Presentations already confirmed include:
► Mallet against machine: regulating the AI landscape
Subhajit Basu, Associate Professor Cyber Law, University of Leeds
- In order to make automation effective, feeding a vast amount of data is necessary. How do you ensure that this data is used in a secure way and for the right purposes?
- What are the legal implications if a machine learning platform gets hacked?
- The connected landscape needs greater regulation. But how do you implement this, especially when there is a stigma that ‘lawyers don’t understand technology and technology professionals don’t understand the law!
► Innovation: Information security’s worst nightmare?
Adam Hembury, Director of Innovation, DLA Piper
- Where do innovation and Information Security collide?
- The strategic data questions we face:
- Client confidentiality
- Data ownership
- Data Analytics
- Artificial Intelligence - Machine Learning
- Enterprise search
- Case study: innovation and its application at DLA Piper
► Machine vs. machine. How AI is changing how we tackle cyber-threats
Noura Al Moubayed, Assistant Professor in the department of Computer Science, Durham University
- How artificial intelligence is impacting the cyber-threat landscape
- How can AI and automation help the process of cyber threat detection and prevention
- Collaboration between academia and law enforcement
► Get your head out of the Clouds: clear truths on how AI can help Cloud security
Stephen McGough, Senior Lecturer, Data Science, Newcastle University
- How can AI help secure the Cloud? Case study on how machine learning algorithms can be used in detecting fraudulent behaviour.
- How AI can help in the efforts against ransomware. How machine learning algorithms can be used to profile both the victims and the perpetrators of ransomware attacks
- The need for greater collaboration between industry, private sector and law enforcement if we are to secure connected networks and tackle cyber-criminals who are also using machine learning.
►Automate to authenticate. AI as a key player in authentication
Stefano V. Albrecht, Assistant Professor, Artificial Intelligence, School of Informatics at The University of Edinburgh
- The new Centre of Excellence in Cyber Security Research at Edinburgh University: research and collaboration opportunities
- Rethinking remote authentication: a new approach based on interaction between intelligent autonomous agents
- The DARPA Spectrum Collaboration Challenge: designing wireless networks as intelligent collaborative systems and associated security risks
► HR Analytics and the 'Insider Threat' Detection
John Bishop, Professor of Cognitive Computing, Goldsmiths University
- Insider threat: why is it still such a problem and can AI help?
- Case study: insights into how to use HR Analytics to analyse and assess user behaviour and aid in the cyber-threat detection effort
- Can AI be used to detect a potential insider threat before it happens?
► Placing your bets on Machine Learning: Now core capability for all functions
Finbarr Joy, Group CTO, Superbet
- Formerly a niche / edge specialisation, ML has become core to how all software is built
- Embedding ML as a core function ensures security considerations can be better integrated than ever before
- Looking at strategy and implementation scenarios for ML-driven initiatives in support of security
► AI: Reasons to Just Say No
James McKinlay, Chief Information Security Officer, Barbican Insurance Group
- The AI bandwagon. And the risks of jumping on it
- When every vendor is claiming AI expertise, how do you differentiate?
- What could/should you be doing instead?
► CNI AI: the Impact of Machine Learning on Data Protection and Management in Critical National Infrastructure
Peter Jackson, Chief Data Officer, Southern Water
- What is the real business case for implementing machine learning? Do the benefits in business efficiency outweigh the risks and costs?
- The critical real world consequences when machine learning goes wrong
- AI and data protection. In order for a machine learning platform to be truly effective, a huge amount of data needs to input. How do you manage, regulate and secure this data?