Graph analysis is a powerful tool for modeling malicious group behavior and detecting anomalies in domains ranging from traffic analysis to fraud detection. This talk will cover techniques and open-source tools for graph analytics, including an end-to-end analysis of a novel application of graph analytics to malware detection: from real data collection to the visualization of results.
Learning Objectives:
1: Receive an introduction to graph analytics.
2: Understand the complete work-flow of a realistic application of graph analytics.
3: Understand limitations and pitfalls of applying graph analytics to a real problem.
Speaker: Mayana Pereira
Mayana Wanderley Pereira has been working in security and security-related fields since she obtained her M.Sc. in cryptography in 2011. For the last years, she has applied graph analytics and machine learning techniques to a range of problems in healthcare, social networks and network security first at the Center for Data Science of the University of Washington and now at Infoblox as a Data Scientist. Her results have resulted in patent applications and publications and presentations in prestigious venues, including the computer journal of the British Computing Society and ACM conferences. Pereira is also experienced in cryptography, anomaly detection and behavioural analytics.
Detailed Presentation:
Comments