Four ways AI/ML can make a real difference for your cybersecurity

Generally speaking, AI and machine learning have the most to offer when augmenting human intelligence to assist with time and labor-intensive tasks involving large datasets. At least for the foreseeable future, AI/ML will be neither a replacement for human ingenuity nor a panacea for cybersecurity’s most vexing problems.

Nevertheless, hype is the hulking gorilla in the room during any discussion of real-world AI/ML applications. Its strengths and weaknesses are not generally well understood. As a result, it can be tricky to accurately articulate the potential impact of AI/ML on our digital experiences. In this video, VP of Transformation Strategy and Field CTO Sanjit Ganguli explains the practical, tactical AI/ML applications Zscaler employs to protect its users. 

Watch to learn how Zscaler uses one of the internet’s largest datasets (informed by more than 250 billion daily transactions) to train AI/ML algorithms to assist with tasks including:

1. Data classification
2. Application segmentation
3. Performance monitoring
4. Cyber threat mitigation

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