A Review on the Security of IoT Networks: From Network Layer's Perspective

被引:26
作者
Jahangeer, Asma [1 ]
Bazai, Sibghat Ullah [1 ]
Aslam, Saad [2 ]
Marjan, Shah [3 ]
Anas, Muhammad [1 ]
Hashemi, Sayed Habibullah [4 ]
机构
[1] Balochistan Univ Informat Technol Engn & Managemen, Dept Comp Sci, Quetta, Pakistan
[2] Sunway Univ, Sch Engn & Technol, Dept Comp & Informat Syst, Subang Jaya, Selangor, Malaysia
[3] Balochistan Univ Informat Technol, Dept Software Engn Engn & Management Sci, Quetta, Pakistan
[4] Paktia Univ, Dept Phys, Gardez, Paktia, Afghanistan
关键词
IoT; machine learning; network layer; RPL; sinkhole attack; INTRUSION DETECTION SYSTEM; SYBIL ATTACK; ROUTING PROTOCOL; RPL; INTERNET; CHALLENGES; PREVENTION;
D O I
10.1109/ACCESS.2023.3246180
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Internet of Things (IoT) has revolutionized the world in the last decade. Today millions of devices are connected to each other utilizing IoT technology in one way or the other. With the significant growth in IoT devices, the provision of IoT security is imperative. Routing protocol for low power and lossy networks (RPL) is a network layer protocol, specially designed for routing in IoT devices. RPL protocol faces many attacks such as selective forwarding attacks, blackhole attacks, sybil attacks, wormhole attacks, and sinkhole attacks. All these attacks pose great threats to IoT networks and can substantially affect the performance of the network. In this work, a comprehensive review of internal attacks on the network layer is presented. Specifically, we focus on the literature that considers presenting solutions for the detection and prevention of sinkhole attacks. We reviewed the state-of-the-art works and different performance parameters like energy consumption, scalability, threshold value, packet delivery ratio, and throughput. Moreover, we also present a detailed analysis of machine learning-based algorithms and techniques proposed for the security of RPL protocol against internal attacks.
引用
收藏
页码:71073 / 71087
页数:15
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