Inside the Mind of Hackers: Safeguard your intellectual property in an AI driven future

As AI accelerates innovation, the risk of intellectual property theft grows. Application code - whether in C++, .NET, Python, or other environments - often contains sensitive algorithms, and machine learning (ML) models are now prime targets for attacks. From knowledge exposure to algorithm replay and integrity violations, organizations must defend their critical assets against evolving threats.

This presentation takes a hacker’s perspective on software security, analyzing real-world attack scenarios and presenting practical countermeasures. We will explore how to protect code and data in conventional and ML applications while securing the entire ML environment from development to deployment. With real-world cases, proven strategies, and ready-to-use techniques, we’ll demonstrate that effective software protection is not just a necessity - it’s a competitive advantage.