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.- 24795Murphy ≡ 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?- 29885Murphy ≡ 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- 23345Murphy ≡ DeepGuide
Optimizing Sigma Rules in Spark with the Aho-Corasick Algorithm
Extending Spark for improved performance in handling multiple search terms- 26584Murphy ≡ DeepGuide
We look at an implementation of the HyperLogLog cardinality estimati
Using clustering algorithms such as K-means is one of the most popul
Level up Your Data Game by Mastering These 4 Skills
Learn how to create an object-oriented approach to compare and evalu
When I was a beginner using Kubernetes, my main concern was getting
Tutorial and theory on how to carry out forecasts with moving averag