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:
- Data classification
- Application segmentation
- Performance monitoring
- Cyber threat mitigation
What to read next
How AI/ML assists in solving the unsolvable in cybersecurity [podcast]
Predictive analytics and machine learning in cybersecurity: an untapped opportunity for ‘negative’ response time