Dr. Blaine Nelson

Background

  • 1995-1999: Student at Franklin County High School, Frankfort, KY
  • 1999-2003: Undergraduate studies (Computer Science) at the University of South Carolina, Columbia
  • 2003-2010: Research assistant (Computer Science) at the University of California, Berkeley
  • Since March 2011: Post-doc at the Center for Bioinformatics (ZBIT), University of T\übingen

 

Research Interests

  • Computer Security
  • Machine Learning
  • Secure/Robust Machine Learning

 

Recent Activities

Current Projects

  • Investigating robustness of classifiers against adversarial noise.
  • Designing new classifier techniques to be more robust.

 

Publications

  1. Ling Huang, Anthony D. Joseph, Blaine Nelson, Benjamin I. P. Rubinstein, and J. D. Tygar. Adversarial Machine Learning, In Proceedings of the 4th ACM Workshop on Artificial Intelligence and Security, ACM, 21 October 2011. [ pdf | bibtex]
  2. Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, and J. D. Tygar. Classifier Evasion: Models and Open Problems, In Privacy and Security Issues in Data Mining and Machine Learning, volume 6549 of Lecture Notes in Computer Science, 2011, pages 92-98. [ pdf | bibtex]
  3. Marco Barreno, Blaine Nelson, Anthony D. Joseph, and J. D. Tygar. The Security of Machine Learning, In Machine Learning Journal, 81(2), 2010, pp. 121-148. [pdf | bibtex]. (Technical Report: EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2008-43, 2008. [pdf | bibtex])
  4. Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Steven Lee, Satish Rao, Anthony Tran and J. D. Tygar, Near-Optimal Evasion of Convex-Inducing Classifiers, In the Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010), 2010. [pdf | bibtex]
  5. Benjamin I. P. Rubinstein, Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Satish Rao, Nina Taft, and J. D. Tygar, ANTIDOTE: Understanding and Defending against Poisoning of Anomaly Detectors, In the Proceedings of the Internet Measurement Conference (IMC 2009), 2009. [pdf | bibtex]
  6. Benjamin I. P. Rubinstein, Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Satish Rao, Nina Taft, and J. D. Tygar, Stealthy Poisoning Attacks on PCA-based Anomaly Detectors, In ACM SIGMETRICS Performance Evaluation Review, 2009. [pdf | bibtex]
  7. Blaine Nelson, Marco Barreno, Fuching Jack Chi, Anthony D. Joseph, Benjamin I. P. Rubinstein, Udam Saini, Charles Sutton, J. D. Tygar, and Kai Xia. Misleading learners: Co-opting your spam filter, Book chapter in Jeffrey J. P. Tsai and Philip S. Yu (eds.) Machine Learning in Cyber Trust: Security, Privacy, and Reliability, pg. 17-51, 2009. [pdf | bibtex]
  8. Marco Barreno, Peter L. Bartlett, Fuching Jack Chi, Anthony D. Joseph, Blaine Nelson, Benjamin I. P. Rubinstein, Udam Saini, and J. D. Tygar, Open Problems in the Security of Learning, In the Proceedings of the First ACM Workshop on AISec, pg. 19-26, 2008. [pdf | slides | bibtex]
  9. Benjamin I. P. Rubinstein, Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Nina Taft, and J. D. Tygar, Evading Anomaly Detection through Variance Injection Attacks on PCA (Extended Abstract), In the 11th International Symposium on Recent Advances in Intrusion Detection (RAID 2008), pg. 394-395, 2008. Winner of the RAID08 Best Poster Award. [pdf | bibtex]
  10. Benjamin I. P. Rubinstein, Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Nina Taft and J. D. Tygar, Compromising PCA-based Anomaly Detectors for Network-Wide Traffic, EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2008-73, 2008. [pdf | bibtex]
  11. Blaine Nelson, Marco Barreno, Fuching Jack Chi, Anthony D. Joseph, Benjamin I.P. Rubinstein, Udam Saini, Charles Sutton, J. D. Tygar, and Kai Xia, Exploiting Machine Learning to Subvert Your Spam Filter, In the Proceedings of the First USENIX Workshop on Large-Scale Exploits and Emergent Threats (LEET'08), San Francisco, CA, April 15, 2008. [pdf | slides | bibtex]
  12. Blaine Nelson, and Anthony D. Joseph, 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. [pdf | slides | bibtex]
  13. Marco Barreno, Blaine Nelson, Russell Sears, Anthony D. Joseph, and J. D. Tygar, Can Machine Learning Be Secure? (Invited paper) , In the Proceedings of the ACM Symposium on InformAtion, Computer and Communications Security (ASIACCS'06) , Taipei, Taiwan, March, 2006. [pdf | bibtex]

 

Theses

  1. Blaine Nelson, Behavior of Machine Learning Algorithms in Adversarial Environments (PhD dissertation). University of California, Berkeley, Department of EECS technical report UCB/EECS-2010-140. November 23 2010. [pdf | bibtex]
  2. Blaine Nelson, Designing, Implementing, and Analyzing a System for Virus Detection (Master's dissertation) University of California, Berkeley, Department of EECS technical report UCB/EECS-2006-27, March 19 2006. [pdf | bibtex]

 

Address, Phone, Fax, Email

Eberhard-Karls-Universität Tübingen
Wilhelm-Schickard-Institut für Informatik
Lehrstuhl Kognitive Systeme
Sand 1
D - 72076 Tübingen
 
Germany


Email: blaine<DOT>nelson<AT>gmail<DOT>com