• Prachi Chaudhary
• MS Upasana

This research paper examines the integration of Software-Defined Network (SDN) architecture into Wireless Sensor Networks (WSNs) to enhance security in sensitive environments. Specifically, the focus is on establishing a Software-Defined Wireless Sensor Network (SDWSN). The paper analyzes three Artificial Intelligence (AI) approaches, namely decision tree, naïve Bayes, and deep artificial neural network, as intrusion detection systems (IDSs) in SDWSNs. The findings reveal that the decision tree approach outperforms the others and is the most suitable for implementing IDSs in conventional SDWSNs due to its superior performance. The paper highlights the significance of AI in securing SDWSNs and provides valuable insights for researchers and practitioners in the field of network security. Keywords: AI, intrusion detection, SDWSN, security, WSN.

"Comparison of AI Intrusion Detection System For Software Defined Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 8, page no.f200-f212, August-2023, Available :http://www.jetir.org/papers/JETIR2308522.pdf

"Comparison of AI Intrusion Detection System For Software Defined Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 8, page no. ppf200-f212, August-2023, Available at : http://www.jetir.org/papers/JETIR2308522.pdf