Ahmed Salem

According to our database, Ahmed Salem authored at least 41 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

A Representation Engineering Perspective on the Effectiveness of Multi-Turn Jailbreaks.

Blake Bullwinkel, Mark Russinovich, Ahmed Salem, Santiago Zanella-Béguelin, Daniel Jones, Giorgio Severi, Eugenia Kim, Keegan Hines, Amanda J. Minnich, Yonatan Zunger, Ram Shankar Siva Kumar

CoRR, July, 2025

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs.

Yanan Cai, Ahmed Salem, Besmira Nushi, Mark Russinovich

CoRR, June, 2025

LLMail-Inject: A Dataset from a Realistic Adaptive Prompt Injection Challenge.

Sahar Abdelnabi, Aideen Fay, Ahmed Salem, Egor Zverev, Kai-Chieh Liao, Chi-Huang Liu, Chun-Chih Kuo, Jannis Weigend, Danyael Manlangit, Alex Apostolov, Haris Umair, João Donato, Masayuki Kawakita, Athar Mahboob, Tran Huu Bach, Tsun-Han Chiang, Myeongjin Cho, Hajin Choi, Byeonghyeon Kim, Hyeonjin Lee, Benjamin Pannell, Conor McCauley, Mark Russinovich, Andrew Paverd, Giovanni Cherubin

CoRR, June, 2025

Securing AI Agents with Information-Flow Control.

Manuel Costa, Boris Köpf, Aashish Kolluri, Andrew Paverd, Mark Russinovich, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin

CoRR, May, 2025

Linear Control of Test Awareness Reveals Differential Compliance in Reasoning Models.

Sahar Abdelnabi, Ahmed Salem

CoRR, May, 2025

Jailbreaking is (Mostly) Simpler Than You Think.

Mark Russinovich, Ahmed Salem

CoRR, March, 2025

Obliviate: Efficient Unmemorization for Protecting Intellectual Property in Large Language Models.

Mark Russinovich, Ahmed Salem

CoRR, February, 2025

Get My Drift? Catching LLM Task Drift with Activation Deltas.

Sahar Abdelnabi, Aideen Fay, Giovanni Cherubin, Ahmed Salem, Mario Fritz, Andrew Paverd

Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2025

2024

The Price of Intelligence: Three risks inherent in LLMs.

Mark Russinovich, Ahmed Salem, Santiago Zanella-Béguelin, Yonatan Zunger

ACM Queue, 2024

Permissive Information-Flow Analysis for Large Language Models.

Shoaib Ahmed Siddiqui, Radhika Gaonkar, Boris Köpf, David Krueger, Andrew Paverd, Ahmed Salem, Shruti Tople, Lukas Wutschitz, Menglin Xia, Santiago Zanella-Béguelin

CoRR, 2024

Vera Verto: Multimodal Hijacking Attack.

Minxing Zhang, Ahmed Salem, Michael Backes, Yang Zhang

CoRR, 2024

Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplification.

Boyang Zhang, Yicong Tan, Yun Shen, Ahmed Salem, Michael Backes, Savvas Zannettou, Yang Zhang

CoRR, 2024

Hey, That's My Model! Introducing Chain & Hash, An LLM Fingerprinting Technique.

Mark Russinovich, Ahmed Salem

CoRR, 2024

SOS! Soft Prompt Attack Against Open-Source Large Language Models.

Ziqing Yang, Michael Backes, Yang Zhang, Ahmed Salem

CoRR, 2024

Are you still on track!? Catching LLM Task Drift with Activations.

Sahar Abdelnabi, Aideen Fay, Giovanni Cherubin, Ahmed Salem, Mario Fritz, Andrew Paverd

CoRR, 2024

Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack.

Mark Russinovich, Ahmed Salem, Ronen Eldan

CoRR, 2024

Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition.

Edoardo Debenedetti, Javier Rando, Daniel Paleka, Silaghi Fineas Florin, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Rui Wen, Ahmed Salem, Giovanni Cherubin, Santiago Zanella-Béguelin, Robin Schmid, Victor Klemm, Takahiro Miki, Chenhao Li, Stefan Kraft, Mario Fritz, Florian Tramèr, Sahar Abdelnabi, Lea Schönherr

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Detection and Attribution of Models Trained on Generated Data.

Ge Han, Ahmed Salem, Zheng Li, Shanqing Guo, Michael Backes, Yang Zhang

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Maatphor: Automated Variant Analysis for Prompt Injection Attacks.

Ahmed Salem, Andrew Paverd, Boris Köpf

CoRR, 2023

Rethinking Privacy in Machine Learning Pipelines from an Information Flow Control Perspective.

