As part of a broader blog post on Google’s approach to AI Security, Phil Venables, CISO for Google Cloud and Royal Hansen, VP Engineering for Privacy, Safety, and Security, shared seven examples of existing Google products that use AI at scale to improve security outcomes:

• Gmail’s AI-powered spam-filtering capabilities block nearly 10 million spam emails every minute. This keeps 99.9% of phishing attempts and malware from reaching your inbox.
• Google’s Safe Browsing, an industry-leading service, uses AI classifiers running directly in the Chrome web browser to warn users about unsafe websites.
• IAM recommender uses AI technologies to analyze usage patterns to recommend more secure IAM policies that are custom tailored to an organization’s environment. Once implemented, they can make cloud deployments more secure and cost-effective, with maximum performance.
• Chronicle Security Operations and Mandiant Automated Defense use integrated reasoning and machine learning to identify critical alerts, suppress false positives, and generate a security event score to help reduce alert fatigue.
• Breach Analytics for Chronicle uses machine learning to calculate a Mandiant IC-Score, a data science-based “maliciousness” scoring algorithm that filters out benign indicators and helps teams focus on relevant, high-priority IOCs. These IOCs are then matched to security data stored in Chronicle to find incidents in need of further investigation.
• reCAPTCHA Enterprise and Web Risk use unsupervised learning models to detect clusters of hijacked and fake accounts to help speed up investigation time for analysts and act to protect accounts, and minimize risk.
• Cloud Armor Adaptive Protection uses machine learning to automatically detect threats at Layer 7, which contributed to detecting and blocking one of the largest DDoS attacks ever reported.