Streaming systems, hidden risks, and AI-driven consequences
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About this event
Agenda
Modern AI systems don’t rely on static datasets, they depend on continuous streams of real-time data to train, update, and make decisions.
We explore streaming data pipelines as a critical attack vector for AI-driven applications.
Instead of targeting models directly, attackers manipulate the data flowing into them. By injecting, modifying, or replaying events, adversaries poison training data, distort real-time features, and influence decisions without detection.
We’ll examine how these attacks work in practice, from subtle data drift to targeted event injection, and why traditional security measures fall short. We’ll look at key weaknesses in modern pipelines and explore defensive strategies that go beyond infrastructure security.
About speaker:
Olena is a Staff Developer Advocate at Confluent and a recognized expert in data streaming and analytics. With two decades of experience in software engineering, she has built mission-critical applications, led high-performing teams, and driven large-scale technology adoption at industry leaders like Nokia, HERE Technologies, AWS, and Aiven. A passionate advocate for real-time data processing and AI-driven applications, Olena empowers developers and organizations to use the power of streaming data. She is an AWS Community Builder, a dedicated mentor, and a volunteer instructor at a nonprofit tech school, helping to shape the next generation of engineers. As an international speaker and thought leader, Olena regularly presents at top global conferences, sharing deep technical insights and hands-on expertise. Whether through her talks, workshops, or content, she is committed to making complex technologies accessible and inspiring innovation in the developer community.
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