The recent surge in adoption of the Internet of Things (IoT) has accelerated integration and Internet access beyond smart devices, which in turn has made the Internet more and more pervasive in our daily lives and IoT devices open up endless new possibilities and simplify lives. Unfortunately, the current system able to spy on users of unprotected IoT systems. Thus, the predictive models taught by machine learning algorithms is demanded and have great potential to alleviate some of these problems as the looming crisis deepens. In this work, a lightweight encryption technique (SIT) to secure an IoT is proposed. It is a 64-bit block cypher that encrypts data with a 64-bit key. The proposed algorithm's architecture is a hybrid type and delivers significant security in just five encryption cycles in simulations. The technique is implemented in hardware on a low-cost 8-bit microcontroller. The impact of an intense attack and buffer size are discussed in this work to analyze the Distributed Denial-of-Service (DDoS) attacks on a server. Finally, the proposed mitigation approached shows a better performance according to the energy consumption level during the attacks and the mitigation applied. Thus, the DDoS attacks successfully being reduced.
Analysis of Security Threats on Data Centre in Internet of Things
Advances in Engineering res
Proceedings of the Multimedia University Engineering ; 2022 ; Cyberjaya and Melaka, Malaysia July 25, 2022 - July 27, 2022
Proceedings of the Multimedia University Engineering Conference (MECON 2022) ; Kapitel : 33 ; 377-389
23.12.2022
13 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Security Security threats increase demand for protection
British Library Online Contents | 2004