Feature Papers in Safety, Security, Privacy, and Cyber Resilience

Dear Colleagues,

Artificial intelligence pervades all aspects of contemporary life and is increasingly shaping how we work, communicate and organize ourselves as a society. Its rapid diffusion across industry, research and public services will continue to accelerate, leading to increasingly complex and interdependent AI-driven systems. The driving force behind all these successful applications is machine learning and knowledge extraction. Here, the need for resilient, trustworthy and secure approaches grows substantially.

Modern applications operate in open, dynamic and often adversarial environments, creating vulnerabilities ranging from data poisoning and adversarial manipulation to model drift, misuse and systemic failures.

At the same time, AI has become indispensable for maintaining cyber security itself, supporting anomaly detection, threat intelligence, incident response, compliance checking and the continuous monitoring of complex infrastructures. These developments require not only technical safeguards but also governance structures, auditability, transparency and alignment with organizational and societal norms.

This topical collection therefore invites contributions from researchers and practitioners that address fundamental and applied challenges involving MAKE in security, safety, privacy and cyber resilience.

Submissions that connect machine learning with knowledge extraction, hybrid or domain-informed methods, causal reasoning, verification techniques or human-centred evaluation are particularly welcome, as they reflect the interdisciplinary scope of the journal.

Work on emerging directions such as secure foundation models, provenance tracking, watermarking, robustness under distributional shift, risk-aware learning, explainability for safety-critical contexts and red-team evaluation will fit equally well within the scope.

Prof. Dr. Simon Tjoa
Collection 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. 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 collection 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. Machine Learning and Knowledge Extraction 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 1800 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.