Jason Trost is the VP of Threat Research at Anomali, Inc. and leads Anomali Labs, the research team. He has worked in security for more than ten years, and he has several years of experience leveraging big data technologies for security data mining and analytics. He is deeply interested in network security, DFIR, honeypots, big data and machine learning. He is currently focused on building highly scalable systems for processing, analyzing, and visualizing high speed network/security events in real-time as well as systems for analyzing massive amounts of malware. He is a regular attendee of Big Data and security conferences, and he has spoken at Blackhat, SANS CTI Summit, BSidesSF, BSidesLV, BSidesDC, BSidesNYC, FloCon, and Hadoop Summit. He has contributed to several security and big data related open source projects including the Modern Honey Network (MHN), BinaryPig, ElasticSearch, Apache Accumulo, and Apache Storm. He has held senior technical positions with the U.S. Department of Defense, Booz Allen Hamilton, and Endgame Inc.