Efficient Game-Theoretic Approach for Malware Detection in Delay-Tolerant Networks

Abstract

Delay Tolerant Networking (DTN) is introduced as an approach in network architecture that is used to address the technical problems in non-homogeneous networks that may reduce continuous network connectivity. Proximity malware is a malware which enters into Networks via Bluetooth, WI-Fi etc. and exploits the opportunistic contacts for propagation. The behavioral characterization of malware is an alternative approach to pattern matching for detecting proximity malware. Since there is a risk associated with a decision in behavioral malware characterization, an extension named Look Ahead is introduced in this work. Furthermore, two extensions are developed such as Adaptive Look ahead and Dogmatic filtering to remove the challenge of evil nodes sharing false evidences. In the proposed research, a Game Theoretic approach for malware detection is introduced. The game theory provides a powerful mathematical tool having huge number of players. The proposed system achieves a high detection rate than previous approaches.