Browsing by Author "Dalveren, Y."

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Citation - WoS: 1
Citation - Scopus: 1
On the Accuracy of an Emitter Localization Method Based on Multipath Exploitation in Realistic Scenarios
(Taylor & Francis Ltd, 2022) Al Imran, M. A.; Ank, E.; Dalveren, Y.; Tabakcioglu, M. B.; Kara, A.
This study aims to evaluate the accuracy of a method proposed for passive localization of radar emitters around irregular terrains with a single receiver in Electronic Support Measures systems. Previously, the authors targeted only the theoretical development of the localization method. In fact, this could be a serious concern in practice since there is no evidence regarding its accuracy under the real data gathered from realistic scenarios. Therefore, an accurate ray-tracing algorithm is adapted to enable the implementation of the method in practice. Then, realistic scenarios are determined based on the geographic information system map generated to collect high-resolution digital terrain elevation data, as well as realistic localization problems for radar emitters. Next, simulations are performed to test the localization method. Thus, the performance of the method is verified for practical implementation in the electronic warfare context for the first time. Lastly, the performance bounds of the method are discussed.
Securing the Internet of Things: Challenges and Complementary Overview of Machine Learning-Based Intrusion Detection
(Institute of Electrical and Electronics Engineers Inc., 2024) Isin, L.I.; Dalveren, Y.; Leka, E.; Kara, A.
The significant increase in the number of IoT devices has also brought with it various security concerns. The ability of these devices to collect a lot of data, including personal information, is one of the important reasons for these concerns. The integration of machine learning into systems that can detect security vulnerabilities has been presented as an effective solution in the face of these concerns. In this review, it is aimed to examine the machine learning algorithms used in the current studies in the literature for IoT network security. Based on the authors' previous research in physical layer security, this research also aims to investigate the intersecting lines between upper layers of security and physical layer security. To achieve this, the current state of the area is presented. Then, relevant studies are examined to identify the key challenges and research directions as an initial overview within the authors' ongoing project. © 2024 IEEE.