I am a Staff Engineer at Canonical where I work on a variety of open source things.
I am interested in a broad range of security topics. Most recently, I have focused on building systems that are resilient to attack using a range of techniques, including trusted computing and data provenance. You can find more information about my research and teaching interests on others pages on this site.
Prior to joinging Canonical I was an assistant professor in the Department of Software and Information Systems at the University of North Carolina at Charlotte.
Prior to joining the faculty at UNCC, I was a research scientist at MIT Lincoln Laboratory in the Secure Resilient Systems and Technology Group working with a number of incredibly talented people. While there, I worked on a range of topics related to computer and network defense.
Prior to joining the lab, I received my Ph.D. in Computer Science and Engineering from The Pennsylvania State University from the Computer Science and Engineering Department. I was a member of the Systems and Internet Infrastructure Security Lab where I was advised by Professor Patrick McDaniel. My dissertation focused on building high-integrity systems at scale. I also received my M.S. in Computer Science and Engineering and my B.S. in Computer Engineering from Penn State.
Dec 22, 2022
Our paper titled “Deep Packet Inspection at Scale: Search Optimization Through Locality-Sensitive Hashing” received the best paper award from IEEE International Symposium on Network Computing and Applications (NCA 2022).
Nov 29, 2022
Our paper titled “Deep Packet Inspection at Scale: Search Optimization Through Locality-Sensitive Hashing” was accepted at the IEEE International Symposium on Network Computing and Applications (NCA 2022).
Oct 3, 2022
I have started a new position as a Staff Engineer with Canonical.
Oct 1, 2022
Our paper titled “Detecting VoIP Data Streams: Approaches Using Hidden Representation Learning” was accepted at the Annual Conference on Innovative Applications of Artificial Intelligence (IAAI 23).
Jul 26, 2022
Our paper titled “Flurry: A Fast Framework for Provenance Graph Generation for Representation Learning” was accepted at the ACM International Conference on Information & Knowledge Management.
Aug 24, 2021
Our paper titled “Prov-GEm: Automated System Provenance Analysis through Graph Embeddings” was accepted at the IEEE International Conference on Machine Learning and Applications.
Jul 29, 2019
Our paper titled “Detecting Safety and Security Faults in PLC Systems with Data Provenance” was accepted at the IEEE International Symposium on Technologies for Homeland Security 2019 in Waltham, MA.
Nov 16, 2018
Our paper titled “IoTC2: A Formal Method Approach for Detecting Conflicts in Large Scale IoT Systems” was accepted at the IFIP/IEEE International Symposium on Integrated Network Management 2019 in Washington DC.
May 15, 2018
Our paper titled “Curator: Provenance Management for Modern Distributed Systems” was accepted at the 10TH USENIX Workshop on the Theory and Practice of Provenance (TaPP), 2018 in London, UK.
Oct 26, 2017
Our paper titled “Towards Scalable Cluster Auditing through Grammatical Inference over Provenance Graphs” was accepted at the 25th Network and Distributed System Security Symposium (NDSS), 2018 in San Diego, CA.