A Recent Survey on Intrusion Detection Methods for Wireless Networks

Wireless networks have become an integral part of modern society allowing the use of several applications which are essential to society. However, their open nature leaves them vulnerable to a variety of security risks such as denial of service, unauthorized access, wormhole attack, etc. In recent years, the complexity and the number of attacks has increased which demands more robust and dynamic intrusion detection systems. This paper presents an in-depth review of existing techniques based on various parameters like time, location, traffic analysis, machine learning etc., and discusses their advantages and disadvantages. The comparative analysis suggests that machine learning based detection techniques are more precise and accurate. Further, the paper also focuses on the challenges and opportunities associated in these areas for future research work.