AI for API Security: Field-Tested Insights from Cequence.ai Co-Founder Shreyans Mehta

Cyber Sentries: AI Insight to Cloud Security · 2024-02-14 · 30 min

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Topics in this episode

Cloud security AI security Shreyans Mehta cequence.ai

Episode notes

John sits down with Shreyans Mehta, CTO and co-founder of Cequence Security, to discuss how AI and machine learning can be applied to improve cloud security. They provide valuable insights for security teams looking to leverage AI to protect their cloud environments and applications. The conversation focuses on using AI for security use cases like detecting anomalies and suspicious behavior, identifying misconfigurations, and automating response. Shreyans shares real-world examples of how Cequence Security has developed AI models to analyze network traffic, APIs, logs, and other data sources to detect threats targeting cloud applications and infrastructure. Questions we answer in this episode: How can AI improve visibility across cloud environments? What are some common use cases for AI in cloud security? How can AI help overburdened security teams? Key Takeaways: AI excels at detecting subtle anomalies and identifying emerging threats based on learned patterns. AI models must be continuously trained on new data to remain effective as attacks evolve. AI augments human analysts by automating tedious tasks so they can focus on higher-value security activities.