The WAF Said Nothing. The IDS Said Nothing. The ML Model Said "Block This." Here's How We Built That
Traditional signature-based tools fail against zero-day attacks. We built a behavioral anomaly detection system using AWS Lambda, SageMaker, and API Gateway for our Java microservices. Results: 94% accuracy on known attacks, 78% zero-day detection, sub-100ms latency. This article covers feature engineering, model training with Random Cut Forest, real-time response automation, and lessons on false positive tuning. Includes code examples for telemetry emission, Lambda authorizers, and deployment architecture. Read All
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The WAF Said Nothing. The IDS Said Nothing. The ML Model Said "Block This." Here's How We Built That
byRamyabyRamya@ramyav
Lead Java Software Engineer specializing in healthcare technology, building HIPAA-compliant, event-driven, cloud-native
SubscribeMarch 21st, 2026
audio element.Speed1xVoiceDr. One Ms. Hacker byRamya@ramyavbyRamya@ramyavLead Java Software Engineer specializing in healthcare technology, building HIPAA-compliant, event-driven, cloud-native
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Lead Java Software Engineer specializing in healthcare technology, building HIPAA-compliant, event-driven, cloud-native
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cybersecurity#zero-day-attacks#cybersecurity#java#aws-lambda#machine-learning#microservices#cloud-security#artificial-intelligence
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