Modeling the effects of insider threats on cybersecurity of complex systems. - Teodora Baluta; Lavanya Ramapantulu; Yong Meng Teo; Ee-Chien Chang (WSC, 2017)

Quantitative Verification of Neural Networks and Its Security Applications. - Teodora Baluta; Shiqi Shen; Shweta Shinde; Kuldeep S. Meel; Prateek Saxena (CCS, 2019)

One Engine To Serve 'em All: Inferring Taint Rules Without Architectural Semantics. - Zheng Leong Chua; Yanhao Wang; Teodora Baluta; Prateek Saxena; Zhenkai Liang; Purui Su (NDSS, 2019)

Private Hierarchical Clustering in Federated Networks. - Aashish Kolluri; Teodora Baluta; Prateek Saxena (CCS, 2021)

Scalable Quantitative Verification For Deep Neural Networks. - Teodora Baluta; Zheng Leong Chua; Kuldeep S. Meel; Prateek Saxena (ICSE, 2021)

SynGuar: guaranteeing generalization in programming by example. - Bo Wang 146; Teodora Baluta; Aashish Kolluri; Prateek Saxena (ESEC/SIGSOFT FSE, 2021)

SynGuar: Guaranteeing Generalization in Programming by Example (Artifact). - Bo Wang 146; Teodora Baluta; Aashish Kolluri; Prateek Saxena (Zenodo, 2021)

Membership Inference Attacks and Generalization: A Causal Perspective. - Teodora Baluta; Shiqi Shen; S. Hitarth; Shruti Tople; Prateek Saxena (CCS, 2022)

LPGNet: Link Private Graph Networks for Node Classification. - Aashish Kolluri; Teodora Baluta; Bryan Hooi; Prateek Saxena (CCS, 2022)

Unforgeability in Stochastic Gradient Descent. - Teodora Baluta; Ivica Nikolic; Racchit Jain; Divesh Aggarwal; Prateek Saxena (CCS, 2023)

Explaining SAT Solving Using Causal Reasoning. - Jiong Yang 002; Arijit Shaw; Teodora Baluta; Mate Soos; Kuldeep S. Meel (SAT, 2023)

User-customizable Transpilation of Scripting Languages. - Bo Wang 146; Aashish Kullori; Ivica Nikolic; Teodora Baluta; Prateek Saxena (CoRR, 2023)

DuoGlot: User-Customizable Transpilation of Scripting Languages (Artifact). - Bo Wang 146; Aashish Kolluri; Ivica Nikolic; Teodora Baluta; Prateek Saxena (Zenodo, 2023)

User-Customizable Transpilation of Scripting Languages. - Bo Wang 146; Aashish Kolluri; Ivica Nikolic; Teodora Baluta; Prateek Saxena (Proc. ACM Program. Lang., 2023)

Unlearning in- vs. out-of-distribution data in LLMs under gradient-based method. - Teodora Baluta; Pascal Lamblin; Daniel Tarlow; Fabian Pedregosa; Gintare Karolina Dziugaite (CoRR, 2024)

Model Provenance Testing for Large Language Models. - Ivica Nikolic; Teodora Baluta; Prateek Saxena (CoRR, 2025)