Malicious Activity Detection using Smart Contracts in IoT

Mwangi Eric, Hany Atlam, Nawfal Fadhel

Abstract

Internet of Things (IoT) is a unique element in the realm of Cybersecurity. It constitutes countless applications, including defense, health, agriculture, finance, amongst other industries. The majority of existing studies focus on various developments of IoT products and services essential to our day-to-day activities, with little emphasis on the security of developed systems. This has led to the proliferation of IoT solutions acquired through rapid development and overlooking the need for a structured security framework during the systems’ development stages. IoT security capability can be improved by using complementary technologies. This paper explores applying Risk-Based Access Control Model using Blockchain to control access to IoT devices. Although current access control models provide efficient security measures to control who can access the system resources, there is no way to detect and prevent malicious attacks after granting access. The proposed solution utilizes smart contracts under the Hyperledger Fabric (HLF) Blockchain Framework to create access permissions and measure the security risks associated with any event in the IoT system and create access permissions to determine what processes may be performed. This will allow the detection of any malicious activity at the early stages of the attack and grant or deny access based on the risk associated with any activity.

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Paper Citation


in Harvard Style

Eric M., Atlam H. and Fadhel N. (2021). Malicious Activity Detection using Smart Contracts in IoT. In Proceedings of the 6th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-504-3, pages 286-295. DOI: 10.5220/0010474802860295


in Bibtex Style

@conference{iotbds21,
author={Mwangi Eric and Hany Atlam and Nawfal Fadhel},
title={Malicious Activity Detection using Smart Contracts in IoT},
booktitle={Proceedings of the 6th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2021},
pages={286-295},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010474802860295},
isbn={978-989-758-504-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 6th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - Malicious Activity Detection using Smart Contracts in IoT
SN - 978-989-758-504-3
AU - Eric M.
AU - Atlam H.
AU - Fadhel N.
PY - 2021
SP - 286
EP - 295
DO - 10.5220/0010474802860295