The paper “Dos and Dont’s of Machine Learning in Computer Security”, co-authored by Dr. Fabio Pierazzi, member of the Cybersecurity Group (CYS) at the Department of Informatics at King’s College London, received a prestigious Distinguished Paper Award at the USENIX Security Symposium 2022, one of the flagship cybersecurity conferences
At the Dagstuhl Seminar on Security of Machine Learning in July 2022, experts from all over the world met to discuss research trends and future directions for research in protecting ML-based systems. The seminar featured a mix of academics, young researchers, and industry practitioners. Despite the relaxed atmosphere, the seminar inspired diverse questions—among which, a recurring theme entailed the practical relevance of related research. For example, should industry truly be worried about the attacks portrayed in research papers, and are the assumptions made in research truly representative of the real world?
On the 4th of November 2022, the Cybersecurity Group (CYS) of KCL Informatics organized a workshop day at the Strand campus, an opportunity to share the breadth of research being conducted across CYS. The workshop was also a chance to meet Prof. Martin Albrecht and his PhD students, who will be joining KCL in January 2022. Martin and his team presented their research lattice-based and post-quantum cryptography, block ciphers for algebraic platforms and attacks on cryptographic protocols.
Research led by Dr Kovila P.L Coopamootoo, Lecturer in Computer Science in the Department of Informatics, in collaboration with colleagues from Newcastle and Durham, has examined how internet users feel about online tracking and how their feelings affect their online behaviour.
Academics from the Department of Informatics are conducting world-leading research with measurable impact: 1) an AI planning tool that makes drilling safer, faster, and more environmentally friendly, 2) the development of robotic therapy devices for the treatment of lower limb injuries, 3) pioneering 5G research that impacts global telecommunications industry and 4) research on provenance, a fundamental data governance technique that provides a reliable account of a system's actions and the data it altered.
There are increasing calls for explainability of data-intensive applications. Such a demand for explainability stems from various reasons, such as regulations, governance frameworks or business drivers. Explanations are becoming a mechanism to demonstrate good governance of data-processing pipelines.