Akamai researchers developed a hybrid CNN-BiLSTM-Attention deep learning framework for real-time detection of Domain Generation Algorithms (DGAs) used by modern malware for resilient C2 communications. The approach specifically targets dictionary-based DGAs that generate human-readable domains mimicking legitimate traffic, which traditional static defenses and entropy-based detection methods fail to identify. The framework incorporates adaptive retraining strategies to counter concept drift as DGA techniques evolve.
Machine Learning
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Adaptive AI for Detecting Modern DGA Attacks Machine Learning Operations: Yesterday, Today, and Tomorrow Akamai details its internal Machine Learning Operations (MLOps) platform, highlighting the transition from manual model management to a standardized, Kubeflow-based infrastructure. The platform enhances real-time security detections by streamlining model evaluation, tuning, and deployment, and is currently evolving to support LLMOps and AgentOps for generative AI applications.