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A Blockchain-Based Collaborative Intrusion Detection Systems Framework

delete2024-08-01
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PRE
AI
S
Shatha Alharbi *
D
Daniyal Alghazzawi
A
Abeer Hakeem
L
Linda Mohaisen
L
Li Cheng
A
Afraa Attiah
DOI:10.1109/JIOT.2023.3347492delete
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摘要

摘要

En 中文
Nowadays, the Internet of Things (IoT) has become immensely popular in various fields like healthcare, smart cities, and industrial automation. IoT networks are expanding rapidly, including different IoT devices with limited capabilities in terms of power and storage which make the IoT security a crucial issue. IoT Network intrusion detection system (IDS) is one of the most famous solutions that used to identify different types of attack and extract their features (e.g., IP addresses of attackers). The IP address is a valuable feature that can identify malicious traffic of an attacker who attempts to access the IoT network. However, IoT Network IDSs has different limitations: centralization and scalability which easily allow attackers to access the IoT network. Accordingly, this article aims to address these issues by proposing a novel collaborative framework called blockchain-based collaborative IDSs (BC-IDSs) that utilizes Blockchain technology to connect several IDSs. The BC-IDSs framework: 1) creates a list of malicious IP addresses using IDSs; 2) utilizes Blockchain to share and store the Blacklist; and 3) creates a function for duplication check in the Blockchain layer. Further, the implementation of a proof of concept for a BC-IDSs framework is presented by using Ethereum Blockchain simulators. Compared to previous works, this article discusses several types of performance metrics that prove BC-IDSs is able to secure IoT networks. BC-IDSs also increases the scalability by 50% when compared to one of the previous defence works.
Keyword:
Security
IP networks
Collaboration
Artificial intelligence
Telecommunication traffic
Blockchain
cybersecurity
Internet of Things (IoT)
intrusion detection system (IDS)
network security
intrusion detection system (IDS)
network security

期刊

IEEE Internet of Things Journal 封面图
IEEE Internet of Things Journal
IF:
8.9
论文数:
1.4W
被引数:
7.8W

机构

K
King Abdulaziz University
学者数:
2.0W
论文数: 1.9W
被引数: 3.3W
H
hubei university
学者数:
1.1W
论文数: 7.0K
被引数: 7
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