MLCS2020: 2nd Workshop on Machine Learning for Cybersecurity ECMLPKDD 2020 Ghent, Belgium, September 14, 2020 |
Conference website | http://mlcs.lasige.di.fc.ul.pt/ |
Submission link | https://easychair.org/conferences/?conf=mlcs2020 |
Abstract registration deadline | June 19, 2020 |
Submission deadline | June 19, 2020 |
Call for papers
COVID-19 PLAN
The ECML-PKDD 2020 conference and all its satellite events, including MLCS 2020 workshop, *will not be postponed*: everything will take place on September 14-18, 2020, as planned.Thus, all accepted contributions (including workshop papers) will be published, presented, etc, as normal, although presentations may likely take a different form.The organization of ECML-PKDD 2020 is developing plans in case the conference needs to be organized entirely virtually, or in a hybrid manner.Final decisions on the modalities will be taken and communicated as soon as possible, and in any case before the early registration deadline (second half of July).
Important Dates (Lisbon, GMT)
- Paper submission deadline: June 19, 2020, 11:59 PM (strict, extended)
- Acceptance notification: July 9, 2020
- Camera ready submission: July 20, 2020
- Workshop: September 14, 2020
Overview
The last decade has been a critical one regarding cybersecurity, with studies estimating the cost of cybercrime to be up to 0.8 percent of the global GDP. The capability to detect, analyse, 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.
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
Submission guidelines
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. Templates are available here. 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.
Committees
Workshop chairs
- Annalisa Appice, Università degli Studi di Bari, Italy
- Donato Malerba, Università degli Studi di Bari, Italy
- Ibéria Medeiros, Universidade de Lisboa, LASIGE, Potugal
- Michael Kamp, Monash University, Australia
- Pedro M. Ferreira, Universidade de Lisboa, LASIGE, Portugal
Invited Speaker
TBA
Program Committee
- Alysson Bessani, University of Lisbon - LASIGE, Portugal
- Cagatay Turkay, University of Warwick, United Kingdom
- Fabio, Pierazzi, King's College London, United Kingdom
- Giorgio Giacinto, University of Cagliary, Italy
- Leonardo Aniello, University of Southampton, United Kingdom
- Lorenzo, Cavallaro, King's College London, United Kingdom
- Luis Muñoz-González, Imperial College London, United Kingdom
- Marc Dacier, Eurecom, France
- Marco Vieira, University of Coimbra, Portugal
- Miguel Correia, University of Lisbon, Portugal
- Rogério de Lemos, University of Kent, United Kingdom
- Sara Madeira, University of Lisbon, Portugal
- Shihao Ji, Georgia State University, USA
- Tommaso Zoppi, University of Florence, Italy
- Vasileios Mavroeidis, University of Oslo, Norway