Skip to main navigation Skip to search Skip to main content

Building an Intelligent Global IoT Reputation and Malicious Devices Detecting System

  • Jordan University of Science and Technology
  • Duquesne University

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The Internet of Things (IoT) applications are growing immensely. However, malicious IoT devices are major concerns that threaten the security of IoT applications. This paper proposes an intelligent reputation system for IoT devices using edge computing and cloud computing infrastructures. The proposed system can be used to mitigate the effect of malicious and malfunction IoT devices. Therefore, the proposed system can be used to enhance the effectiveness of IoT based systems such as smart cities, and reduce the risk of malicious IoT devices especially in sensitive systems, such as military applications, that leverage IoT devices. To achieve this goal, the paper proposes a new identification method for uniquely and globally identifying IoT devices wherever they move. Moreover, the paper proposes a new approach for computing the reputation of IoT devices, and calculating correct values based on these reputations. The results show that the proposed approach achieves very good results in detecting malicious IoT devices and computing very close values to the true values.

Original languageEnglish
Article number45
JournalJournal of Network and Systems Management
Volume29
Issue number4
DOIs
StatePublished - Oct 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Edge computing
  • Information security
  • Intelligent systems
  • Internet of Things
  • Reputation systems
  • Trust systems

Fingerprint

Dive into the research topics of 'Building an Intelligent Global IoT Reputation and Malicious Devices Detecting System'. Together they form a unique fingerprint.

Cite this