A Novel QoS-Oriented Intrusion Detection Mechanism for IoT Applications

Author:

Noorwali Abdulfattah1ORCID,Alvi Ahmad Naseem2ORCID,Khan Mohammad Zubair3ORCID,Javed Muhammad Awais2ORCID,Boulila Wadii4ORCID,Pattanaik Priyadarshini A.5

Affiliation:

1. Department of Electrical Engineering, Umm Al-Qura University, Makkah 21961, Saudi Arabia

2. Department of Electrical and Computer Engineering, COMSATS University Islamabad, 45550, Pakistan

3. Department of Computer Science, College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia

4. RIADI Laboratory, National School of Computer Science, University of Manouba, Tunisia

5. Image and Information Processing Department, IMT Atlantique, LaTIM Inserm U1101, Brest 29238, France

Abstract

Wireless sensor network (WSN) is an integral part of Internet of Things (IoT). The sensor nodes in WSN generate large sensing data which is disseminated to intelligent servers using multiple wireless networks. This large data is prone to attacks from malicious nodes which become part of the network, and it is difficult to find these adversaries. The work in this paper presents a mechanism to detect adversaries for the IEEE 802.15.4 standard which is a central medium access protocol used in WSN-based IoT applications. The collisions and exhaustion attacks are detected based on a soft decision-based algorithm. In case the QoS of the network is compromised due to large data traffic, the proposed protocol adaptively varies the duty cycle of the IEEE 802.15.4. Simulation results show that the proposed intrusion detection and adaptive duty cycle algorithm improves the energy efficiency of a WSN with a reduced network delay.

Funder

Umm Al-Qura University

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3