• Dr.V.Lakshman Narayana
• Dr.P.Radhika
• Mohammad Suhana
• D.Vyshnavi
• K.Sirisha , M.Manasa

Due to its deployment in many remote and heterogeneous locations, where small sensor nodes transmit sensitive data on a short timescale, wireless sensor networks (WSNs) present serious security challenges. Battlegrounds, industry, and smart cities are among the areas where IoT-enabled WSNs find use. However, the automatic information flow and networked devices that come with their integration provide new security vulnerabilities. Deploying safe Internet of Things applications requires an understanding of wireless sensor weaknesses. The use of machine learning algorithms which achieve high accuracy in recognizing cyber attacks across various datasets, is highlighted in research on the creation of intrusion detection systems (IDS).To improve detection performance, these models make use of feature reduction methods including SVD, PCA, and K-means clustering. Large-scale deployment of WSNs integrated into IoT ecosystems still depends heavily on security, and current research is concentrated on improving network resilience against malicious actions and minimizing emerging threats. To efficiently identify the intrusions in the network, this research proposes a Multistage Node Pattern Analysis Model for Cyber Attack Detection (MNPAM-CAD) in the WSN. The proposed model when compared with the traditional models performs better in cyber attack detection in WSN.

Wireless Sensor Networks (WSNs), Cyber Attacks, Pattern Analysis, Data Loss, Intrusion detection, malicious activities.

"Cyber Attack Detection with Pattern Analysis in IoT enabled Wireless Sensor Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 10, page no.131-141, October-2024, Available :http://www.jetir.org/papers/JETIRGN06016.pdf

"Cyber Attack Detection with Pattern Analysis in IoT enabled Wireless Sensor Networks", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 10, page no. pp131-141, October-2024, Available at : http://www.jetir.org/papers/JETIRGN06016.pdf