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Cracking the Anonymous IoT Routing Networks: A Deep Learning Approach

  • Gaurang Bansal
  • , Vinay Chamola
  • , Amir Hussain
  • , Muhammad Khurram Khan

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

In recent years, IoT technology has been one of the most rapidly expanding fields, connecting over 27 billion connected devices worldwide. Increasing security concerns, such as software flaws and cyberattacks, limit the use of IoT devices. Tor, also known as 'The Onion Router,' is one of the most popular, secure, and widely deployed anonymous routing systems in IoT networks. Tor is based on a worldwide network of relays operated by volunteers worldwide. Tor continues to be one of the most popular and secure tools against network surveillance, traffic analysis, and information censorship due to its robust use of encryption, authentication, and routing protocols. However, ToR is not anticipated to be entirely safe. The increasing computational capabilities of adversaries threaten Tor's ability to withstand adversarial attacks and maintain anonymity. This article describes the foundation of the Tor network, how it operates, potential attacks against Tor, and the network's defense strategies. In addition, the authors present a framework for deep learning that uses bandwidth performance to identify the server's location in Tor, thereby compromising anonymity. This article examines Tor's network's current and projected future in the Internet of Things.

Original languageEnglish
Pages (from-to)120-126
Number of pages7
JournalIEEE Internet of Things Magazine
Volume6
Issue number1
DOIs
StatePublished - 1 Mar 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems

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