Fortifying IoT against crimpling cyber-attacks: a systematic review

Usman Tariq, Irfan Ahmed, Muhammad Attique Khan, Ali Kashif Bashir

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

The rapid growth and increasing demand for Internet of Things (IoT) devices in our everyday lives create exciting opportunities for human involvement, data integration, and seamless automation. This fully interconnected ecosystem considerably impacts crucial aspects of our lives, such as transportation, healthcare, energy management, and urban infrastructure. However, alongside the immense benefits, the widespread adoption of IoT also brings a complex web of security threats that can influence society, policy, and infrastructure conditions. IoT devices are particularly vulnerable to security violations, and industrial routines face potentially damaging vulnerabilities. To ensure a trustworthy and robust security framework, it is crucial to tackle the diverse challenges involved. This survey paper aims to aid researchers by categorizing attacks and vulnerabilities based on their targets. It provides a detailed analysis of attack methods and proposes effective countermeasures for each attack category. The paper also highlights case studies of critical IoT applications, showcasing security solutions. In addition to traditional cryptographic approaches, this work explores emerging technologies like Quantum Crypto Physical Unclonable Functions (QC-PUFs) and blockchain, discussing their pros and cons in securing IoT environments. The research identifies and examines attacks, vulnerabilities, and security measures and endeavors to impact the overall understanding of IoT security. The insights and findings presented here will serve as a valuable resource for researchers, guiding the development of resilient security mechanisms to ensure the trustworthy and safe operation of IoT ecosystems.

Original languageEnglish
Pages (from-to)665-686
Number of pages22
JournalKarbala International Journal of Modern Science
Volume9
Issue number4
DOIs
StatePublished - 2023

Keywords

  • Anomaly Detection
  • Blockchain
  • Cyber Security
  • Internet of Things
  • Machine Learning (ML)
  • Systematic Literature Review

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