Sahil Garg

TL;DR: An SDN-based edge-cloud interplay is presented to handle streaming big data in IIoT environment, wherein SDN provides an efficient middleware support and a multi-objective evolutionary algorithm using Tchebycheff decomposition for flow scheduling and routing in SDN is presented.

TL;DR: This article developed a decentralized paradigm for big data-driven cognitive computing (D2C), using federated learning and blockchain jointly, which can solve the problem of “data island” with privacy protection and efficient processing while blockchain provides incentive mechanism, fully decentralized fashion, and robust against poisoning attacks.

TL;DR: A hybrid deep-learning-based anomaly detection scheme for suspicious flow detection in the context of social multimedia is proposed to enhance the reliability of the software-defined networks (SDN).

TL;DR: The results obtained demonstrate that the proposed cloud-based anomaly detection model is superior in comparison to the other state-of-the-art models (used for network anomaly detection), in terms of accuracy, detection rate, false positive rate, and F-score.

TL;DR: A Peer-to-Peer (P2P) computing resource trading system to balance computing resource spatio-temporal dynamic demands in IoV-assisted smart city and security analysis shows the security performance of the system and numerical simulations show that the strategies can encourage the collaboration between the buyer and smart vehicles.