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
Which Programming Languages Do Hackers Use?
Analyzing the Exploit Database with Python- 28394Murphy ≡ 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 4): Flux Capacitor Design
We implement a Spark structured streaming stateful mapping function to handle temporal proximity correlations in cyber security logs- 23332Murphy ≡ 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
Which GPT-like Engineering Strategies Work on System Logs?
Evaluation of Transformer Neural Network Modeling Methodologies applied to Behavior Malware Traces.- 20585Murphy ≡ DeepGuide
Architecture of AI-Driven Security Operations with a Low False Positive Rate
This article discusses a mindset on building production-ready machine learning solutions when applied to cyber-security needs- 21608Murphy ≡ DeepGuide
Anomaly Detection Using Sigma Rules: Build Your Own Spark Streaming Detections
Easily deploy Sigma rules in Spark streaming pipelines: a future-proof solution supporting the upcoming Sigma 2 specification- 24348Murphy ≡ DeepGuide
Post-Quantum Cryptography with Python and Linux
A beginner's guide- 27209Murphy ≡ DeepGuide
Securing your Containerised Models and Workloads
Containerisation is now the de facto means of deploying many applications, with Docker being the forefront software driving its adoption. With its popularity also comes the increased risk of attacks [1]. Hence it will serve us well to secure our docker ap- 29589Murphy ≡ DeepGuide
Unleashing the Power of SQL Analytical Window Functions: A Deep Dive into Fusing IPv4 Blocks
How to summarize a geolocation table by merging contiguous network IPv4 blocks- 29337Murphy ≡ DeepGuide
Performant IPv4 Range Spark Joins
A Practical guide to optimizing non-equi joins in Spark- 25059Murphy ≡ DeepGuide
Performance Insights from Sigma Rule Detections in Spark Streaming
Utilizing Sigma rules for anomaly detection in cybersecurity logs: A study on performance optimization- 23964Murphy ≡ DeepGuide
Optimizing Sigma Rules in Spark with the Aho-Corasick Algorithm
Extending Spark for improved performance in handling multiple search terms- 26625Murphy ≡ 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