Current Research:

I'm currently working with Anthony Joseph to use statistical machine learning techniques in security sensitive environments that could benefit from adaptive automated techniques; in particular, the crux of this research focuses on identifying virus email traffic. The following are my current research interests:

Security in machine learning: 

In this project, we are studying the effect a malicious user can have on statistical learning techniques used in security sensitive environments.

SAT-based DTP

This project has focused on developing solvers for large instances of Disjunctive Temporal Problems (DTPs) by converting them into a SAT representation.

Clustering with Pairwise Constraints

This project explored the use of pairwise constraints between data points for clustering algorithms. The constraints we considered indicated whether pairs of points belonged to the same cluster or to different clusters. Using these constraints, one is able to better cluster data as has been demonstrated in several image applications. Our contribution was a new sampling algorithm that uses these constraints.

Adaptive Protection Environment

This project uses machine learning techniques to identify viruses in email traffic.

Duke Landmine Detection project

Talks

Here I list the research talks I've given and provide slides.

Conference Talks

  1. Open Problems in the Security of Learning, In the Proceedings of the First ACM Workshop on AISec, pg. 19-26, November, 2008. [slides]
  2. Exploiting Machine Learning to Subvert Your Spam Filter at In the Proceedings of the First USENIX Workshop on Large-Scale Exploits and Emergent Threats (LEET'08), San Francisco, CA, April 15, 2008. [slides | audio]
  3. CircuitTSAT: A Solver for Large Instances of the Disjunctive Temporal Problem, In the Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2008. [slides]
  4. Revisiting Probabilistic Models for Clustering with Constraints, In the Proceedings of the International Conference on Machine Learning (ICML), 2007. [slides]
  5. Bounding an Attack's Complexity for a Simple Learning Model , In the Proceedings of the First Workshop on Tackling Computer Systems Problems with Machine Learning Techniques (SysML) , Saint-Malo, France, June, 2006. [slides]