Omar Abdel Wahab

TL;DR: This survey provides a comprehensive tutorial on federated learning and its associated concepts, technologies and learning approaches, and designs a three-level classification scheme that first categorizes the Federated learning literature based on the high-level challenge that they tackle, and classify each high- level challenge into a set of specific low-level challenges to foster a better understanding of the topic.

TL;DR: Performance analysis and simulation results show that the proposed model can maintain the network stability, reduce the end-to-end delay, increase the packet delivery ratio, and reduce the communications overhead.

TL;DR: This paper discusses the challenging problem of having active malicious Web services in the composite and community-based architectures and can be used by the future researchers as a roadmap to explore new trust and reputation models for Web services taking into account the shortcomings of the existing models.

TL;DR: A multi-decision intelligent detection model called CEAP is proposed that complies with the highly mobile nature of VANET with increased detection rate and minimal overhead, and is able to increase the accuracy of detections, enhance the attack detection rate, decrease the false positive rate, and improve the packet delivery ratio in the presence of high mobility.

TL;DR: A three-fold solution that includes: trust establishment framework that is resilient to collusion attacks that occur to mislead trust results; bootstrapping mechanism that capitalizes on the endorsement concept in online social networks to assign initial trust values; and trust-based hedonic coalitional game that enables services to distributively form trustworthy multi-cloud communities is proposed.