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A Novel IDS with a Dynamic Access Control Algorithm to Detect and Defend Intrusion at IoT Nodes.
Alazab, Moutaz; Awajan, Albara; Alazzam, Hadeel; Wedyan, Mohammad; Alshawi, Bandar; Alturki, Ryan.
Afiliação
  • Alazab M; Department of Intelligent Systems, Faculty of Artificial Intelligence, Al-Balqa Applied University, Al-Salt 19385, Jordan.
  • Awajan A; Cybersecurity Department, School of Computing and Data Sciences, Oryx Universal College with Liverpool John Moores University, Doha 34110, Qatar.
  • Alazzam H; Department of Intelligent Systems, Faculty of Artificial Intelligence, Al-Balqa Applied University, Al-Salt 19385, Jordan.
  • Wedyan M; Department of Intelligent Systems, Faculty of Artificial Intelligence, Al-Balqa Applied University, Al-Salt 19385, Jordan.
  • Alshawi B; Department of Computer Sciences, Faculty of Information Technology and Computer Sciences, Yarmouk University (YU), Irbid 21163, Jordan.
  • Alturki R; Department of Computer and Network Engineering, College of Computing, Umm Al-Qura University, Makkah 24382, Saudi Arabia.
Sensors (Basel) ; 24(7)2024 Mar 29.
Article em En | MEDLINE | ID: mdl-38610399
ABSTRACT
The Internet of Things (IoT) is the underlying technology that has enabled connecting daily apparatus to the Internet and enjoying the facilities of smart services. IoT marketing is experiencing an impressive 16.7% growth rate and is a nearly USD 300.3 billion market. These eye-catching figures have made it an attractive playground for cybercriminals. IoT devices are built using resource-constrained architecture to offer compact sizes and competitive prices. As a result, integrating sophisticated cybersecurity features is beyond the scope of the computational capabilities of IoT. All of these have contributed to a surge in IoT intrusion. This paper presents an LSTM-based Intrusion Detection System (IDS) with a Dynamic Access Control (DAC) algorithm that not only detects but also defends against intrusion. This novel approach has achieved an impressive 97.16% validation accuracy. Unlike most of the IDSs, the model of the proposed IDS has been selected and optimized through mathematical analysis. Additionally, it boasts the ability to identify a wider range of threats (14 to be exact) compared to other IDS solutions, translating to enhanced security. Furthermore, it has been fine-tuned to strike a balance between accurately flagging threats and minimizing false alarms. Its impressive performance metrics (precision, recall, and F1 score all hovering around 97%) showcase the potential of this innovative IDS to elevate IoT security. The proposed IDS boasts an impressive detection rate, exceeding 98%. This high accuracy instills confidence in its reliability. Furthermore, its lightning-fast response time, averaging under 1.2 s, positions it among the fastest intrusion detection systems available.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Jordânia

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Jordânia