Wormhole Attack Detection System for IoT Network: A Hybrid Approach

Abstract

Many errors in data communication cause security attacks in Internet of Things (IoT). Routing errors which are prominent errors in IoT, degrade the quality of data communication. Many attacks like sinkhole attack, blackhole attack, selective forwarding attack and wormhole attack enter the network through network layer of the IoT. This paper has an emphasis on the wormhole attack detection because it is one of the most uncompromising attacks at the network layer of IoT protocol stack. The wormhole attack inserts wrong routes information in the network; it also alters the network information by causing failure of the location-dependent protocols thus defeating the purpose of routing algorithms. The wormhole attack is activated in the network by forming a tunnel between two long-distance nodes. These nodes create an illusion that they are directly connected and nearer to each other. They attract legitimate nodes to transmit data through them by advertising less hop-count. Most of the time, due to the presence of attack, packets take the long route and reduce their strength. This paper covers the design and implementation of an innovative intrusion detection system for the IoT that detects the wormhole attack and the attacker nodes. The presence of the wormhole attack is identified using location information of any node and its neighbor with the help of Received Signal Strength Indicator (RSSI) values and hop-count. The proposed system is energy efficient and hence it is beneficial for a resource-constrained environment of IoT. It also provides precise true-positive and false-positive detection rate.

Wormhole attack mitigation strategies and their impact on wireless sensor network performance: A literature survey

“…The wormholes are addressed, and the source node uses the particle swarm optimization (PSO) method to find an optimal path among the safe paths. 52 In Bhosale and Sonavane, 55 the wormhole is detected baed on the location of any node along with its neighbor information which can be obtained by using the received signal strength indicator (RSSI) and hop count. The ESWI algorithm detects suspicious nodes using transmission-time information.…”

“…In Bhosale and Sonavane, 55 the wormhole is detected baed on the location of any node along with its neighbor information which can be obtained by using the received signal strength indicator (RSSI) and hop count. The ESWI algorithm detects suspicious nodes using transmission‐time information.…”