Ultrasound images are used in various branches of medicine to detect diseases. The process of obtaining this data is complex due to procedures and legal restrictions, leading to scarce datasets. Different data augmentation techniques can be employed to improve classification performance. This paper shows that augmenting the ultrasound breast cancer images dataset using generative adversarial networks (GANs) increased the classification accuracy compared to the original dataset and compared to the dataset augmented using standard techniques.

Digital credentials represent a cornerstone of digital identity on the Internet. To achieve privacy, certain functionalities in credentials should be implemented. One is selective disclosure, which allows users to disclose only the claims or attributes they want. This paper presents a novel approach to selective disclosure that combines Merkle hash trees and Boneh-Lynn-Shacham (BLS) signatures. Combining these approaches, we achieve selective disclosure of claims in a single credential and creation of a verifiable presentation containing selectively disclosed claims from multiple credentials signed by different parties. Besides selective disclosure, we enable issuing credentials signed by multiple issuers using this approach.

Digital credentials represent crucial elements of digital identity on the Internet. Credentials should have specific properties that allow them to achieve privacy-preserving capabilities. One of these properties is selective disclosure, which allows users to disclose only the claims or attributes they must. This paper presents a novel approach to selective disclosure BLS-MT-ZKP that combines existing cryptographic primitives: Boneh-Lynn-Shacham (BLS) signatures, Merkle hash trees (MT) and zero-knowledge proof (ZKP) method called Bulletproofs. Combining these methods, we achieve selective disclosure of claims while conforming to selective disclosure requirements. New requirements are defined based on the definition of selective disclosure and privacy spectrum. Besides selective disclosure, specific use cases for equating digital credentials with paper credentials are achieved. The proposed approach was compared to the existing solutions, and its security, threat, performance and limitation analysis was done. For validation, a proof-of-concept was implemented, and the execution time was measured to demonstrate the practicality and efficiency of the approach.

Digital credentials represent crucial elements of digital identity on the Internet. Credentials should have specific properties that allow them to achieve privacy-preserving capabilities. One of these properties is selective disclosure, which allows users to disclose only the claims or attributes they must. This paper presents a novel approach to selective disclosure BLS-MT-ZKP that combines existing cryptographic primitives: Boneh-Lynn-Shacham (BLS) signatures, Merkle hash trees (MT) and zero-knowledge proof (ZKP) method called Bulletproofs. Combining these methods, we achieve selective disclosure of claims while conforming to selective disclosure requirements. New requirements are defined based on the definition of selective disclosure and privacy spectrum. Besides selective disclosure, specific use cases for equating digital credentials with paper credentials are achieved. The proposed approach was compared to the existing solutions, and its security, threat, performance and limitation analysis was done. For validation, a proof-of-concept was implemented, and the execution time was measured to demonstrate the practicality and efficiency of the approach.

Web developers utilize responsive web design principles and frameworks to develop websites that are accessible on various platforms. As consumers often access websites through laptops, tablets, mobile phones, and desktop computers, it is necessary for the website to adjust its appearance according to the device's display frame width. However, the quality assurance process for responsive web pages is typically manual, time-consuming, and error prone. This study introduces ReDeCheck, an open-source automated website layout checking tool developed by Thomas A. Walsh, Gregory M. Kapfhammer, and Phil McMinn. The tool identifies the most common types of responsive design failures by utilizing a set of display frame widths based on the presentation of the website's dynamic layout, also known as the Responsive Layout Graph. This paper verifies the tool's functionality and its underlying concepts.