posted by user: Xavier || 7858 views || tracked by 18 users: [display]

MDPI Information 2019 : MDPI OA Journal of Information Science, Technology and Engineering --SI on Machine Learning for Cyber-Security

FacebookTwitterLinkedInGoogle

Link: https://www.mdpi.com/journal/information/special_issues/ML_Cybersecurity
 
When N/A
Where N/A
Submission Deadline Feb 28, 2019
Categories    machine learning   security   intrusion detection systems   artificial intelligence
 

Call For Papers

Dear Colleagues,

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
Guest Editor

High visibility: indexed by Ei Compendex, Scopus (Elsevier), Emerging Sources Citation Index (ESCI - Web of Science)

Related Resources

ECCSIT 2021   2021 European Conference on Computer Science and Information Technology (ECCSIT 2021)
IARCE 2021-Ei Compendex & Scopus 2021   2021 5th International Conference on Industrial Automation, Robotics and Control Engineering (IARCE 2021)
EI-CFAIS 2021   2021 International Conference on Frontiers of Artificial Intelligence and Statistics (CFAIS 2021)
IJCIS 2021   International Journal on Cryptography and Information Security
FCSIT 2021   2021 3rd Euro-Asia Conference on Frontiers of Computer Science and Information Technology (FCSIT 2021)
CFMAI 2021   2021 3rd International Conference on Frontiers of Mathematics and Artificial Intelligence (CFMAI 2021)
MDPI Mathematics InSysModGraph 2021   Special Issue Information Systems Modeling Based on Graph Theory
EI-ISoIRS 2021   2021 2nd International Symposium on Intelligent Robotics and Systems (ISoIRS 2021)
MDPI-SI-BDHA 2021   Call for Papers: Special Issue “Big Data for eHealth Applications” (MDPI Applied Sciences, IF 2.474 – Indexed on Scopus, Web of Science)
ICRE--EI, Scopus 2021   2021 5th International Conference on Reliability Engineering (ICRE 2021)--EI Compendex, Scopus