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Image authentication is an important field that employs many different approaches and has several significant applications. In the proposed approach, we used a combination of two techniques to achieve authentication. Image watermarking is one of the techniques that has been used in many studies but the authentication field still needs to be studied. Blockchain technology is a relatively new technology that has significant research potential related to image authentication. The watermark is embedded into the third-level discrete wavelet transform (DWT) in the middle frequency regions to achieve security and imperceptibility goals. Peak signal-to-noise ratio PSNR, structural similarity matrix (SSIM), normalized correlation coefficient (NCC), and bit error rate (BER) are used to measure the performance of image watermarking. We used blockchain technology to avoid involving a trusted third party for authentication. Secure Hash Algorithm 256 (SHA-256) is applied on the watermark to save it into the blockchain. The watermark is encrypted using Advanced Encryption Standard (AES) and embedded into the image. The proposed method is tested on the USP SICI database and the MedPix medical image database. Ethereum blockchain is used to provide security, anonymity, and integrity of data with no third-party intervention. The proposed solution demonstrates enhanced security for image authentication compared with the state-of-the-art. [ABSTRACT FROM AUTHOR]

Biometric template disclosure starts gaining an important concern in deploying practical biometric authentication systems, where an assailant compromises the database for illegitimate access. To protect biometric templates from disclosure attacks, biometric authentication systems should meet these four requirements: security, diversity, revocability, and performance. Different methods have been suggested in the literature such as feature transformation techniques and biometric cryptosystems. However, no single method could satisfy the four requirements, giving rise to the deployment of hybrid mechanisms. In this context, the current paper proposes a hybrid system for multimodal biometric template protection to provide robustness against template database attacks. Herein, a secure sketch method is first applied to secure the fingerprint modality. Subsequently, a Dual-Tree Complex Wavelet Transform Discrete Cosine Transform (DTCWT-DCT) based watermarking is employed to entrench the fingerprint sketch into the face image. However, a 3D chaotic-map-based encryption method is employed to protect the watermarked facial image in order to offer an added security level. The experimentation performed using the ORL face database and three Fingerprint Verification Competition (FVC) fingerprint databases showed the approach's efficiency in withstanding standard digital image watermarking attacks, brute force attacks, and information leakage. Moreover, the results revealed that the approach achieves high performance, and satisfies diversity and revocability requirements. [ABSTRACT FROM AUTHOR]

In health sector, trust is considered important because it indirectly influences the quality of health care through patient satisfaction, adherence and the continuity of its relationship with health care professionals and the promotion of accurate and timely diagnoses. One of the important requirements of TRSs in the health sector is rating secrecy, which mandates that the identification information about the service consumer should be kept secret to prevent any privacy violation. Anonymity and trust are two imperative objectives, and no significant explicit efforts have been made to achieve both of them at the same time. In this paper, we present a framework for solving the problem of reconciling trust with anonymity in the health sector. Our solution comprises Anonymous Reputation Management (ARM) protocol and Context-aware Trustworthiness Assessment (CTA) protocol. ARM protocol ensures that only those service consumers who received a service from a specific service provider provide a recommendation score anonymously with in the specified time limit. The CTA protocol computes the reputation of a user as a service provider and as a recommender. To determine the correctness of the proposed ARM protocol, formal modelling and verification are performed using High Level Petri Nets (HLPN) and Z3 Solver. Our simulation results verify the accuracy of the proposed context-aware trust assessment scheme. [ABSTRACT FROM AUTHOR]