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
Vera Rimmer

Research expert, DistriNet, KU Leuven

Expertise: Computer security and privacy, applied machine learning and deep learning

More details

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