Anomaly Detection using Sigma Rules (Part 1): Leveraging Spark SQL Streaming
Sigma rules are used to detect anomalies in cyber security logs. We use Spark structured streaming to evaluate Sigma rules at scale.- 24858Murphy ≡ DeepGuide
Anomaly Detection using Sigma Rules (Part 3) Temporal Correlation Using Bloom Filters
Can a custom tailor made stateful mapping function based on bloom filters outperform the generic Spark stream-stream join?- 29937Murphy ≡ DeepGuide
Anomaly Detection using Sigma Rules (Part 5) Flux Capacitor Optimization
To boost performance, we implement a forgetful bloom filter and a custom Spark state store provider- 23388Murphy ≡ DeepGuide
Optimizing Sigma Rules in Spark with the Aho-Corasick Algorithm
Extending Spark for improved performance in handling multiple search terms- 26625Murphy ≡ DeepGuide
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