Machine learning techniques are becoming more sophisticated. Can these techniques be more affective at assessing mobile apps for malicious or risky behaviors than traditional means? This session will include a live demo showing data analysis techniques and the results machine learning delivers in terms of classifying mobile applications with malicious or risky behavior. The presentation will also explain the difference between supervised and unsupervised algorithms used for machine learning as well as explain how you can use unsupervised machine learning to detect malicious or risky apps.
What you will learn:
Understand the difference between advanced machine learning techniques vs. traditional means. Recognize different types of algorithms used to improve mobile security. Understand how you can use unsupervised machine learning to detect malicious or risky apps.