Yazar "Sindiren, Erhan" seçeneğine göre listele

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    Network Forensics of RPL-Based Attacks
    (Düzce Üniversitesi Fen Bilimleri Enstitüsü, 2020) Karacayılmaz, Gökçe; Gönen, Serkan; Artuner, Harun; Yılmaz, Ercan Nurcan; Sayan, Hasan Hüseyin; Sindiren, Erhan
    IoT devices, which are increasing in highly manner day by day, are now in everywhere in our life. WSNs are used together with IoT devices to monitor real environments. In this study, attacks against WSNs were carried out. The attack chosen for this study is a flood attack. In addition, solution suggestions for this attack are presented. In this context, firstly reference and attack packages have been collected, and then the collected packages have been compared with the reference packages and forensic investigations have been carried out. The result of the evaluation has shown the importance continuous monitoring on 24/7 basis and detecting abnormal behaviors in IoT traffic with forensics analysis for preventing attacks.
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    A New Approach in Cyber Security of Industrial Control Systems: Li-Fi
    (Gazi Üniversitesi, 2022) Gönen, Serkan; Sayan, Hasan Hüseyin; Karacayılmaz, Gökçe; Sindiren, Erhan; Üstünsoy, Furkan; Artuner, Harun; Yılmaz, Ercan Nurcan; Işık, Mehmet Fatih
    Industrial Control Systems used in the control of critical infrastructures, especially in smart grids, have made a rapid transition from an isolated network architecture to wired and wireless external networks due to the factors that facilitate human life such as productivity, economy and speed. With this transition, industrial control systems specific protocols have become insufficient and hybrid protocols have started to be used. As a result, the vulnerabilities specific to the internet and new protocols besides the vulnerabilities specific to industrial control systems have started to threaten control systems. In this study, the usability of the Light Fidelity (Li-Fi) transmission infrastructure in data transmission was investigated as a solution proposal for the smart city / network infrastructure where attack of False Data Injection carried out. This study will make important contributions to the studies carried out for industrial control systems security.
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    Öğe
    A Novel Approach to Prevention of Hello Flood Attack in IoT Using Machine Learning Algorithm
    (TUBITAK, 2022) Gönen, Serkan; Barişkan, Mehmet Ali; Karacayilmaz, Gökçe; Alhan, Birkan; Yilmaz, Ercan Nurcan; Artuner, Harun; Sindiren, Erhan
    With the developments in information technologies, every area of our lives, from shopping to education, from health to entertainment, has transitioned to the cyber environment, defined as the digital environment. In particular, the concept of the Internet of Things (IoT) has emerged in the process of spreading the internet and the idea of controlling and managing every device based on IP. The fact that IoT devices are interconnected with limited resources causes users to become vulnerable to internal and external attacks that threaten their security. In this study, a Flood attack, which is an important attack type against IoT networks, is discussed. Within the scope of the analysis of the study, first of all, the effect of the flood attack on the system has been examined. Subsequently, it has been focused on detecting the at-tack through the K-means algorithm, a machine learning algorithm. The analysis results have been shown that the attacking mote where the flood attack has been carried out has been successfully detected. In this way, similar flood attacks will be detected as soon as possible, and the system will be saved from the attack with the most damage and will be activated as soon as possible. © 2022, TUBITAK. All rights reserved.