Multiple features based approach for automatic fake news detection on social networks using deep learning

Recently, researchers found that the intended generalizability of (deep) face recognition systems increases their vulnerability against attacks. In particular, the attacks based on morphed face images pose a severe security risk to face recognition systems. In the last few years, the topic of (face) image morphing and automated morphing attack detection has sparked the interest of several research laboratories working in the field of biometrics and many different approaches have been published. In this paper, a conceptual categorization and metrics for an evaluation of such methods are presented, followed by a comprehensive survey of relevant publications. In addition, technical considerations and tradeoffs of the surveyed methods are discussed along with open issues and challenges in the field.

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Face Recognition Systems Under Morphing Attacks: A Survey

Secure blockchain enabled Cyber–physical systems in healthcare using deep belief network with ResNet model

The propagation of information over insecure communication system is one of the most important aspect of digitally advance era. The electronic information is travels in form of binary bits. The secrecy of these digital contents is one of the most important issue of existing world. In this article, we have utilized multiple chaotic iterative maps in order to propose a novel image encryption technique. The suggested encryption added confusion as well as diffusion in offered scheme which is one of the most fundamental aspect of encryption technique. We have tested our anticipated scheme against different performances analysis and compared it with already existing results. The designed scheme is capable of providing an excellent privacy to digital images.

A novel chaotic image encryption technique based on multiple discrete dynamical maps

Deep face recognition using imperfect facial data

Despite the large body of work on fingerprint identification systems, most of it focused on using specialized devices. Due to the high price of such devices, some researchers directed their attention to digital cameras as an alternative source for fingerprints images. However, such sources introduce new challenges related to image quality. Specifically, most digital cameras compress captured images before storing them leading to potential losses of information. This study comes to address the need to determine the optimum ratio of the fingerprint image compression to ensure the fingerprint identification system’s high accuracy. This study is conducted using a large in-house dataset of raw images. Therefore, all fingerprint information is stored in order to determine the compression ratio accurately. The results proved that the used software functioned perfectly until a compression ratio of (30–40%) of the raw images; any higher ratio would negatively affect the accuracy of the used system.

Impact of digital fingerprint image quality on the fingerprint recognition accuracy

Quality has become a fundamental requirement for success and sustainability of websites. This study discusses the evaluation of some e-Learning websites as one of the main sources of information to administrators, students and teachers in the educational systems. This article investigates the quality of e-learning websites in the Middle East in term of usability and content accessibility. Eleven websites from eleven countries were selected for this study. Evaluations process is done based on different web diagnostic tools and measures. The experimental results show several issues on usability and content accessibility of the selected e-learning websites. Many usability problems with respect of speed and number of broken links were found. Moreover, the design of the selected websites is not fit with the content accessibility standards.

Fatima Abdalla Al-Alem

Papers

Impact of digital fingerprint image quality on the fingerprint recognition accuracy

Evaluating Usability and Content Accessibility for e-Learning Websites in the Middle East