Optimizing Intrusion Detection in WSNs: A Data-Driven Analysis of Signature-Based Intrusion Detection System

In this era, due to the increased demand for data, Wireless Sensor Networks (WSNs) are used in many applications like healthcare, industrialization, manufacturing, education etc. Due to its complex design, high power and bandwidth are required for data processing. Thus, it has many security threats and vulnerabilities which lead to the exploitation of resources. However, signature based intrusion detection systems (IDS) provide an effective countermeasures against the threats known. The main objective of the current study is to conduct a critical comparison of signature-based IDS for WSN. A comparative analysis has been performed at how different parameters affect resource usage, false alarm rate, and detection rate. Meta-analysis of data-driven methodologies from earlier studies has also been done and the analysis suggests improvement in effectiveness of IDS for WSN. It also investigates the benefits and drawbacks of IDS for WSN that depends on signatures based approaches.