Threshold-Based Method for Detection of Distributed Denial of Service Attack in IoT

Abstract

The internet of things is the decentralized type of network in which sensor devices can join or leave the network when they want. Due to such nature of the network malicious nodes enter the network which affects network performance in terms of certain parameters. This research work is based on the detection and isolation of distributed denial of service attack in internet of things. The distributed denial of service attack is the denial of service type attack which affects network performance to large extent. In the existing techniques there are two main drawbacks. The first drawback is that the technique does not pin point malicious nodes from the network. The second drawback is that the malicious node detection time is very high. In this research, the new technique will be proposed for the isolation of malicious nodes from the network. In this technique, similarity of the traffic is analyzed using the cosine similarity. The sensor node which is generated dissimilar type of traffic is detected as malicious nodes. The proposed technique has been implemented in MATLAB and results have been analyzed in terms of certain parameters. It is expected that proposed technique detect malicious nodes in least amount of time.