Analyzing Behavioral Features for Email Classification. - Steve Martin; Blaine Nelson; Anil Sewani; Karl Chen; Anthony D. Joseph (CEAS, 2005)

Can machine learning be secure? - Marco Barreno; Blaine Nelson; Russell Sears; Anthony D. Joseph; J. D. Tygar (AsiaCCS, 2006)

Revisiting probabilistic models for clustering with pair-wise constraints. - Blaine Nelson; Ira Cohen (ICML, 2007)

CircuitTSAT: A Solver for Large Instances of the Disjunctive Temporal Problem. - Blaine Nelson; T. K. Satish Kumar (ICAPS, 2008)

Open problems in the security of learning. - Marco Barreno; Peter L. Bartlett; Fuching Jack Chi; Anthony D. Joseph; Blaine Nelson; Benjamin I. P. Rubinstein; Udam Saini; J. Doug Tygar (AISec, 2008)

Exploiting Machine Learning to Subvert Your Spam Filter. - Blaine Nelson; Marco Barreno; Fuching Jack Chi; Anthony D. Joseph; Benjamin I. P. Rubinstein; Udam Saini; Charles Sutton; J. Doug Tygar; Kai Xia (LEET, 2008)

Evading Anomaly Detection through Variance Injection Attacks on PCA. - Benjamin I. P. Rubinstein; Blaine Nelson; Ling Huang 001; Anthony D. Joseph; Shing-hon Lau; Nina Taft; J. Doug Tygar (RAID, 2008)

ANTIDOTE: understanding and defending against poisoning of anomaly detectors. - Benjamin I. P. Rubinstein; Blaine Nelson; Ling Huang 001; Anthony D. Joseph; Shing-hon Lau; Satish Rao; Nina Taft; J. D. Tygar (Internet Measurement Conference, 2009)

Stealthy poisoning attacks on PCA-based anomaly detectors. - Benjamin I. P. Rubinstein; Blaine Nelson; Ling Huang 001; Anthony D. Joseph; Shing-hon Lau; Satish Rao; Nina Taft; J. D. Tygar (SIGMETRICS Perform. Evaluation Rev., 2009)

Classifier Evasion: Models and Open Problems. - Blaine Nelson; Benjamin I. P. Rubinstein; Ling Huang 001; Anthony D. Joseph; J. D. Tygar (PSDML, 2010)

Near-Optimal Evasion of Convex-Inducing Classifiers. - Blaine Nelson; Benjamin I. P. Rubinstein; Ling Huang 001; Anthony D. Joseph; Shing-hon Lau; Steven J. Lee; Satish Rao; Anthony Tran; J. Doug Tygar (AISTATS, 2010)

The security of machine learning. - Marco Barreno; Blaine Nelson; Anthony D. Joseph; J. D. Tygar (Mach. Learn., 2010)

Behavior of Machine Learning Algorithms in Adversarial Environments. - Blaine Nelson (2010)

Adversarial machine learning. - Ling Huang 001; Anthony D. Joseph; Blaine Nelson; Benjamin I. P. Rubinstein; J. D. Tygar (AISec, 2011)

Understanding the risk factors of learning in adversarial environments. - Blaine Nelson; Battista Biggio; Pavel Laskov (AISec, 2011)

Support Vector Machines Under Adversarial Label Noise. - Battista Biggio; Blaine Nelson; Pavel Laskov (ACML, 2011)

Microbagging Estimators: An Ensemble Approach to Distance-weighted Classifiers. - Blaine Nelson; Battista Biggio; Pavel Laskov (ACML, 2011)

Fifth ACM workshop on artificial intelligence and security (AISec 2012). - Alvaro A. Cárdenas; Blaine Nelson; Benjamin I. P. Rubinstein (CCS, 2012)

Poisoning Attacks against Support Vector Machines. - Battista Biggio; Blaine Nelson; Pavel Laskov (ICML, 2012)

Machine Learning Methods for Computer Security (Dagstuhl Perspectives Workshop 12371). - Anthony D. Joseph; Pavel Laskov; Fabio Roli; J. Doug Tygar; Blaine Nelson (Dagstuhl Reports, 2012)

Query Strategies for Evading Convex-Inducing Classifiers. - Blaine Nelson; Benjamin I. P. Rubinstein; Ling Huang 001; Anthony D. Joseph; Steven J. Lee; Satish Rao; J. D. Tygar (J. Mach. Learn. Res., 2012)

Summary/overview for artificial intelligence and security (AISec'13). - Blaine Nelson; Christos Dimitrakakis; Elaine Shi (CCS, 2013)

Evasion Attacks against Machine Learning at Test Time. - Battista Biggio; Igino Corona; Davide Maiorca; Blaine Nelson; Nedim Srndic; Pavel Laskov; Giorgio Giacinto; Fabio Roli (ECML/PKDD (3), 2013)

Robust, Secure and Private Bayesian Inference. - Christos Dimitrakakis; Blaine Nelson; Aikaterini Mitrokotsa; Benjamin I. P. Rubinstein (CoRR, 2013)

Robust and Private Bayesian Inference. - Christos Dimitrakakis; Blaine Nelson; Aikaterini Mitrokotsa; Benjamin I. P. Rubinstein (ALT, 2014)

Security Evaluation of Support Vector Machines in Adversarial Environments. - Battista Biggio; Igino Corona; Blaine Nelson; Benjamin I. P. Rubinstein; Davide Maiorca; Giorgio Fumera; Giorgio Giacinto; Fabio Roli (CoRR, 2014)

Support vector machines under adversarial label contamination. - Huang Xiao; Battista Biggio; Blaine Nelson; Han Xiao 002; Claudia Eckert 001; Fabio Roli (Neurocomputing, 2015)

Differential Privacy for Bayesian Inference through Posterior Sampling. - Christos Dimitrakakis; Blaine Nelson; Zuhe Zhang; Aikaterini Mitrokotsa; Benjamin I. P. Rubinstein (J. Mach. Learn. Res., 2017)

Tree of Attacks: Jailbreaking Black-Box LLMs Automatically. - Anay Mehrotra; Manolis Zampetakis; Paul Kassianik; Blaine Nelson; Hyrum S. Anderson; Yaron Singer; Amin Karbasi (NeurIPS, 2024)

Extracting Memorized Training Data via Decomposition. - Ellen Su; Anu Vellore; Amy Chang; Raffaele Mura; Blaine Nelson; Paul Kassianik; Amin Karbasi (CoRR, 2024)

Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report. - Paul Kassianik; Baturay Saglam; Alexander Chen; Blaine Nelson; Anu Vellore; Massimo Aufiero; Fraser Burch; Dhruv Kedia; Avi Zohary; Sajana Weerawardhena; Aman Priyanshu; Adam Swanda; et al. (CoRR, 2025)

Large Language Models Encode Semantics in Low-Dimensional Linear Subspaces. - Baturay Saglam; Paul Kassianik; Blaine Nelson; Sajana Weerawardhena; Yaron Singer; Amin Karbasi (CoRR, 2025)

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report. - Sajana Weerawardhena; Paul Kassianik; Blaine Nelson; Baturay Saglam; Anu Vellore; Aman Priyanshu; Supriti Vijay; Massimo Aufiero; Arthur Goldblatt; Fraser Burch; Ed Li; Jianliang He; et al. (CoRR, 2025)