A Distance Vector Hop and Differential Evolution based Interception Strategy for detecting Cross Border Infiltration in Underground Tunnel

Abstract

Securing the external border of a nation through potential surveillance is considered to be highly essential for safeguarding them from terrorists and other national armies that intentionally try to conquer regions. The infiltration of trespassers and terrorists into a territory is considered to greatly influence the harmony and peace of a nation. In this context, conventional border surveillance systems safeguard the border regions based on the pre-determined routes at various time intervals. However, the intensive involvement of human in patrolling is determined as the major challenge in the process of safeguarding longer border areas. Moreover, detecting the infiltration of terrorists through the underground tunnel is considered to be the other challenge. At this juncture, wireless sensor networks are considered to be the best suitable candidate for safeguarding the external borders through real-time monitoring to attain maximized accuracy, efficiency in the detection and least human intervention. In this paper, Distance Vector-Hop (DV-Hop) and Differential Evolution (DE)-based Interception Strategy (DV-Hop-DE-IS) is proposed for accurate detection of cross border infiltration in the underground tunnel. This proposed DV-Hop-DE-IS includes the merits of converting the discrete values of hop count into a highly accurate continuous value depending on the information received from the number of shared one-hop nodes that exists between neighbouring nodes. This problem of intruder detection is formulated as the minimum optimization problem that could be optimally solved through the utilization of the Differential Evolution algorithm with maximized efficiency. The simulation results of the DV-Hop-DE-IS confirmed better detection rate, accuracy with a reduced false positive rate compared to the benchmarked intruder detection approaches.