A novel framework for jamming detection and classification in wireless networks

Launching jamming attacks is trivial but detecting and classifying attacks are more difficult especially in Wireless Networks. This is due to the open nature of this medium that leaves it vulnerable to multiple security threats. Anyone with a transceiver can launch jamming based DoS attacks on wireless transmissions, inject spurious messages, or jam legitimate ones. Jamming attacks usually occur at physical and MAC layers and involves different methods, techniques and technology. Therefore designing an efficient Intrusion Detection System (IDS) is a challenging task. The objective of this paper is to propose a new IDS framework that enables detection and classification of jamming in physical and MAC layers in wireless networks. To address this, problems that arise due to jamming at both layers are identified and investigated. Lists of parameters and variables are associated with jamming are identified and formulated to detect and classify attacks. Finally a novel IDS framework for detecting and classifying jamming attacks is proposed. This framework is found to be able to detect and classify jamming faster and more efficient.