Security Challenges and Innovative Solutions (SCIS): Harnessing AI to Safeguard IoT in Healthcare
In the ever-evolving landscape of healthcare technology, the integration of Internet of Things (IoT) devices has revolutionized patient care, data management, and operational efficiency. However, this technological advancement comes with its own set of challenges, particularly in the realm of security. This topic delves into the Security Challenges and Solutions for IoT in Healthcare with a specific focus on leveraging Artificial Intelligence (AI). As the healthcare sector becomes increasingly reliant on IoT devices for patient monitoring, diagnostics, and data management, it faces unprecedented security threats. This includes multifaceted challenges, ranging from data breaches to network vulnerabilities. In response, cutting-edge AI solutions are explored, such as machine learning techniques for anomaly detection, blockchain for secure data transmission, AI-driven encryption methods, and secure and explainable deep learning algorithms for diagnosis etc. This session aims to illuminate these groundbreaking strategies, projecting a landscape where AI not only mitigates risks but fortifies the very foundation of IoT in healthcare, ensuring patient privacy, data integrity, and system resilience in the face of evolving cyber threats.
Organisers:
Lu Zhang, Swansea university, lu.zhang@swansea.ac.uk
Jingjing Deng, Durham university
Hanchi Ren, Swansea university
Changrun Chen, Kent university
Submission format: This special session welcomes both full length papers (12 pages plus up to 2 pages of references) and abstracts (3 pages including references).
Deadline: All deadlines, including submission deadline and review timeline are the same as the main conference. Please follow this link to see all the Important Dates.
If you have any questions regarding this Special Session, please contact the organiser.