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JOURNALS // Informatics and Automation // Archive

Informatics and Automation, 2024 Issue 23, volume 5, Pages 1423–1453 (Mi trspy1329)

Artificial Intelligence, Knowledge and Data Engineering

Rivest-Shamir-Adleman algorithm optimized to protect iot devices from specific attacks

R. Jenifer, V. J. Prakash

Cauvery College for Women (Autonomous), Affiliated to Bharathidasan University

Abstract: IoT devices are crucial in this modern world in many ways, as they provide support for environmental sensing, automation, and responsible resource conservation. The immense presence of IoT devices in everyday life is inevitable in the smart world. The predominant usage of IoT devices lurks the prying eyes of intentional hackers. Though there are several precautionary security systems and protocols available for generic wireless networks, it is observed that there is a need to formulate a state-of-the-art security mechanism exclusively for IoT network environments. This work is submitted here for the betterment of IoT network security. Three dedicated contributions are integrated in this work to achieve higher security scores in IoT network environments. Fast Fuzzy Anomaly Detector, Legacy Naïve Bayes Attack Classifiers, and Variable Security Schemer of Rivest-Shamir-Adleman algorithm are the novel modules introduced in this work abbreviated as ASORI. Captivating the advantages of the onboard IoT certification mechanism and selecting a dynamic security strategy are the novelties introduced in this work. ASORI model is tested with industrial standard network simulator OPNET to ensure the improved security along with vital network performance parameter betterments.

Keywords: Internet-of-Things (IoT), network security, fuzzy anomaly detection, Naïve Bayes classification, RSA.

UDC: 004

Received: 30.01.2024

Language: English

DOI: 10.15622/ia.23.5.6



© Steklov Math. Inst. of RAS, 2024