Every single security company is talking about how they are using machine learning—as a security company you have to claim artificial intelligence to be even part of the conversation. However, this approach can be dangerous when we blindly rely on algorithms to do the right thing. Rather than building systems with actual security knowledge, companies are using algorithms that nobody understands and, in turn, discovering wrong insights.
In this session, we will discuss:
- Limitations of machine learning and issues of explainability
- Where deep learning should never be applied
- Examples of how the blind application of algorithms can lead to wrong results
Raffael Marty brings more than 20 years of cybersecurity industry experience across engineering, analytics, research and strategy to Forcepoint. Prior to joining the company, Marty ran security analytics for Sophos, a leading endpoint and network security company, launched pixlcloud, a visual analytics platform, and Loggly, a cloud-based log management solution. Additionally, Marty held key roles at IBM Research, ArcSight and Splunk and is an expert on best practices and emerging innovative trends in the security analytics space. Marty is one of the industry’s most respected authorities on security data analytics, big data and visualization. He is the author of “Applied Security Visualization” and is a frequent speaker at global academic and industry events. Marty holds a master's degree in computer science from ETH Zurich, Switzerland.