A Novel Approach to Detect Network Attacks Using G-HMM-Based Temporal Relations Between Internet Protocol Packets

This paper introduces novel attack detection approaches on mobile and wireless device security and network which consider temporal relations between internet packets. In this paper, the authors first present a field selection technique using a Genetic Algorithm and generate a Packet-based Mining Association Rule from an original Mining Association Rule for Support Vector Machine in mobile and wireless network environment. Through the preprocessing with PMAR, SVM inputs can account for time variation between packets in mobile and wireless network. Third, they present Gaussian observation Hidden Markov Model to exploit the hidden relationships between packets based on probabilistic estimation.