Detection and Blockchain-Based Collaborative Mitigation of Internet of Things Botnets

Author:

Sajjad Syed Muhammad1,Mufti Muhammad Rafiq2ORCID,Yousaf Muhammad1ORCID,Aslam Waqar3ORCID,Alshahrani Reem4,Nemri Nadhem5,Afzal Humaira6,Khan Muhammad Asghar7ORCID,Chen Chien-Ming8ORCID

Affiliation:

1. Riphah Institute of Systems Engineering, Riphah International University, Islamabad 45320, Pakistan

2. Department of Computer Science, COMSATS University Islambad, Vehari Campus, 61100, Pakistan

3. Department of Computer Science & Information Technology, The Islamia University of Bahawalpur, 63100, Pakistan

4. Department of Computer Science, College of Computers and Information Technology, Taif University, P.O.Box 11099, Taif 21944, Saudi Arabia

5. Department of Information Systems, College of Science and Arts at Mahayil, King Khalid University, Muhayel Aseer, Saudi Arabia

6. Department of Computer Science, Bahauddin Zakariya University, Multan 60822, Pakistan

7. Hamdard Institute of Engineering & Technology, Islamabad, Pakistan

8. College of Computer Science and Technology, Shandong University of Science and Technology, Shandong, China

Abstract

DDoS (distributed denial of service) attacks have drastically effected the functioning of Internet-based services in recent years. Following the release of the Mirai botnet source code on GitHub, the scope of these exploitations has grown. The attackers have been able to construct and launch variations of the Mirai botnet thanks to the open-sourcing of the Mirai code. These variants make the signature-based detection of these attacks challenging. Moreover, DDoS attacks are typically detected and mitigated reactively, making DDoS mitigation solutions very expensive. This paper presents a proactive IoT botnet detection system that detects the anomalies in the behavior of the IoT device and mitigates the DDoS botnet exploitation at the source end, which makes our proposal a low-cost solution. Further, this paper uses a collaborative trust relationship-based threat intelligence-sharing mechanism to prevent other IoT devices from being compromised by the detected botnet. The researchers have evaluated the collaborative threat intelligence sharing mechanism using Ethereum Virtual Machine and Hyperledger. The performance of our proposed system can detect 97% of the Mirai botnet attack activities. Furthermore, our collaborative threat intelligence sharing mechanism based on the Ethereum Virtual Machine showed more scalability.

Funder

Taif University

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

Reference80 articles.

1. A Lightweight and Robust User Authentication Protocol with User Anonymity for IoT-Based Healthcare

2. Smart Connectivity for Internet of Things (IoT) Applications

3. Internet of Things security (IoT sec) challenges, current status, trends and architecture;R. Pannananda

4. Security analysis of Internet of Things adaptation layer;S. M. Sajjad;Science International,2016

5. Security analysis of IEEE 802.15.4 MAC in the context of Internet of Things (IoT)

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