Artificial Intelligence-Enabled Security and Privacy for IoT
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 5765
Special Issue Editors
Interests: secure elements and trusted computing system design; security engineering (security patterns); monitoring of security properties in clouds
Special Issues, Collections and Topics in MDPI journals
Interests: Internet of Things; blockchain; security; software engineering; cloud computing; eHealth Systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) is a discipline that is gaining attention exponentially. Techniques such as machine learning and deep learning are being used to solve problems that were difficult to solve before they appeared. Large technology companies are exploring the application of AI in different markets such as healthcare, financial technology and autonomous vehicles. AI is currently driving transformations in various fields, including cybersecurity, which is another cross-cutting discipline. Security has been applying AI to improve the security posture of networks, systems and devices, with significant success. However, along with the benefits of AI, new threats are emerging as attackers themselves make use of deep learning or machine learning techniques to improve their malware. In fact, data protection, data quality and adversarial attacks that exploit vulnerabilities in AI systems are on the rise. This does not stop there; AI can also be used to create more sophisticated attacks that trigger an AI arms race between defenders and attackers. To effectively use AI in the cybersecurity domain and address these challenges, novel ideas and effective approaches need to be explored. To meet this plethora of new challenges, measures of different types need to be applied without losing sight of the fact that the basics of software engineering must remain during all phases in the secure software lifecycle. This Special Issue aims to collect contributions by leading researchers both from academia and industry, show the latest research results in the field of IoT monitoring, security and privacy and provide valuable information to researchers as well as practitioners, standards developers and policymakers. Its aim is to focus on the research challenges and issues in IoT security. Manuscripts regarding novel algorithms, architectures, implementations and experiences are welcome. Topics include, but are not limited to, the following:
- Formal security and resilience analysis of AI;
- Risk management and governance for AI application;
- Adversarial machine learning;
- AI for detection, prevention, response and recovery against potential threats;
- AI for wide-area situational awareness and traceability;
- Applied cryptography for AI and IIoT;
- Applications of formal methods to systems security;
- Embedded systems security;
- Privacy-preserving machine learning;
- Case studies of malware analysis in IoT environments;
- Security diagnosis tools;
- Trust frameworks and secure/private collaboration mechanisms;
- Operative systems security;
- Deep learning and AI for security;
- Specifically tailored security and privacy solutions;
- Secure methodologies for emerging technologies;
- Secure elements (TPM, TEE, SGX, ARM, etc.) in security engineering;
- AI cryptography in secure elements.
Dr. Antonio Muñoz
Dr. Alexandru Vulpe
Guest Editors
Manuscript Submission Information
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