Signature-Based Method and Stream Data Mining Technique Performance Evaluation for Security and Intrusion Detection in Advanced Metering Infrastructures (AMI)

Abstract

Advanced Metering Infrastructure is a system for collecting, measuring and analyzing power energy use which beside the mentioned parameters is responsible to transmit this information between elements of this network. One of the problems of processing in these networks and the most main installation duct is security in the network. Beside the precautionary operations used for achieving security in AMI, today the usage of intrusion detection systems (IDS) is paid attention as a second blocker defense against network security attacks. According to variations of Intrusion Detection techniques in network, many different designs for applying IDS and AMI have been suggested so far. In this paper we aim to evaluate the newest techniques of operation in abnormality-based IDS in Intrusion Detection and security achievement in AMI against signature-based IDS operation with the use of standard criteria in equal situations experimentally. According to the results from this research we can see that the signature-based methods are not useful in IDS systems applied in AMI network. The measurement on anomaly-based IDS which is using data mining techniques showed very hopeful results. However these methods need some improvements in order to achieve their best place.