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基于物联网的无线传感器网络中Sybil攻击对策的调查。

A survey of Sybil attack countermeasures in IoT-based wireless sensor networks.

作者信息

Arshad Akashah, Mohd Hanapi Zurina, Subramaniam Shamala, Latip Rohaya

机构信息

Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, UPM Serdang, Selangor Darul Ehsan, Malaysia.

出版信息

PeerJ Comput Sci. 2021 Sep 22;7:e673. doi: 10.7717/peerj-cs.673. eCollection 2021.

Abstract

Wireless sensor networks (WSN) have been among the most prevalent wireless innovations over the years exciting new Internet of Things (IoT) applications. IoT based WSN integrated with Internet Protocol IP allows any physical objects with sensors to be connected ubiquitously and send real-time data to the server connected to the Internet gate. Security in WSN remains an ongoing research trend that falls under the IoT paradigm. A WSN node deployed in a hostile environment is likely to open security attacks such as Sybil attack due to its distributed architecture and network contention implemented in the routing protocol. In a Sybil attack, an adversary illegally advertises several false identities or a single identity that may occur at several locations called Sybil nodes. Therefore, in this paper, we give a survey of the most up-to-date assured methods to defend from the Sybil attack. The Sybil attack countermeasures includes encryption, trust, received signal indicator (RSSI), encryption and artificial intelligence. Specifically, we survey different methods, along with their advantages and disadvantages, to mitigate the Sybil attack. We discussed the lesson learned and the future avenues of study and open issues in WSN security analysis.

摘要

多年来,无线传感器网络(WSN)一直是最流行的无线创新技术之一,催生了令人兴奋的新物联网(IoT)应用。基于物联网的WSN与互联网协议IP集成,使任何带有传感器的物理对象都能无处不在地连接,并将实时数据发送到连接到互联网网关的服务器。WSN中的安全问题仍然是物联网范式下一个持续的研究趋势。由于其分布式架构和路由协议中实现的网络争用,部署在敌对环境中的WSN节点可能容易受到诸如女巫攻击等安全攻击。在女巫攻击中,攻击者非法宣传几个虚假身份或一个可能出现在多个位置的单一身份,这些位置称为女巫节点。因此,在本文中,我们对防御女巫攻击的最新可靠方法进行了综述。女巫攻击对策包括加密、信任、接收信号指示器(RSSI)、加密和人工智能。具体来说,我们综述了不同的方法及其优缺点,以减轻女巫攻击。我们讨论了在WSN安全分析中吸取的教训、未来的研究方向和开放问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef98/8507477/2e1cdc81bedd/peerj-cs-07-673-g001.jpg

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