Artificial Intelligence-Supported Detection Systems on Embedded Devices

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Alnıaçık F., Yıldırım F., GÖNEN S., Alhan B., BARIŞKAN M. A., SAYAN H. H., ...More

El-Cezeri Journal of Science and Engineering, vol.11, no.1, pp.109-119, 2024 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 11 Issue: 1
  • Publication Date: 2024
  • Doi Number: 10.31202/ecjse.1312555
  • Journal Name: El-Cezeri Journal of Science and Engineering
  • Journal Indexes: Scopus
  • Page Numbers: pp.109-119
  • Keywords: Artificial Intelligence, Attack Detection, Cyber Security, Embedded System Security, Vulnerability Analysis
  • Istanbul University Affiliated: No


With the transition to the information society, all areas of our lives rapidly shift to the digital environment. From education to health, citizenship procedures to social life, all areas of our lives interact in the digital cyber environment. In this process, smart cities, smart networks, and smart factories, especially critical infrastructures required for social life, have become open to the intranet and the internet for efficient efficiency, speed, remote maintenance, and maintenance. Along with this process, these systems have faced new threat surfaces. One of the components that play an essential role in the operation of these systems is embedded systems. These systems contribute significantly to the effective operation of essential infrastructures. However, interruption in these systems can lead to significant negative consequences, including economic damage and human life. Although there are many studies on the functioning of embedded systems, there are not enough studies on the cyber security analysis of these systems. For this reason, attack and detection analyses for embedded systems have been carried out in this study on the test environment created using real systems. The study aims to detect passive attack, which is more difficult to detect than active attacks on the system, by using artificial intelligence algorithms. The analysis results have shown that the attack has been detected in a high ratio. It has been evaluated that the study will significantly contribute to other studies on the security of embedded systems.