Integrated Combined Layer Algorithm (ICLA) for Jamming Detection in MANET

Abstract

The nature of MANETs such as open medium, dynamic mobility and lack of security makes it susceptible to a range of attacks. Jamming attacks is recorded as the highest occurring attacks that exist at physical and MAC layers in MANET. Therefore, an integrated combined layer algorithm (ICLA) is proposed using reverse engineering and anomaly detection technique. The methodology begins by collecting data through OPNET. Analysis and evaluation of the data produces three jammers detection Metrics which are used detect jammers. The performance of the outcome are then tested against other jammers’ model at MAC and physical layer to evaluate the detection performance. This enables identification of jamming attack at both lower layers in MANET. It is combination of three tested metrics such as SNR, BER and throughput that able to detect jamming attack using combined layer approach. The combination of these three metrics across layers shows improvement in identification performance.