| Title | Decision Tree based AIS strategy for Intrusion Detection in MANET |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Jim, Lincy Elizebeth, Chacko, Jim |
| Conference Name | TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON) |
| Keywords | AIS strategy, artificial immune system, artificial immune system strategy, artificial immune systems, artificial intelligence, Batteries, battlefield communications, Cheat Node, cheat nodes, compositionality, critical scenarios, Decision Tree, Decision trees, fixed infrastructure, Immune system, Intrusion Detection strategy, intrusion detection system, MANET, MANET security, Metrics, mobile ad hoc networks, multihop communication, natural disaster, network communications, Pathogens, pubcrawl, reduced packet delivery ratio, Resiliency, Routing, Routing protocols, security measures, security of data, security strategies, telecommunication security, wired networks, wireless networks |
| Abstract | Mobile Ad hoc Networks (MANETs) are wireless networks that are void of fixed infrastructure as the communication between nodes are dependent on the liaison of each node in the network. The efficacy of MANET in critical scenarios like battlefield communications, natural disaster require new security strategies and policies to guarantee the integrity of nodes in the network. Due to the inherent frailty of MANETs, new security measures need to be developed to defend them. Intrusion Detection strategy used in wired networks are unbefitting for wireless networks due to reasons not limited to resource constraints of participating nodes and nature of communication. Nodes in MANET utilize multi hop communication to forward packets and this result in consumption of resources like battery and memory. The intruder or cheat nodes decide to cooperate or non-cooperate with other nodes. The cheat nodes reduce the overall effectiveness of network communications such as reduced packet delivery ratio and sometimes increase the congestion of the network by forwarding the packet to wrong destination and causing packets to take more times to reach the appropriate final destination. In this paper a decision tree based artificial immune system (AIS) strategy is utilized to detect such cheat nodes thereby improving the efficiency of packet delivery. |
| DOI | 10.1109/TENCON.2019.8929362 |
| Citation Key | jim_decision_2019 |
Decision Tree based AIS strategy for Intrusion Detection in MANET