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Why Safety and Security is Important in ML and How to Secure your ML-based Solutions |
When enterprises adopt new technology, safety and security are often on the back burner as it can seem more important to get new products or services to users as quickly and cost-effective as possible. AI and ML offer all the same opportunities for vulnerabilities and misconfigurations as earlier technological advances, but they also have unique risks. As businesses embark on major digital transformations powered by these technologies, those risks may become greater, as AI and ML require more and more complex data. This means cloud platforms may handle heavy workloads, adding another level of vulnerability. It is no surprise that cybersecurity is one of the most worrisome risks for AI adopters. In this presentation, Rachid Kherrazi will focus on safety and secure coding best practices and discuss security pitfalls of the Python programming language. The engineer will talk also about machine learning with some hands-on demostrations and stories from real life.
Rachid Kherrazi Rachid Kherrazi is CTO at AKKA Technologies in the Netherlands, an ICT service provider in the High-Tech Industry. During his career, Rachid obtained experience in Digital Transformation, AI and quality improvements in several companies. In that regard, Rachid has adquired strong skills in product and process development. Currently, he is working on several innovation projects within the Dutch high-tech sector and is involved in several academic research initiatives in Europe. Rachid Kherrazi obtained his Master on electrical engineering from the Technical University of Errachidia (Morocco), is a Six Sigma Certified Black Belt and recently obtained his license as an iSQI Certified Model Based Trainer.
This presentation will give an overview of ML in relation to security and safety. |
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