Akademik Veri Yönetim Sistemi
Doktora Sonrası Araştırma Programı Projesi, 2024 - 2025
(a) Novelty: Although the Internet of Things (IoT) is a technology that allows many devices to communicate with each other over the Internet, it faces many cybersecurity threats. Next-generation cybersecurity methods can provide more effective protection against these threats for the security of large and complex networks such as the Edge of Things (EoT) by using technologies such as artificial intelligence, machine learning, deep learning, learning from large datasets and recognizing a wide variety of threats. EoT allows data from IoT devices to be processed locally before being sent to cloud storage centers. However, new security structures must be developed to protect against various security attacks by addressing security challenges such as data integrity, privacy, and reliability in EoT networks. This research proposal aims to fill the gap in this field in the literature. In particular, we aim to provide low-cost and energy-efficient security solutions for edge devices with cloud computing in the IoT era.
(b) Method: A new EoT security framework that combines deep learning and federated learning-based security mechanisms will be proposed during the research process, by examining the existing IoT security frameworks. The suitability of the proposed solution for EoT and real life applications will be tested. This research also aims to propose lightweight and energy-efficient security methods for resource-constrained Edge devices by focusing on the EoT security issue.
(c) Management: The research will be co-directed with Dr. Alma Oracevic from the University of Bristol. We also plan to include some other academics who are experts in the field of cybersecurity at the University of Bristol and a doctoral student from Hacettepe University in the research.
(d) Widespread impact: We aim to produce three journal/conference publications with our proposed solutions to the given research problems. In addition, our other academic output goal is that the problems we will work on contribute to a postgraduate thesis.
(e) Career development potential: I aim to develop my career in this direction by researching the applications of deep learning algorithms and federated learning approaches, which have become widespread in recent years in EoT security. Moreover, my plans include introducing new courses in the field of IoT and Edge Computing security to our Artificial Intelligence Engineering Department, filling the shortage of scientists in this field in our country through developing collaborations with the relevant institutions, and increasing my motivation by reinvigorating my knowledge and research experience in a strong research environment such as Bristol University. I believe that this project will be an important step in achieving my career goals.
(f) Host advisor: Dr. Alma Oracevic has carried out many studies on the design of security solutions for various Internet of Things applications, which is the main topic of this project. The University of Bristol is one of the top 100 universities in the world. Bristol Cyber Security Group, where the research will be conducted, is among the institutions with the best laboratory for industrial IoT applications in the UK and the world, as well as a hub with extensive knowledge and necessary datasets and test environments to be used in the research. I believe the institution's facilities and the expertise of Dr. Alma Oracevic in the field will significantly contribute to the success of the proposed research.