Abstract

Data security is a huge responsibility for sensor network as there are various ways in which security can be breached, enabling hackers to access sensitive data. Threats to wireless sensor networks are numerous and potentially devastating. Security issues ranging from session hijacking to Denial of Service (DOS) can plague a WSN. To aid in the defense and detection of these potential threats, WSN employ a security solution that includes an intrusion detection system (IDS). Different neural methods have been proposed in recent years for the development of intrusion detection system. In this paper, we surveyed denial of service attacks that disseminate the WSN such a way that it temporarily paralyses a network and proposed a hybrid Intrusion Detection approach based on stream flow and session state transition analysis that monitor and analyze stream flow of data, identify abnormal network activity, detect policy violations against sync flood attack.

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