| Graph-based malware detection using dynamic analysis B Anderson, D Quist, J Neil, C Storlie, T Lane Journal in computer Virology 7, 247-258, 2011 | 369 | 2011 |
| Machine learning for encrypted malware traffic classification: accounting for noisy labels and non-stationarity B Anderson, D McGrew Proceedings of the 23rd ACM SIGKDD International Conference on knowledge …, 2017 | 283 | 2017 |
| Identifying encrypted malware traffic with contextual flow data B Anderson, D McGrew Proceedings of the 2016 ACM workshop on artificial intelligence and security …, 2016 | 270 | 2016 |
| Deciphering malware’s use of TLS (without decryption) B Anderson, S Paul, D McGrew Journal of Computer Virology and Hacking Techniques 14, 195-211, 2018 | 259 | 2018 |
| Improving malware classification: bridging the static/dynamic gap B Anderson, C Storlie, T Lane Proceedings of the 5th ACM workshop on Security and artificial intelligence …, 2012 | 189 | 2012 |
| Integrating multiple data sources for malware classification BH Anderson, CB Storlie, T Lane US Patent 9,021,589, 2015 | 165 | 2015 |
| OS fingerprinting: New techniques and a study of information gain and obfuscation B Anderson, D McGrew 2017 IEEE Conference on Communications and Network Security (CNS), 1-9, 2017 | 63 | 2017 |
| Analyzing encrypted traffic behavior using contextual traffic data J Kohout, BH Anderson, M Grill, D McGrew, M Kopp, T Pevny US Patent 10,805,338, 2020 | 43 | 2020 |
| Automating reverse engineering with machine learning techniques B Anderson, C Storlie, M Yates, A McPhall Proceedings of the 2014 Workshop on Artificial Intelligent and Security …, 2014 | 42 | 2014 |
| Tls beyond the browser: Combining end host and network data to understand application behavior B Anderson, D McGrew Proceedings of the Internet Measurement Conference, 379-392, 2019 | 41 | 2019 |
| Enhanced telemetry for encrypted threat analytics D McGrew, B Anderson 2016 IEEE 24th international conference on network protocols (ICNP), 1-6, 2016 | 39 | 2016 |
| Leveraging endpoint and network environment inferences for malware traffic classification BH Anderson, M Rehak, D McGrew, M Vejman, T Pevny, M Grill, J Kohout US Patent 10,855,698, 2020 | 37 | 2020 |
| Using a machine learning classifier to assign a data retention priority for network forensics and retrospective detection D McGrew, BH Anderson, KT Reddy, P Patil, DG Wing US Patent 10,257,214, 2019 | 32 | 2019 |
| Stochastic identification of malware with dynamic traces C Storlie, B Anderson, SV Wiel, D Quist, C Hash, N Brown The Annals of Applied Statistics, 1-18, 2014 | 31 | 2014 |
| An automated method for segmenting white matter lesions through multi-level morphometric feature classification with application to lupus M Scully, B Anderson, T Lane, C Gasparovic, V Magnotta, W Sibbitt, ... Frontiers in human neuroscience 4, 1176, 2010 | 29 | 2010 |
| Subroutine based detection of APT malware J Sexton, C Storlie, B Anderson Journal of Computer Virology and Hacking Techniques 12, 225-233, 2016 | 27 | 2016 |
| Malware classification and attribution through server fingerprinting using server certificate data BH Anderson, D McGrew, S Paul, I Nikolaev, M Grill US Patent 10,686,831, 2020 | 25 | 2020 |
| Passive decryption on encrypted traffic to generate more accurate machine learning training data BH Anderson, A Chi, D McGrew, SW Dunlop US Patent 10,536,268, 2020 | 24 | 2020 |
| Bayesian networks with prior knowledge for malware phylogenetics D Oyen, B Anderson, C Anderson-Cook Workshops at the Thirtieth AAAI Conference on Artificial Intelligence, 2016 | 21 | 2016 |
| A study of usability-aware network trace anonymization K Mivule, B Anderson 2015 Science and Information Conference (SAI), 1293-1304, 2015 | 20 | 2015 |
David McGrewCisco SystemsVerified email at cisco.com
