Raspberry Pi Based Intrusion Detection System Using K-Means Clustering Algorithm

Safety has become a growing concern in this rapidly evolving environment of worldwide data sharing, inexpensive Web access and fast-paced technological growth. The protection of all sorts of communications and the storing of data on the Web is one of the fundamental needs of today's environment. The fundamental security features of computer security including the protection of access to information and data integrity Anomaly-based IDS is used to check and record for an unusual behaviour in a packet series and to classify them based on their behavior. The methodology proposed in this paper uses Raspberry Pi to recognize, block, store and classify the address of intruder. The proposed work is devoted to implement an intrusion detection scheme using k-means clustering algorithm technique for an intrusion detection framework focused on a signature. The suggested method utilizes k-means clustering for identifying and classifying type of attacks on the network and blocking the intruder completely in certain cases which is attempting to reach the IP of the host.