Knowledge Transfer

LLM-PBE: Assessing Data Privacy in Large Language Models

Li, Qinbin, Hong, Junyuan, Xie, Chulin, Tan, Jeffrey, Xin, Rachel, Hou, Junyi, Yin, Xavier, Wang, Zhun, Hendrycks, Dan, Wang, Zhangyang, Li, Bo, He, Bingsheng, Song, Dawn

Proceedings of the VLDB Endowment, 17(11), Pages 3201 - 3214.July 1, 2024

Poster: Brave: Byzantine-resilient and privacy-preserving peer-to-peer federated learning

Xu, Z., Jiang, F., Niu, L., Jia, J., Li, Bo, Poovendran, Radha

In Proceedings of the 19th ACM Asia Conference on Computer and Communications Security (pp. 1934-1936). Singapore

Poster: Double-Dip: Thwarting Label-Only Membership Inference Attacks with Transfer Learning and Randomization

Rajabi, A., Pimple, R., Janardhanan, A., Asokraj, S., Ramasubramanian, B., Poovendran, Radha

ACM Asia Conference on Computer and Communications Security (ACM AsiaCCS), Singapore

Poster: Game of Trojans: Adaptive Adversaries Against Output-based Trojaned-Model Detectors

Sahabandu, D., Xu, X., Rajabi, A., Niu, L., Ramasubramanian, B., Bo, Li, Poovendran, Radha

ACM Asia Conference on Computer and Communications Security (ACM AsiaCCS), SingaporeJuly 1, 2024

An Inclusive Study of Petri Nets and Their Applications

McDuffie, Jasmine, Chenou, Jules

Norfolk State University College of Science, Engineering and Technology. Technical Report No.1. June 30, 2024

Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares

Gavin Brown, Jonathan Hayase, Samuel Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith

To appear in the 37th Annual Conference on Learning Theory (COLT 2024), June 30th-July 3rd, 2024 in Edmonton, Canada.

Defending Membership Inference Attack on Edge using Trusted Execution Environments

Cheng-Yun Yang, Gowri Ramshankar, Sudarshan Nambiar, Evan Miller, Xun Zhang, Nicholas Eliopoulos, Purvish Jajal, Dave Tian, Shuo-Han Chen, Chiy-Ferng Perng, Yung-Hsiang Lu

Poster at Design Automation Conference (DAC 2024), San Francisco, CA, June 23 - 27, 2024

Practical Region-level Attack against Segment Anything Models

Yifan Shen, Zhengyuan Li, Gang Wang

In Proceedings of the IEEE CVPR Workshop on Fair, Data-efficient, and Trusted Computer Vision (TCV), in conjunction with IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), Seattle, WA, June 17-20, 2024

MMSum: A Dataset for Multimodal Summarization and Thumbnail Generation of Videos

Jielin Qiu, Jiacheng Zhu, William Han, Aditesh Kumar, Karthik Mittal, Claire Jin, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Ding Zhao, Bo Li, Lijuan Wang

Computer Vision and Pattern Recognition Conference (CVPR 2024), Seattle, WA, June 17 - 21, 2024

ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous Vehicles.

Jiawei Zhang, Chejian Xu, Bo Li

Computer Vision and Pattern Recognition Conference (CVPR 2024), Seattle, WA, June 17 - 21, 2024

PerAda: Parameter-efficient and generalizable federated learning personalization with guarantees

Chulin Xie, De-An Huang, Wenda Chu, Daguang Xu, Chaowei Xiao, Bo Li, Anima Anandkumar

Computer Vision and Pattern Recognition Conference (CVPR 2024), Seattle, WA, June 17 - 21, 2024

EDC: Effective and Efficient Dialog Comprehension for Dialog State Tracking

Lu, Q., Ramasubramanian, B., Poovendran, Radha

In Proceedings of findings of 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-2024, findings), Mexico City, Mexico

Sentiment Analysis in the Era of Large Language Models: A Reality Check

Wenxuan Zhang, Yue Deng, Bing Liu, Sinno Jialin Pan , Lidong Bing

In Proceedings of findings of 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-2024, findings), Mexico City, Mexico, June 16–21, 2024

ArtPrompt: ASCII art-based jailbreak attacks against aligned LLMs

Jiang, F., Xu, Z., Niu, L., Xiang, Z., Li, Bo, Poovendran, Radha

ICLR Workshop on Secure and Trustworthy Large Language Models (ICLR SeT-LLM), Vienna, Austria

Does It Matter Who Said It? Exploring the Impact of Deepfake-Enabled Profiles On User Perception Towards Disinformation

Margie Ruffin, Haeseung Seo, Aiping Xiong, Gang Wang

In Proceedings of The International AAAI Conference on Web and Social Media (ICWSM), Buffalo, NY, June 3 - 6, 2024

Markov Chain Monte Carlo for Koopman-based Optimal Control

Hespanha, J., Camsari, K.

