Perception layer security in Internet of Things

被引:113
|
作者
Khattak, Hasan Ali [1 ]
Shah, Munam Ali [2 ]
Khan, Sangeen [3 ]
Ali, Ihsan [4 ]
Imran, Muhammad [5 ]
机构
[1] COMSATS Univ, Comp Sci, Islamabad, Pakistan
[2] COMSATS Univ, Islamabad, Pakistan
[3] COMSATS Univ, Comp Sci Dept, Islamabad, Pakistan
[4] Univ Malaya, Fac Comp Sci & Informat Technol, Kuala Lumpur, Malaysia
[5] King Saud Univ, Coll Appl Comp Sci, Riyadh, Saudi Arabia
关键词
Perception layer; Internet of Things; Security; Radio frequency identification; Wireless sensor networks; WIRELESS SENSOR NETWORKS; CYBER-PHYSICAL SYSTEMS; RFID-TAGS; AD HOC; IOT; ATTACKS; CHALLENGES; ISSUES; COMMUNICATION; ARCHITECTURE;
D O I
10.1016/j.future.2019.04.038
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Internet of Things (IoT) is one of the rising innovations of the current era that has largely attracted both the industry and the academia. Life without the IoT is entirely indispensable. To dispel the doubts, if any, about the widespread adoption, the IoT certainly necessitates both technically and logically correct solutions to ensure the underlying security and privacy. This paper explicitly investigates the security issues in the perception layer of IoT, the countermeasures and the research challenges faced for large scale deployment of IoT. Perception layer being one of the important layers in IoT is responsible for data collection from things and its successful transmission for further processing. The contribution of this paper is twofold. Firstly, we describe the crucial components of the IoT (i.e., architectures, standards, and protocols) in the context of security at perception layer followed by IoT security requirements. Secondly, after describing the generic IoT-layered security, we focus on two key enabling technologies (i.e., RFID and sensor network) at the perception layer. We categorize and classify various attacks at different layers of both of these technologies through taxonomic classification and discuss possible solutions. Finally, open research issues and challenges relevant to the perception layer are identified and analyzed. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:144 / 164
页数:21
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