TY - JOUR
T1 - Markov decision process based model for performance analysis an intrusion detection system in IoT networks
AU - Kalnoor, Gauri
AU - Gowrishankar, S.
N1 - Publisher Copyright:
© 2021 National Institute of Telecommunications. All rights reserved.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85117476285
UR - https://www.scopus.com/inward/citedby.url?scp=85117476285&partnerID=8YFLogxK
U2 - 10.26636/JTIT.2021.151221
DO - 10.26636/JTIT.2021.151221
M3 - Article
AN - SCOPUS:85117476285
SN - 1509-4553
VL - 2021
SP - 42
EP - 49
JO - Journal of Telecommunications and Information Technology
JF - Journal of Telecommunications and Information Technology
IS - 3
ER -