SecAppDev 2025 lecture details
Navigating the Security Landscape of Modern AI
In this session, we will overview the general security landscape of AI technologies, including foundational machine learning, deep learning, and large language models.
Schedule TBD
Abstract
The fast-evolving ecosystem of AI-enabled applications has exposed a complex interplay of vulnerabilities, some stemming from intrinsic pitfalls of data-driven AI and others arising from its unsafe integration into real-world applications. The goal of the session is to raise awareness about the underlying principles and practical challenges of AI security and privacy, and the ongoing mitigation efforts by both academic and industry players.
Key takeaway
Integrating AI inevitably increases the threat landscape of a system. Understanding how AI can be exploited is key to developing effective mitigations
Content level
Deep-dive
Target audience
Industry practitioners, developers, security analysts, security managers, and policy makers
Prerequisites
None
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Vera Rimmer
Research expert, DistriNet, KU Leuven
Expertise: Computer security and privacy, applied machine learning and deep learning
Join us for SecAppDev. You will not regret it!
Grab your seat nowRelated lectures
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