Visible to the public Flooding attack detection and prevention in MANET based on cross layer link quality assessment

TitleFlooding attack detection and prevention in MANET based on cross layer link quality assessment
Publication TypeConference Paper
Year of Publication2017
AuthorsAnsari, A., Waheed, M. A.
Conference Name2017 International Conference on Intelligent Computing and Control Systems (ICICCS)
Keywordsaccurate flooding attack detection, attack detection, compositionality, Computer crime, Cross Layer, Cross layer design, cross layer link quality assessment, cross layer MAC-Network interface, DDoS, DDoS Attack, Distributed Denial of Services attack, Flooding Attack, flooding node detection, link layer assessment based flooding attack detection, MANET, Metrics, mobile ad hoc network, mobile ad hoc networks, Network topology, pubcrawl, resilience, Resiliency, Routing, routing table, telecommunication network routing, telecommunication security, Topology

Mobile Ad hoc Network (MANET) is one of the most popular dynamic topology reconfigurable local wireless network standards. Distributed Denial of Services is one of the most challenging threats in such a network. Flooding attack is one of the forms of DDoS attack whereby certain nodes in the network miss-utilizes the allocated channel by flooding packets with very high packet rate to it's neighbors, causing a fast energy loss to the neighbors and causing other legitimate nodes a denial of routing and transmission services from these nodes. In this work we propose a novel link layer assessment based flooding attack detection and prevention method. MAC layer of the nodes analyzes the signal properties and incorporated into the routing table by a cross layer MAC/Network interface. Once a node is marked as a flooding node, it is blacklisted in the routing table and is communicated to MAC through Network/MAC cross layer interface. Results shows that the proposed technique produces more accurate flooding attack detection in comparison to current state of art statistical analysis based flooding attack detection by network layer.

Citation Keyansari_flooding_2017