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MLCS2021@ECMLPKDD 2021 : MLCS2021@ECMLPKDD: The 3th Workshop on Machine Learning for CyberSecurity 2021-Extended deadline (June 30)

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Link: https://mlcs.lasige.di.fc.ul.pt/
 
When Sep 13, 2021 - Sep 13, 2021
Where Bilbao,Spain
Submission Deadline Jun 30, 2021
Notification Due Jul 24, 2021
Categories    cybersecurity   adversarial machine learning   data security and privacy   machine learning
 

Call For Papers

MLCS@ECMLPKDD2021: 3rd International Workshop on Machine Learning for Cybersecurity 
OVERVIEW
The last decade has been a critical one regarding cybersecurity, with studies estimating the cost of cybercrime to be up to 1 percent of the global GDP in 2020. The capability to detect, analyze, and defend against threats in (near) real-time conditions is not possible without employing machine learning techniques and big data infrastructures. This gives rise to cyberthreat intelligence and analytic solutions, such as (informed) machine learning on big data and open-source intelligence, to perceive, reason, learn, and act against cyber adversary techniques and actions. Moreover, organisations’ security analysts have to manage and protect systems and deal with the privacy and security of all personal and institutional data under their control. The aim of this workshop is to provide researchers with a forum to exchange and discuss scientific contributions, open challenges and recent achievements in machine learning and their role in the development of secure systems.
The workshop follows the success of the two previous editions (MLCS 2019 and MLCS 2020) co-located with ECML-PKDD 2019 and ECML-PKDD 2020 - in both editions the workshop gained strong interest, with an attendance between 30 and 40 participants. 
 
CALL FOR PAPERS
MLCS welcomes both research papers reporting results from mature work, recently published work, as well as more speculative papers describing new ideas or preliminary exploratory work. Papers reporting industry experiences and case studies will also be encouraged. However, it should be noticed that papers based on recently published work will not be considered for publication in the proceedings.
Topics
All topics related to the contribution of machine learning approaches to the security of organisations’ systems and data are welcome. These include, but are not limited to:
• Machine learning for:
◦ the security and dependability of networks, systems, and software
◦ open-source threat intelligence and cybersecurity situational awareness
◦ data security and privacy
◦ cybersecurity forensic analysis
◦ the development of smarter security control
◦ the fight against (cyber)crime, e.g., biometrics, audio/image/video analytics
◦ vulnerability analysis
◦ the analysis of distributed ledgers
◦ malware, anomaly, and intrusion detection
• Adversarial machine learning and the robustness of AI models against malicious actions
• Interpretability and Explainability of machine learning models in cybersecurity
• Privacy preserving machine learning
• Trusted machine learning
• Data-centric security
• Scalable / big data approaches for cybersecurity
• Deep learning for automated recognition of novel threats
• Graph representation learning in cybersecurity
• Continuous and one-shot learning
• Informed machine learning for cybersecurity
• User and entity behavior modeling and analysis
Paper submission
MLCS welcomes both research papers reporting results from mature work, recently published work, as well as more speculative papers describing new ideas or preliminary exploratory work. Papers reporting industry experiences and case studies will also be encouraged. However, it should be noticed that papers based on recently published work will not be considered for publication in the proceedings.
Submissions are accepted in two formats:
• Regular research papers with 12 to 16 pages including references. To be published in the proceedings, research papers must be original, not published previously, and not submitted concurrently elsewhere.
• Short research statements of at most 6 pages. Research statements aim at fostering discussion and collaboration. They may review research published previously or outline new emerging ideas.
 
All submissions should be made in PDF using the EasyChair platform and must adhere to the Springer LNCS style. 
All regular workshop papers (except papers reporting recently published work) will be published in the workshop proceedings. Research statements will be published online in the workshop program page.
IMPORTANT DATES
Paper Submission Deadline:  Extended: June 30 2021
Paper author notification:  Extended: July 24, 2021
Camera Ready Submission: July,31 2021
Workshop: September,13 2021
WEB PAGE
https://mlcs.lasige.di.fc.ul.pt/

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