Knowledge Transfer

Unifying logic and probability

Stuart Russell

Communications of the ACM, 58(7), 88-97, 2015.

Automatically Evading Classifiers: A Case Study on PDF Malware Classifiers

Weilin Xu, Yanjun Qi, David Evans

Network and Distributed System Security Symposium (NDSS). San Diego, CA. 21-24 February 2016.

Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection

Xiaojun Xu, Chang Liu, Qian Feng, Heng Yin, Le Song, Dawn Song

Proceedings of the 2017 ACM SIGSAC conference on computer and communications security (pp. 363-376).

A Game-Theoretic Approach for Dynamic Information Flow Tracking to Detect Multi-Stage Advanced Persistent Threats

Shana Moothedath, Dinuka Sahabandu, Joey Allen, Andrew Clark, Linda Bushnell, Wenke Lee, Radha Poovendran

IEEE Transactions on Automatic Control, December 2020.

Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries

Fnu Suya, Jianfeng Chi, David Evans, Yuan Tian

In 29th USENIX Security Symposium. Boston, MA. August 12–14, 2020.

Application-Driven Privacy-Preserving Data Publishing with Correlated Attributes

Aria Rezaei, Chaowei Xiao, Jie Gao, Bo Li, Sirajum Munir

Proceedings of the 18th International Conference on Embedded Wireless Systems and Networks (EWSN 2021), February 17-19, 2021.
Received the Best Paper Award.

New Directions in Automated Traffic Analysis

Jordan Holland, Paul Schmitt, Nick Feamster, Prateek Mittal

In ACM Conference on Computer and Communications Security (CCS).

DeepReflect: Discovering Malicious Functionality through Binary Reconstruction

Evan Downing, Kyuhong Park, Yisroel Mirsky, Wenke Lee

In Proceedings of the 2021 USENIX Security Symposium.

ATLAS: A Sequence-based Learning Approach for Attack Investigation

Abdulellah Alsaheel , Yuhong Nan, Shiqing Ma, Le Yu, Gregory Walkup, Z. Berkay Celik, Xiangyu Zhang, Dongyan Xu

Proceedings of the 30th USENIX Security Symposium.

An Efficient One-Class SVM for Novelty Detection in IoT

Kun Yang, Samory Kpotufe, Nick Feamster

Transactions on Machine Learning Research, 11(2022).

Agent-Temporal Attention for Reward Redistribution in Episodic MultiAgent Reinforcement Learning

Baicen Xiao, Bhaskar Ramasubramanian, Radha Poovendran

Proc. of the 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022), Online, May 2022.

A Theoretical Study on Solving Continual Learning

Gyuhak Kim, Changnan Xiao, Tatsuya Konishi, Zixuan Ke, Bing Liu

Proceedings of Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS-2022), Nov. 28 - Dec. 9, 2022.

Co-evolution of Opinion and Social Tie Dynamics Towards Structural Balance

Haotian Wang, Feng Luo, Jie Gao

Proceedings of the ACM-SIAM Symposium on Discrete Algorithms (SODA’22), 3362-3388, January 9 – 12, 2022.

DEEPCASE: Semi-Supervised Contextual Analysis of Security Events

Thijs Ede, Hojjat Aghakhani, Noah Spahn, Riccardo Bortolameotti, Marco Cova, Andrea Continella, Maarten Steen, Andreas Peter, Christopher Kruegel, Giovanni Vigna

Proceedings of the IEEE Symposium on Security and Privacy (SP), San Francisco, CA.

Cognitive Bias-Aware Dissemination Strategies for Opinion Dynamics with External Information Sources

Abdullah Al Maruf, Luyao Niu, Bhaskar Ramasubramanian, Andrew Clark, Radha Poovendran

22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023), May 2023.

Continual Learning of Language Models

Zixuan Ke, Yijia Shao, Haowei Lin, Tatsuya Konishi, Gyuhak Kim, Bing Liu

To appear in Proceedings of The Eleventh International Conference on Learning Representations (ICLR-2023), Kigali Rwanda, Mon May 1 - Fri May 5 2023.

Adversarial Policies Beat Superhuman Go AIs

Tony T. Wang, Adam Gleave, Tom Tseng, Nora Belrose, Kellin Pelrine, Joseph Miller, Michael D Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell

February 18, 2023

Watch Out for Updates: Understanding the Effects of Model Explanation Updates in AI-Assisted Decision Making

Xinru Wang, Ming Yin

Proceedings of ACM CHI'23, 2023.

Identifying and Mitigating Vulnerabilities in LLM-Integrated Applications

Fengqing Jiang, Zhangchen Xu, Luyao Niu, Boxin Wang, Jinyuan Jia, Bo Li, Radha Poovendran

Published at NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following, December 2023.

Watch Out for Updates: Understanding the Effects of Model Explanation Updates in AI-Assisted Decision Making

Xinru Wang, Ming Yin

Proceedings of ACM CHI'23, Hamburg, Germany.

VulChecker: Graph-based Vulnerability Localization in Source Code

Yisroel Mirsky, George Macon, Michael Brown, Carter Yagemann , Matthew Pruett, Evan Downing, Sukarno Mertoguno, Wenke Lee

In Proceedings of the 2023 USENIX Security Symposium. (to appear)

BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models

Zhen Xiang, Fengqing Jiang, Bhaskar Ramasubramanian, Radha Poovendran, Bo Li

Published at NeurIPS 2023 Workshop on Backdoors in Deep Learning- The Good, The Bad, and the Ugly, December 2023.

DGCluster: A Neural Framework for Attributed Graph Clustering via Modularity Maximization

Aritra Bhowmick, Mert Kosan, Zexi Huang, Ambuj Singh, Sourav Medya

To appear in the 38th Annual AAAI Conference on Artificial Intelligence. Feb 20-27, 2024, Vancouver, Canada.