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Many interesting applications of machine learning arise from problems in computer systems and security. At UCSD these problems often spark collaborations between researchers in the AI and Systems and Networking groups. The following are examples of projects in this space:
Profiling the online storefronts of counterfeit merchandise
[IMC-14] [KDD-14]Detecting malicious web sites: a case study in adversarial classification
[AISEC-11] [TIST-11] [ICML-09] [KDD-09]Topic models of the underground Internet economy
[ICML-13] [AISEC-11]Learning to rate vulnerabilities and predict exploits
[KDD-10]
Publications
S. Hill, Z. Zhou, L. Saul, and H. Shacham (2016). On the (in)effectiveness of mosaicing and blurring as tools for document redaction. In Proceedings of the 16th Privacy Enhancing Technologies Symposium(PETS-16), pages 404-418. Darmstadt, Germany.
S. Liu, I. Foster, S. Savage, G. M. Voelker, and L. K. Saul (2015). Who is .com? Learning to Parse WHOIS Records. In Proceedings of the ACM Internet Measurement Conference (IMC-15), pages 369-380. Tokyo, Japan.
T. Halvorson, M. F. Der, I. Foster, S. Savage, L. K. Saul, and G. M. Voelker (2015). From .academy to .zone: An Analysis of the New TLD Land Rush. In Proceedings of the ACM Internet Measurement Conference (IMC-15), pages 381-394. Tokyo, Japan.
D. Wang, M. F. Der, M. Karami, L. K. Saul, D. McCoy, S. Savage, G. M. Voelker (2014). Search and seizure: the effectiveness of interventions on SEO campaigns. In Proceedings of the 2014 Internet Measurement Conference (IMC-14), pages 359-372. Vancouver, BC, Canada.
M. F. Der, L. K. Saul, S. Savage, and G. M. Voelker (2014). Knock it off: profiling the online storefronts of counterfeit merchandise. In Proceedings of the Twentieth ACM Conference on Knowledge Discovery and Data Mining (KDD-14), pages 1759-1768. New York, NY.
D.-K. Kim, G. M. Voelker, and L. K. Saul (2013). A variational approximation for topic modeling of hierarchical corpora. To appear in Proceedings of the 30th International Conference on Machine Learning (ICML-13). Atlanta, GA.
X. Ma, P. Huang, X. Jin, P. Wang, S. Park, D. Shen, Y. Zhou, L. K. Saul, and G. M. Voelker (2013). eDoctor: automatically diagnosing abnormal battery drain issues on smartphones. In Proceedings of the 10th ACM/USENIX Symposium on Networked Systems Design and Implementation (NSDI-13). Lombard, IL.
S. N. Bannur, L. K. Saul, and S. Savage (2011). Judging a site by its content: learning the textual, structural, and visual features of malicious Web pages. In Proceedings of the 4th ACM Workshop on Artificial Intelligence and Security (AISEC-11), pages 1-10. Chicago, IL.
D.-K. Kim, M. Motoyama, G. M. Voelker, and L. K. Saul (2011). Topic modeling of freelance job postings to monitor web service abuse. In Proceedings of the 4th ACM Workshop on Artificial Intelligence and Security (AISEC-11), pages 11-20. Chicago, IL.
J. T. Ma, L. K. Saul, S. Savage, and G. M. Voelker (2011). Learning to detect malicious URLs. ACM Transactions on Intelligent Systems and Technology 2(3), pages 30:1-24.
M. Bozorgi, L. K. Saul, S. Savage, and G. M. Voelker (2010). Beyond heuristics: learning to classify vulnerabilities and predict exploits. In Proceedings of the Sixteenth ACM Conference on Knowledge Discovery and Data Mining (KDD-10), pages 105-113. Washington, DC.
D. J. Hu, L. van der Maaten, Y. Cho, L. K. Saul, and S. Lerner (2010). Latent variable models for predicting file dependencies in large-scale software development. In J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel, and A. Culotta (eds.), Advances in Neural Information Processing Systems 23, pages 865-873.
J. Ma, L. K. Saul, S. Savage, and G. M. Voelker (2009). Identifying suspicious URLs: an application of large-scale online learning. In Proceedings of the Twenty Sixth International Conference on Machine Learning (ICML-09), pages 681-688. Montreal, Canada.
J. Ma, L. K. Saul, S. Savage, and G. M. Voelker (2009). Beyond blacklists: learning to detect malicious web sites from suspicious URLs. In Proceedings of the Fifthteenth ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-09), pages 1245-1253. Paris, France.