Innovative Solutions for Safeguarding Intelligent Systems

The field of cybersecurity has expanded to address the unique challenges posed by Artificial Intelligence (AI), Machine Learning (ML), and Internet-of-Things (IoT) devices as these technologies have become integral to modern infrastructure. Intelligent systems have become increasingly susceptible to a spectrum of cyber threats that compromise their security and functionality. As such, the urgency to develop robust, innovative security solutions tailored for these technologies cannot be overstated. Recent studies in this field have proposed the integration of advanced AI and ML-based security mechanisms. These approaches focus on proactive identification and mitigation of potential threats that could undermine system integrity and confidentiality. However, despite considerable advancements, gaps still exist in fully securing these systems against sophisticated cyber attacks.

This Research Topic aims to address the essential need for modern and innovative security solutions tailored to various intelligent systems and environments. By exploring cutting-edge methodologies, it seeks to enhance the security framework that ensures the comprehensive protection of AI, ML, and IoT technologies from emerging cyber threats. The goal is to facilitate the development of security solutions that not only respond to threats reactively but also predict and prevent them effectively.

To gather further insights into the range and limitations of intelligent system security, we welcome articles addressing, but not limited to, the following themes:

- AI Security and Privacy
- Information Security in AI ecosystems
- AI-driven IoT Security Solutions
- Comprehensive End-to-End AI Security
- Hardware Security in AI Applications
- Cybersecurity Dynamics in AI and Cloud
- Access Control and Security in AI
- Security Aspects of Microfluidic Biochips
- Methods for Hacking and Testing AI Systems
- Innovative Strategies for End-to-End AI Security

The list of article types for this Research Topic includes, but is not limited to, original research, reviews, case studies, and short reports.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: AI Security, Machine Learning Defense, IoT Vulnerabilities, Proactive Threat Mitigation, Intelligent Systems Protection

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.