Markov Decision Process based Model for Performance Analysis an Intrusion Detection System in IoT Networks

• Autorzy: Kalnoor Gauri , Gowrishankar

Identyfikatory

DOI

10.26636/jtit.2021.151221

• Języki publikacji: EN

Abstrakty

EN

In this paper, a new reinforcement learning intrusion detection system is developed for IoT networks incorporated with WSNs. A research is carried out and the proposed model RL-IDS plot is shown, where the detection rate is improved. The outcome shows a decrease in false alarm rates and is compared with the current methodologies. Computational analysis is performed, and then the results are compared with the current methodologies, i.e. distributed denial of service (DDoS) attack. The performance of the network is estimated based on security and other metrics.

Słowa kluczowe

EN

DDoS; intrusion detection; IoT; machine learning; Markov decision process; MDP; Q-learning; NSL-KDD; reinforcement learning

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2021
• Tom: nr 3
• Strony: 42--49
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Kalnoor Gauri

• B.M.S.C.E, Basavangudi, Bangalore, India

• https://orcid.org/0000-0001-9970-4697

autor

Gowrishankar

• B.M.S.C.E, Basavangudi, Bangalore, India

• https://orcid.org/0000-0002-8119-8711

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).