Trust Management Approach for Detection of Malicious Devices in SIoT

Author:

Hankare Priyanka1,Babar Sachin2,Mahalle Parikshit3

Affiliation:

1. AISSMS IOIT, Pune RTO road, Sangamwadi, Pune-411001, India

2. STES, Lonavala Kusgaon (BK) off. Mumbai-Pune Expressway, Lonavala-410401, India

3. SKNCOE, Pune Wadgaon (BK), Pune-411041, India

Abstract

Internet of Things (IoT) is an innovative era of interrelated devices to provide services to other devices or users. In Social Internet of Thing (SIoT), social networking aspect is used for building relationships between devices. For providing or utilizing services, devices need to trust each other in complex and heterogeneous environments. Separating benign and malicious devices in SIoT is a prime security objective. In literature, several works proposed trust computation models based on trust features. But these models fail to identify malicious devices. This paper focuses on detection of malicious devices. In this paper, basic fundamentals, properties, models and attacks of trust in SIoT are discussed. Up-to-date research distributions on trust management and trust attacks are reviewed and idea of Trust Management using Machine Learning Algorithm (TM-MLA) is proposed for identification of malicious devices.

Publisher

University North

Cited by 12 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

1. Trust management in social Internet of Things across domains;Internet of Things;2023-10

2. Trust Analysis to Identify Malicious Nodes in the Social Internet of Things;2023 International Conference on Software, Telecommunications and Computer Networks (SoftCOM);2023-09-21

3. Traffic Characterization to Provide Trust for Internet of Things Devices;2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN);2023-07-04

4. A Dynamic Trust-Related Attack Detection Model for IoT Devices and Services Based on the Deep Long Short-Term Memory Technique;Sensors;2023-04-07

5. Social Internet of Things: Ethical AI Principles in Trust Management;Procedia Computer Science;2023

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