Publication Type : Conference Paper
Publisher : IEEE
Source : 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)
Url : https://doi.org/10.1109/icccnt61001.2024.10725137
Campus : Chennai
School : School of Computing
Department : Computer Science and Engineering
Year : 2024
Abstract :
Using Internet of Things (IoT) devices has become more efficient and convenient, but it has also increased the potential of security breaches, particularly from ransomware and Distributed Denial of Service (DDoS) assaults. This study looks into the ever-changing threats posed by ransomware on the Internet of Things, emphasizing human-centered detection and mitigation techniques. It highlights attack methods like supply chain breaches and device exploitation that jeopardize privacy and service continuity. To enhance IoT security, a deep neural network-based approach is proposed for automated reaction and real-time monitoring. The superior precision and efficacy of the suggested approach in mitigating ransomware and DDoS assaults in contrast to existing techniques underscores the significance of robust security protocols and active stakeholder engagement. This paper’s goal is to provide a thorough study of these dangers along with a novel solution that will improve security protocols in IoT ecosystems. This study seeks to close the gap between sophisticated technological protections and workable, user-oriented tactics by highlighting the need of human-centered approaches, guaranteeing that IoT devices continue to be dependable and safe in an increasingly interconnected world. This study emphasizes the vital need for an integrated strategy to IoT security that incorporates both cutting-edge technology and proactive human engagement through thorough evaluation and suggested solutions.
Cite this Research Publication : K Geetha, Dharmindar Chaudhary, K. Shrivarshini, Empowering IoT Security: Leveraging Deep Neural Networks Against Ransomware and DDoS Attacks, 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), IEEE, 2024, https://doi.org/10.1109/icccnt61001.2024.10725137