimator (SSE) algorithm for biometric authentication. In the proposed method, a sequential estimator is being designed in the image subspace that addresses challenges arising from nonlinear, nonstationary, and heterogeneous noise. The proposed method includes a subspace technique that overcomes the computational complexity associated with the sequential estimator. In addition, it includes a novel MultiBiometrics encryption algorithm that protects the biometric templates against security, privacy, and unlinkability attacks. Unlike current biometric encryption, this method uses cryptographic keys in conjunction with extracted MultiBiometrics to create cryptographic bonds, called “BioCryptoBond”. To further enhance system security and improve authentication accuracy, the development of a biometric database management system is also being considered. The proposed method is being tested on images from three public databases: the “Put Face Database”, the “Indian Face Database”, and the “CASIA Fingerprint Image Database Version 5.1”. The performance of the proposed solution has been evaluated using the Equal Error Rate (EER) and Correct Recognition Rate (CRR). The experimental results demonstrate the superiority of the proposed method in comparison to its counterparts.

Sequential subspace estimator for an efficient multibiometrics authentication and encryption.

The principal challenge in biometric authentication is to mitigate the effects of any noise while extracting biometric features for biometric template generation. Most biometric systems are developed under the assumption that the extracted biometrics and the nature of their associated interferences are linear, stationary, and homogeneous. When these assumptions are violated due to nonlinear, nonstationary, and heterogeneous noise, the authentication performance deteriorates. As well, demands for biometric templates are on the rise in the field of information technology, leading to an increase in the vulnerability of stored and dynamic information. Thus, the development of a sophisticated authentication and encryption method is necessary to address these challenges. This dissertation proposes a new Sequential Subspace Estimator (SSE) algorithm for biometric authentication. In the proposed method, a sequential estimator is being designed in the image subspace that addresses challenges arising from nonlinear, nonstationary, and heterogeneous noise. The proposed method includes a subspace technique that overcomes the computational complexity associated with the sequential estimator. In addition, it includes a novel MultiBiometrics encryption algorithm that protects the biometric templates against security, privacy, and unlinkability attacks. Unlike current biometric encryption, this method uses cryptographic keys in conjunction with extracted MultiBiometrics to create cryptographic bonds, called “BioCryptoBond”. To further enhance system security and improve authentication accuracy, the development of a biometric database management system is also being considered. The proposed method is being tested on images from three public databases: the “Put Face Database”, the “Indian Face Database”, and the “CASIA Fingerprint Image Database Version 5.1”. The performance of the proposed solution has been evaluated using the Equal Error Rate (EER) and Correct Recognition Rate (CRR). The experimental results demonstrate the superiority of the proposed method in comparison to its counterparts.

Biometric Image Security Using Chaos Algorithm

In this world of Advanced Technology, the Biometrics are proved to be a significant method for user identification. However, the use of biometric is not new, but these days, with the increase in multimedia applications, it has gained its popularity in analysing human characteristics for security purposes. Biometric Encryption using Chaos Algorithm is a technique used to make it more convenient to the user and to provide high level security. The most prominent physical biometric patterns investigated for security purposes are the fingerprint, hand, eye, face, and voice. In the proposed image encryption scheme, an external secret key of 160-bit is used. The initial conditions for the logistic map are derived using the external secret key. The results obtained through experimental analysis provide an efficient and secure way for real-time image encryption and transmission.

Accomplishment of New Protocol for Stupendous Security in Cloud Environment

Cloud is that the rising and thirst area of analysis and advantageous in all the fields. However security is the main disquiet for not espouse cloud for each application. Mainly of the security crisis are connected by authentication with data protection by the respect to cloud security alliance (CSA). The projected New (Biometric encoding and Biometric authentication) protocol can conquer every safety crisis in cloud adjacent. In NEW protocol biometric encryption has been provided for the cloud consumer’s valuable information and identity verification has been utilized in a unique way to scale back the problems associated with authentication and authorization. In NEW protocol Identity verification in cloud environment has been joint by pattern security in coincidence with four entirely dissimilar and influential encryption algorithms for accumulated safety. This protocol improves biometric template protection by the combination of RSA and AES encryption algorithms in proper locations and 3DES, Blowfish has been utilized in information security and solution safety supervision. By implementing such technique can vanish out the un trustiness of adopting cloud, specifically public and hybrid clouds. Since all the users information are hold on in off premise. Adopting this protocol has given nice results when examining with existing work and all the vulnerable places has been considered for improved security.

Combining Watermarking and Hyper-Chaotic Map to Enhance the Security of Stored Biometric Templates

There are a number of issues related to the development of biometric authentication systems, such as privacy breach, consequential security and biometric template storage. Thus, the current paper aims to address these issues through the hybrid approach of watermarking with biometric encryption. A multimodal biometric template protection approach with fusion at score level using fingerprint and face templates is proposed. The proposed approach includes two basic stages, enrollment stage and verification stage. During the enrollment stage, discrete wavelet transform (DWT) is applied on the face images to embed the fingerprint features into different directional sub-bands. Watermark embedding and extraction are done by quantizing the mean values of the wavelet coefficients. Subsequently, the inverse DWT is applied to obtain the watermarked image. Following this, a unique token is assigned for each genuine user and a hyper-chaotic map is used to produce a key stream in order to encrypt a watermarked image using block-cipher. The experimentation results indicate the efficiency of the proposed approach in term of achieving a reasonable error rate of 3.87%.