Yazar "Barişkan, Mehmet Ali" seçeneğine göre listele

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    A novel approach to continuous CVE analysis on enterprise operating systems for system vulnerability assessment
    (Springer Science and Business Media B.V., 2022) Kocaman, Yusuf; Gönen, Serkan; Barişkan, Mehmet Ali; Karacayilmaz, Gökçe; Yilmaz, Ercan Nurcan
    Advances in information and technology have provided great opportunities and conveniences for human life. However, with this process, attackers have switched to cyberspace due to various factors such as anonymity, easy attack tools, and non-deterrent penalties. For this reason, various methods have been developed to protect systems from cyber-attacks. One of the most important methods is the continuity-based vulnerability analysis of the systems and the network created by the systems, even for emerging threats. In this study, the current and comprehensive list of vulnerabilities created by combining the data obtained from different CVE sources is compared with the packages on the operating system. In this way, it is possible to obtain information about the system’s current openness status and take precautions. The analyzes have been carried out on Ubuntu operating system; however, the study can be adapted to other operating systems and larger systems by following the implementation phases of the proposed method. © 2022, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.
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    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.