Workshop on Machine Learning for CyberSecurity (MLCS)
InfoSec Conference Summary
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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.
The workshop aims at providing researchers with a forum to exchange and discuss scientific contributions and open challenges, both theoretical and practical, related to the use of machine-learning approaches in cybersecurity. We want to foster joint work and knowledge exchange between the cybersecurity community, and researchers and practitioners from the machine learning area, and its crossing with big data, data science, and visualization. It aims to highlight the latest research trends in machine learning, privacy of data, big data, deep learning, incremental and stream Learning, and adversarial learning. In particular, it aims to promote the application of these emerging techniques to cybersecurity and measure the success of these less-traditional algorithms.
The workshop shall provide a forum for discussing novel trends and achievements in machine learning and their role in the development of secure systems, and to identify new application areas as well as open and future research problems related to the application of machine-learning in the cybersecurity field.