CPDP 2020: AI for the future of prevention, detection and mitigation of cyberattacks: what is at ...
DATE: Thursday 23 January 2020
VENUE: Area 42 Grand
SLOT: 10.30
ORGANISED BY: Cyber-Trust
MODERATOR: Paul Quinn, VUB (BE)
SPEAKERS: Rosa Barcelo, Squire Patton Boggs (BE); Athena Bourka, ENISA (EU); Dimitris Kavallieros, Center for Security Studies – Hellenic Ministry of Citizen Protection (GR); Carolin Möller, Deloitte (DE)
AI for the future of prevention, detection and mitigation of cyberattacks: what is at stake for privacy and data protection?
Panel Description
The Internet of Things (IoT) aims to establish an ecosystem of heterogeneous connected devices that communicate to deliver environments making our living, cities, transport, energy, and many other areas more intelligent. This amplifies concerns about the security of networked applications and services, based on known and unknown vulnerabilities and backdoors. More and more cybersecurity systems develop and deploy AI tools for the prevention, detection and mitigation of cyber-attacks, in particular in the field of cyber-threat intelligence and device profiling, aiming to simplify the threat identification process and improve the rate of remediation response. The panel aims to reflect upon what is at stake for data protection and privacy by the use of such automated tools, provided inter alia the requirements set in the recently adopted Cybersecurity Act at EU level for enhancing cybersecurity in products and services.
Since AI appears to become increasingly integrated in cybersecurity solutions, what applications are currently deployed, what is being developed by academia, business and the LEAs, how are models trained and what is aspired for in the short- and long-term future in the security sector?
What are the advantages and challenges of using AI in the cybersecurity context with respect to data protection and privacy?
In which ways can security research reconcile privacy, data protection and cybersecurity, creating compliant designs by advancing the principles of data protection and privacy by design and by default as well as integrating the learnings of the Data Protection Impact Assessments?
Best practices and lessons learnt through hands-on experience.
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