Opening speeches stressed on the importance on AI for defense, since each day networks and services experience attacks, not only from external actors, but from inside our networks. The idea is not only to disrupt service, but to steal data, jeopardizing research and intellectual property. This constitutes the rise of adversarial AI, and to react to this menace, it is necessary to enhance our understanding and usage of generative adversarial networks.
Other interesting topic is about "opening the black box" in order to have an explanatory AI, which has the goal of explaining the reasoning of the decisions taken by AI. This is important to gain confidence of users and to speed up the adoption of these techniques in various use cases.
Some other topics that caught my attention:
- The diverse malicious AI techniques to break cyber-security, such as data poisoning. This in order to induce errors on the machine learning model.
- The bias problem, which most of the times has its source of the training data and leads to erroneous decisions at the end of the AI process.
- The usage of different frameworks to have behavioral analysis, very useful to detect deviation of usual usage patterns of an entity. This helps to detect compromised entities our users that deviate or abuse of privileges.
I hope day 2 brings new insights and interesting approaches to better understand AI and its challenges.