ETRI Journal

  • 제44권1호
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  • Pages.155-167
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  • 2022
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  • 1225-6463(pISSN)
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  • 2233-7326(eISSN)
한국전자통신연구원 (Electronics and Telecommunications Research Institute)
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A new method to detect attacks on the Internet of Things (IoT) using adaptive learning based on cellular learning automata

  • Dogani, Javad (Department of Electrical and Computer Engineering, University of Hormozgan) ;
  • Farahmand, Mahdieh (Department of Mechanics, Electrical and Computer, Islamic Azad University Science and Research Branch) ;
  • Daryanavard, Hassan (Department of Electrical and Computer Engineering, University of Hormozgan)
  • 투고 : 2021.02.06
  • 심사 : 2021.08.23
  • 발행 : 2022.02.01
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초록

The Internet of Things (IoT) is a new paradigm that connects physical and virtual objects from various domains such as home automation, industrial processes, human health, and monitoring. IoT sensors receive information from their environment and forward it to their neighboring nodes. However, the large amounts of exchanged data are vulnerable to attacks that reduce the network performance. Most of the previous security methods for IoT have neglected the energy consumption of IoT, thereby affecting the performance and reducing the network lifetime. This paper presents a new multistep routing protocol based on cellular learning automata. The network lifetime is improved by a performance-based adaptive reward and fine parameters. Nodes can vote on the reliability of their neighbors, achieving network reliability and a reasonable level of security. Overall, the proposed method balances the security and reliability with the energy consumption of the network.

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참고문헌

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