Special Issue "Machine Learning for Cyber-Security"
Deadline for manuscript submissions: closed (15 November 2019) | Viewed by 121562
Interests: cyber-security; deception; maritime security; critical infrastructure security; intrusion detection systems; cyber situational awareness; cyber security training
Special Issues, Collections and Topics in MDPI journals
Special Issue in Journal of Cybersecurity and Privacy: Cyber Situational Awareness Techniques and Human Factors
Special Issue in Information: Cyber-Security for the Maritime Industry
Over the past decade, the rise of new technologies, such as the Internet of Things and associated interfaces, have dramatically increased the attack surface of consumers and critical infrastructure networks. New threats are being discovered on a daily basis making it harder for current solutions to cope with the large amount of data to analyse. Numerous machine learning algorithms have found their ways in the field of cyber-security in order to identify new and unknown malware, improve intrusion detection systems, enhance spam detection, or prevent software exploit to execute.
While these applications of machine learning algorithms have been proven beneficial for the cyber-security industry, they have also highlighted a number of shortcomings, such as the lack of datasets, the inability to learn from small datasets, the cost of the architecture, to name a few. On the other hand, new and emerging algorithms, such as Deep Learning, One-shot Learning, Continuous Learning and Generative Adversarial Networks, have been successfully applied to solve natural language processing, translation tasks, image classification and even deep face recognition. It is therefore crucial to apply these new methods to cyber-security and measure the success of these less-traditional algorithms when applied to cyber-security.
This Special Issue on machine learning for cyber-security is aimed at industrial and academic researcher applying non-traditional methods to solve cyber-security problems. The key areas of this Special Issue include, but are not limited to:
Generative Adversarial Models; One-shot Learning; Continuous Learning; Challenges of Machine Learning for Cyber Security; Strength and Shortcomings of Machine Learning for Cyber-Security; Graph Representation Learning; Scalable Machine Learning for Cyber Security; Neural Graph Learning; Machine Learning Threat Intelligence; Ethics of Machine Learning for Cyber Security Applications
Dr. Xavier Bellekens
Manuscript Submission Information
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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. Information 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 1600 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.
- machine learning
- intrusion detection systems