IEEE Control Systems Letters, vol. 8, pp. 1901-1906

RL-ARNE: A Reinforcement Learning Algorithm for Computing Average Reward Nash Equilibrium of Nonzero Sum Stochastic Games

D. Sahabandu, S. Moothedath, J. Allen, L. Bushnell, W. Lee, Poovendran, Radha

IEEE Transactions on Automatic Control ( Volume: 69, Issue: 11, November 2024), pp. 7824 - 7831

Dynamic Information Flow Tracking for Detection of Advanced Persistent Threats: A Stochastic Game Approach

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

IEEE Transactions on Automatic Control

DOI: 10.1109/TAC.2024.3403675

Trojanpuzzle: Covertly poisoning code-suggestion models

Aghakhani, Hojjat, Dai, Wei, Manoel, Andre, Fernandes, Xavier, Kharkar, Anant, Kruegel, Christopher, Vigna, Giovanni, Evans, David, Zorn, Ben, Sim, Robert

Proceedings of 2024 IEEE Security and Privacy Symposium (S&P 2024) San Francisco, California

Are Adversarial Phishing Webpages a Threat in Reality? Understanding the Users’ Perception of Adversarial Webpages

Ying Yuan, Qingying Hao, Giovanni Apruzzese, Mauro Conti, Gang Wang

In Proceedings of The ACM Web Conference (WWW), Singapore, May 13-17, 2024

It's Trying Too Hard To Look Real: Deepfake Moderation Mistakes and Identity-Based Bias

Jaron Mink, Miranda Wei, Collins W. Munyendo, Kurt Hugenberg, Tadayoshi Kohno, Elissa M. Redmiles, Gang Wang

In Proceedings of ACM CHI Conference on Human Factors in Computing Systems (CHI), Honolulu, HI, May 11-16, 2024
 

Badchain: Backdoor chain-of-thought prompting for large language models

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

In Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024

Effective and Efficient Federated Tree Learning on Hybrid Data

Qinbin Li, Chulin Xie, Xiaojun Xu, Xiaoyuan Liu, Ce Zhang, Bo Li, Bingsheng He, and Dawn Song

In Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria    May 7-11, 2024

COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits.

Mintong Kang, Nezihe Merve Gürel, Linyi Li, Bo Li

In Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria    May 7-11, 2024

GNNX-BENCH: Unravelling the utility of perturbation-based gnn explainers through in-depth benchmarking

Mert Kosan, Samidha Verma, Burouj Armgaan, Khushbu Pahwa, Ambuj Singh, Sourav Medya, Sayan Ranu

In Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria    May 7-11, 2024

Tensor trust: Interpretable prompt injection attacks from an online game

Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong , Karim Elmaaroufi , Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell

In Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024

SafeDecoding: Defending against jailbreak attacks via safety-aware decoding

Xu, Z., Jiang, F., Niu, L., Jia, J., Li, Bo, Poovendran, Radha

ICLR Workshop on Secure and Trustworthy Large Language Models (ICLR SeT-LLM), Vienna, AustriaMay 6, 2024

Generalization Bounds for Magnitude-Based Pruning via Sparse Matrix Sketching

Etash Kumar Guha, Prasanjit Dubey, Xiaoming Huo

In Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024) Workshop Bridging the Gap Between Practice and Theory in Deep Learning (BGPT), Vienna, Austria, May 6 - 11, 2024

Ring-A-Bell! How Reliable are Concept Removal Methods for Diffusion Models?

Yu-Lin Tsai, Chia-Yi Hsu, Chulin Xie, Chih-Hsun Lin, Jia-You Chen, Bo Li, Pin-Yu Chen, Chia-Mu Yu, Chun-Ying Huang

In Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 7-11, 2024
 

Defending against transfer attacks from public models

Chawin Sitawarin , Jaewon Chang, David Huang, Wesson Altoyan, David Wagner

International Conference on Learning Representations (ICLR 2024), Vienna, Austria, May 6-11, 2024