Latest Advancements in Machine Learning Applications for Cybersecurity

Dear Colleagues,

The increasing complexity of cyberattacks necessitates advanced, robust, and reliable security mechanisms. Machine learning (ML) has emerged as a powerful tool in the modern cybersecurity arena, enabling various network devices to operate more efficiently and reliably. As cyber threats continue to rapidly evolve in nature and complexity, there is a need for active ongoing research into ML-based cybersecurity solutions. This Special Issue aims to explore the latest advancements in ML applications for cybersecurity, emphasizing both theoretical and practical implementations.

The scope of this Special Issue includes, but is not limited to, the following topics.

• ML-based intrusion detection/prevention;
• Impact of adversarial machine learning (AML) in cybersecurity;
• Anomaly and malware detection;
• Applications of ML in Internet of Things (IoT) security;
• Role of high-quality datasets in ML-based cybersecurity.

We invite high-quality submissions including original research articles, survey papers, and studies that present innovative approaches, evaluations, and real-world applications of ML in cybersecurity. Papers that discuss challenges, pave the way for new research avenues, and propose methodologies to improve the trustworthiness of existing ML-based cybersecurity solutions are also encouraged.

You may choose our Joint Special Issue in Electronics.

Prof. Dr. Weiqing Sun
Dr. Medha Pujari
Guest Editors

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. Network is an international peer-reviewed open access quarterly 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 1200 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.