Deep dives into machine learning, security analytics, AI, and cybersecurity.
Presenting BNY Mellon's flagship innovation using Retrieval-Augmented Generation (RAG) to accelerate security rule development, redundancy detection, and threat intelligence automation.
Comprehensive guide to building ML capabilities at BlockFi from scratch, covering team structure, executive buy-in, blockchain analytics, and operational ML for crypto security.
Showcasing BlockFi's use of Splunk and machine learning for cryptocurrency security, including anomaly detection, fraud identification, and graph analytics for blockchain analysis.
Step-by-step guide to building custom Docker containers for Splunk DLTK, including creating a Nvidia Rapids container for GPU-accelerated machine learning.
Overview of ML & AI concepts for security analysts, with practical walkthroughs of ransomware and botnet detection using machine learning.
Complete guide to integrating Jupyter Notebook with Splunk Enterprise using Docker, enabling data science workflows directly with Splunk data and the ML Toolkit.
Complete guide to setting up Splunk ML Toolkit development environments using Docker, including automated app installation and configuration.
Exploring the journey from reactive to prescriptive analytics in security operations, covering the advanced analytics maturity model and ML-driven incident response automation.
Deep dive on SPL patterns for security use cases, covering tstats command optimization, data model acceleration, and tried-and-tested query patterns for threat detection.
Webinar defining AI and machine learning in cybersecurity context, with practical applications for speeding incident response and optimizing security staff resources.
Practical machine learning techniques for botnet detection using Suricata data, covering data exfiltration, traffic analysis, and advanced threat detection workflows.
Hands-on workshop teaching security practitioners how to build operational Splunk apps, covering methodology, data enrichment, visualization, and machine learning techniques.
Step-by-step guide to integrating Mapbox API with Splunk for enhanced geographical visualizations, including custom tiles and the Missile Map visualization.
Security analysis of the Shadow Brokers NSA tool leak and its impact on enterprise security, with Splunk-based detection strategies.
Step-by-step guide to integrating abuse.ch's ransomware intelligence feed into Splunk Enterprise Security for enhanced threat detection and response.
Using Splunk's Machine Learning Toolkit and Suricata data to analyze and predict Mirai botnet activity through K-means clustering and Random Forest classification.
Keynote presentation on applying machine learning toolkits to Suricata data for threat detection, covering data exfiltration, port analysis, and advanced threat use cases.
Conference presentation on machine learning toolkits in Splunk for security practitioners, covering anomaly detection, data exfiltration, and advanced threat use cases.