Advances in Artificial Intelligence for Intelligent Systems: Methods, Trust, and Cyber Defense
A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Artificial Intelligence and Digital Systems Engineering".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 1879
Special Issue Editor
Interests: cyber security; Internet of Things; information systems security; technology management
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Intelligent systems are now foundational to modern life, from clinical decision support and smart grids to autonomous mobility and digital public services. As these systems scale, they must simultaneously improve capability, reliability, and resilience against evolving cyber threats. This Special Issue of Systems invites contributions that advance the methods, tools, and governance needed to design and operate intelligent systems that are secure, trustworthy, and auditable without sacrificing performance.
We seek submissions at the intersection of AI/ML and cybersecurity, emphasizing end-to-end viewpoints that integrate people, process, technology, and policy. Suitable works include novel algorithms; robust learning and inference; adversarial testing; privacy-preserving analytics; assurance cases; governance, risk, and compliance (GRC) models; and domain case studies demonstrating measurable impacts. We particularly welcome research connecting socio-technical considerations—such as organizational workflows, human factors, and regulatory constraints—to concrete system architectures and life-cycle practices aligned with systems thinking and practice.
This Special Issue seeks contributions that address themes including, but not limited to, the following:
- Trustworthy, explainable, and verifiable AI for mission-critical decisions;
- AI for cyber defense, spanning intrusion detection, anomaly detection, automated threat intelligence, OSINT, deception, and digital forensics;
- Security of AI pipelines, including data curation, model provenance, and model-supply chain integrity;
- Adversarial robustness, model hardening, and continuous validation;
- Cyber–physical systems and ICS/OT security with attention to safety–security trade-offs;
- Privacy-preserving machine learning (federated learning, secure aggregation, differential privacy) for sensitive sectors;
- Governance models, auditability, and compliance frameworks for AI in regulated industries;
- Evaluation frameworks, simulation environments, and reproducible benchmarks that accelerate adoption.
Dr. Maurice E. Dawson
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- trustworthy AI
- adversarial robustness
- privacy-preserving machine learning
- intrusion and anomaly detection
- cyber-physical systems (CPS) security
- federated learning
- explainable AI (XAI)
- AI-driven threat intelligence and OSINT
- governance, risk, and compliance (GRC)
- model and data supply chain security
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