Lukas Wutschitz, Boris Köpf, Andrew Paverd, Saravan Rajmohan, Ahmed Salem, Shruti Tople, Santiago Zanella-Béguelin, Menglin Xia, Victor Rühle

CoRR, 2023

Comprehensive Assessment of Toxicity in ChatGPT.

Boyang Zhang, Xinyue Shen, Wai Man Si, Zeyang Sha, Zeyuan Chen, Ahmed Salem, Yun Shen, Michael Backes, Yang Zhang

CoRR, 2023

Last One Standing: A Comparative Analysis of Security and Privacy of Soft Prompt Tuning, LoRA, and In-Context Learning.

Rui Wen, Tianhao Wang, Michael Backes, Yang Zhang, Ahmed Salem

CoRR, 2023

Two-in-One: A Model Hijacking Attack Against Text Generation Models.

Wai Man Si, Michael Backes, Yang Zhang, Ahmed Salem

Proceedings of the 32nd USENIX Security Symposium, 2023

UnGANable: Defending Against GAN-based Face Manipulation.

Zheng Li, Ning Yu, Ahmed Salem, Michael Backes, Mario Fritz, Yang Zhang

Proceedings of the 32nd USENIX Security Symposium, 2023

SoK: Let the Privacy Games Begin! A Unified Treatment of Data Inference Privacy in Machine Learning.

Ahmed Salem, Giovanni Cherubin, David Evans, Boris Köpf, Andrew Paverd, Anshuman Suri, Shruti Tople, Santiago Zanella-Béguelin

Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

Analyzing Leakage of Personally Identifiable Information in Language Models.

Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, Santiago Zanella-Béguelin

Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

Bayesian Estimation of Differential Privacy.

Santiago Zanella-Béguelin, Lukas Wutschitz, Shruti Tople, Ahmed Salem, Victor Rühle, Andrew Paverd, Mohammad Naseri, Boris Köpf, Daniel Jones

Proceedings of the International Conference on Machine Learning, 2023

2022

Adversarial inference and manipulation of machine learning models.

Ahmed Salem

PhD thesis, 2022

ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models.

Yugeng Liu, Rui Wen, Xinlei He, Ahmed Salem, Zhikun Zhang, Michael Backes, Emiliano De Cristofaro, Mario Fritz, Yang Zhang

Proceedings of the 31st USENIX Security Symposium, 2022

Get a Model! Model Hijacking Attack Against Machine Learning Models.

Ahmed Salem, Michael Backes, Yang Zhang

Proceedings of the 29th Annual Network and Distributed System Security Symposium, 2022

Dynamic Backdoor Attacks Against Machine Learning Models.

Ahmed Salem, Rui Wen, Michael Backes, Shiqing Ma, Yang Zhang

Proceedings of the 7th IEEE European Symposium on Security and Privacy, 2022

2021

MLCapsule: Guarded Offline Deployment of Machine Learning as a Service.

Lucjan Hanzlik, Yang Zhang, Kathrin Grosse, Ahmed Salem, Maximilian Augustin, Michael Backes, Mario Fritz

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements.

Xiaoyi Chen, Ahmed Salem, Dingfan Chen, Michael Backes, Shiqing Ma, Qingni Shen, Zhonghai Wu, Yang Zhang

Proceedings of the ACSAC '21: Annual Computer Security Applications Conference, Virtual Event, USA, December 6, 2021

2020

Don't Trigger Me! A Triggerless Backdoor Attack Against Deep Neural Networks.

Ahmed Salem, Michael Backes, Yang Zhang

CoRR, 2020

BAAAN: Backdoor Attacks Against Autoencoder and GAN-Based Machine Learning Models.

Ahmed Salem, Yannick Sautter, Michael Backes, Mathias Humbert, Yang Zhang

CoRR, 2020

BadNL: Backdoor Attacks Against NLP Models.

Xiaoyi Chen, Ahmed Salem, Michael Backes, Shiqing Ma, Yang Zhang

CoRR, 2020

Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning.

Ahmed Salem, Apratim Bhattacharya, Michael Backes, Mario Fritz, Yang Zhang

Proceedings of the 29th USENIX Security Symposium, 2020

2019

Privacy-Preserving Similar Patient Queries for Combined Biomedical Data.

Ahmed Salem, Pascal Berrang, Mathias Humbert, Michael Backes

Proc. Priv. Enhancing Technol., 2019

ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models.

Ahmed Salem, Yang Zhang, Mathias Humbert, Pascal Berrang, Mario Fritz, Michael Backes

Proceedings of the 26th Annual Network and Distributed System Security Symposium, 2019

MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples.

Jinyuan Jia, Ahmed Salem, Michael Backes, Yang Zhang, Neil Zhenqiang Gong

Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019

2018

ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models.

Ahmed Salem, Yang Zhang, Mathias Humbert, Mario Fritz, Michael Backes

CoRR, 2018