* 1st Workshop on Machine Learning for CyberSecurity (MLCS 2019) *

co-located with ECMLPKDD 2019, the European Conference on Machine
Learning and Principles and Practice of Knowledge Discovery in Databases.

http://mlcs.lasige.di.fc.ul.pt/

    Paper submission deadline: June 7, 2019, 11:59 PM
    Acceptance notification: July 19, 2019
    Camera ready submission: July 26, 2019
    Deadline for participation in competition: August 24, 2019
    Notification of competition results: August 31, 2019
    Workshop: September 20, 2019

*** SUBMISSION GUIDELINES ***

Submissions are accepted in two formats:

1) 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.

2) 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.

Submission web site: https://easychair.org/my/conference?conf=mlcs2019

*** 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 ***

- 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

*** COMMITTEES ***

Workshop chairs

    Annalisa Appice, Università degli Studi di Bari, Italy
    Battista Biggio, Università degli Studi di Cagliari, Italy
    Donato Malerba, Università degli Studi di Bari, Italy
    Fabio Roli, Università degli Studi di Cagliari, Italy
    Ibéria Medeiros, Universidade de Lisboa, LASIGE, Potugal
    Michael Kamp, University of Bonn, Fraunhofer IAIS, Germany
    Pedro M. Ferreira, Universidade de Lisboa, LASIGE, Portugal

Program Committee
(confirmed members)

    Alysson Bessani, University of Lisbon - LASIGE, Portugal
    Gianluigi Folino, CNR-ICAR, Italy
    Giorgio Giacinto, University of Cagliary, Italy
    Luis Muñoz-González, Imperial College London, United Kingdom
    Marc Dacier, Eurecom, France
    Marco Vieira, University of Coimbra, Portugal
    Miguel Correia, University of Lisbon, Portugal
    Mihalis Nicolaou, The Cyprus Institute, Cyprus
    Pavel Laskov, University of Liechtenstein, Liechtenstein
    Rogério de Lemos, University of Kent, United Kingdom
    Sara Madeira, University of Lisbon, Portugal
    Tommaso Zoppi, University of Florence, Italy
    Vasileios Mavroeidis, University of Oslo, Norway