Abstrakt

Identification of Malicious Node by Using Mamdani Method in CRN

P.Amala Grace, B.Padminidevi

A cognitive radio Network is an intelligent system that can be configured dynamically. This network automatically detects the available channels in the radio spectrum. According to that it changes the transmission parameters to allow concurrent communication in a given spectrum. But this cognitive network is sensitive to security threats. So, in order to overcome these issues we use intrusion detection system. Actually in the cognitive radio network the idle channels of the primary users are used by the secondary users. The attackers may be external users or secondary users act as a malicious users. To identify the abnormal behavior due to attacks, we propose non-parametric cumulative sum (cusum) as the change point detection algorithm. There are different types of attacks created by the malicious users in the different types of layers. Like other wireless communication systems, a jamming attack is one of the most difficult threats in CRNs. In order to detect the jamming attack, let us consider a simple observation made by a secondary user involving its PDR and SS. Using the non-parametric cusum algorithm suggests that the mean value of the random sequence should be negative during the normal conditions and becomes positive upon a change. This method detects the malicious users but it is not particularly described whether it is a attacker or not. So, we introduce an innovative approach called Fuzzy Decision making system to recognize the attackers exactly. Fuzzy logic is an approach to computing based on "degrees of truth" rather than the usual "true or false" logic on which the modern computer is based. This fuzzy method uses discrete values to distinguish the attackers. Due to the fuzzy decision making we discover accurate attackers.