Designing Efficient Sinkhole Attack Detection Mechanism in Edge-Based IoT Deployment

Sumit Pundir; Mohammad Wazid; Devesh Pratap Singh; Ashok Kumar Das; Joel J P C Rodrigues; Youngho Park

doi:10.3390/s20051300

Designing Efficient Sinkhole Attack Detection Mechanism in Edge-Based IoT Deployment

Sensors (Basel). 2020 Feb 27;20(5):1300. doi: 10.3390/s20051300.

Authors

Sumit Pundir¹, Mohammad Wazid¹, Devesh Pratap Singh¹, Ashok Kumar Das², Joel J P C Rodrigues^{3

4}, Youngho Park⁵

Affiliations

¹ Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun 248 002, India.
² Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad 500 032, India.
³ Federal University of Piauí (UFPI), 64049-550 Teresina-Pi, Brazil.
⁴ Instituto de Telecomunicações, 1049-001 Lisbon, Portugal.
⁵ School of Electronics Engineering, Kyungpook National University, Daegu 41566, Korea.

Abstract

The sinkhole attack in an edge-based Internet of Things (IoT) environment (EIoT) can devastate and ruin the whole functioning of the communication. The sinkhole attacker nodes ( S H A s) have some properties (for example, they first attract the other normal nodes for the shortest path to the destination and when normal nodes initiate the process of sending their packets through that path (i.e., via S H A ), the attacker nodes start disrupting the traffic flow of the network). In the presence of S H A s, the destination (for example, sink node i.e., gateway/base station) does not receive the required information or it may receive partial or modified information. This results in reduction of the network performance and degradation in efficiency and reliability of the communication. In the presence of such an attack, the throughput decreases, end-to-end delay increases and packet delivery ratio decreases. Moreover, it may harm other network performance parameters. Hence, it becomes extremely essential to provide an effective and competent scheme to mitigate this attack in EIoT. In this paper, an intrusion detection scheme to protect EIoT environment against sinkhole attack is proposed, which is named as SAD-EIoT. In SAD-EIoT, the resource rich edge nodes (edge servers) perform the detection of different types of sinkhole attacker nodes with the help of exchanging messages. The practical demonstration of SAD-EIoT is also provided using the well known NS2 simulator to compute the various performance parameters. Additionally, the security analysis of SAD-EIoT is conducted to prove its resiliency against various types of S H A s. SAD-EIoT achieves around 95 . 83 % detection rate and 1 . 03 % false positive rate, which are considerably better than other related existing schemes. Apart from those, SAD-EIoT is proficient with respect to computation and communication costs. Eventually, SAD-EIoT will be a suitable match for those applications which can be used in critical and sensitive operations (for example, surveillance, security and monitoring systems).

Keywords: NS2 simulation; edge computing; internet of things (IoT); intrusion detection; security; sinkhole attack.