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2020 – today
- 2024
[j2]Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao
, Nicolas Papernot, Ross J. Anderson, Yarin Gal:
AI models collapse when trained on recursively generated data. Nat. 631(8022): 755-759 (2024)- [j1]Anvith Thudi, Ilia Shumailov, Franziska Boenisch, Nicolas Papernot:
From Differential Privacy to Bounds on Membership Inference: Less can be More. Trans. Mach. Learn. Res. 2024 (2024) - [c35]Sierra Calanda Wyllie, Ilia Shumailov, Nicolas Papernot:
Fairness Feedback Loops: Training on Synthetic Data Amplifies Bias. FAccT 2024: 2113-2147 - [c34]David Glukhov, Ilia Shumailov, Yarin Gal, Nicolas Papernot, Vardan Papyan:
Position: Fundamental Limitations of LLM Censorship Necessitate New Approaches. ICML 2024 - [c33]Eleanor Clifford, Ilia Shumailov, Yiren Zhao, Ross J. Anderson, Robert D. Mullins:
ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks. SaTML 2024: 344-357 - [c32]Pranav Dahiya, Ilia Shumailov, Ross Anderson:
Machine Learning needs Better Randomness Standards: Randomised Smoothing and PRNG-based attacks. USENIX Security Symposium 2024 - [c31]Anvith Thudi, Hengrui Jia, Casey Meehan, Ilia Shumailov, Nicolas Papernot:
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD. USENIX Security Symposium 2024 - [i54]Jamie Hayes, Ilia Shumailov, Itay Yona:
Buffer Overflow in Mixture of Experts. CoRR abs/2402.05526 (2024) - [i53]Harry Langford, Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Nicolas Papernot:
Architectural Neural Backdoors from First Principles. CoRR abs/2402.06957 (2024) - [i52]Jamie Hayes, Ilia Shumailov, Eleni Triantafillou, Amr Khalifa, Nicolas Papernot:
Inexact Unlearning Needs More Careful Evaluations to Avoid a False Sense of Privacy. CoRR abs/2403.01218 (2024) - [i51]Sierra Calanda Wyllie, Ilia Shumailov, Nicolas Papernot:
Fairness Feedback Loops: Training on Synthetic Data Amplifies Bias. CoRR abs/2403.07857 (2024) - [i50]Eleanor Clifford, Adhithya Saravanan, Harry Langford, Cheng Zhang, Yiren Zhao, Robert D. Mullins, Ilia Shumailov, Jamie Hayes:
Locking Machine Learning Models into Hardware. CoRR abs/2405.20990 (2024) - [i49]Hanna Foerster, Robert D. Mullins, Ilia Shumailov, Jamie Hayes:
Beyond Slow Signs in High-fidelity Model Extraction. CoRR abs/2406.10011 (2024) - [i48]Aneesh Pappu, Billy Porter, Ilia Shumailov, Jamie Hayes:
Measuring memorization in RLHF for code completion. CoRR abs/2406.11715 (2024) - [i47]Ilia Shumailov, Jamie Hayes, Eleni Triantafillou, Guillermo Ortiz-Jiménez, Nicolas Papernot, Matthew Jagielski, Itay Yona, Heidi Howard, Eugene Bagdasaryan:
UnUnlearning: Unlearning is not sufficient for content regulation in advanced generative AI. CoRR abs/2407.00106 (2024) - [i46]David Glukhov, Ziwen Han, Ilia Shumailov, Vardan Papyan, Nicolas Papernot:
A False Sense of Safety: Unsafe Information Leakage in 'Safe' AI Responses. CoRR abs/2407.02551 (2024) - [i45]Sahra Ghalebikesabi, Eugene Bagdasaryan, Ren Yi, Itay Yona, Ilia Shumailov, Aneesh Pappu, Chongyang Shi, Laura Weidinger, Robert Stanforth, Leonard Berrada, Pushmeet Kohli, Po-Sen Huang, Borja Balle:
Operationalizing Contextual Integrity in Privacy-Conscious Assistants. CoRR abs/2408.02373 (2024) - 2023
- [c30]Yulin Zhou, Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Yarin Gal:
Revisiting Automated Prompting: Are We Actually Doing Better? ACL (2) 2023: 1822-1832 - [c29]Mikel Bober-Irizar, Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Nicolas Papernot:
Architectural Backdoors in Neural Networks. CVPR 2023: 24595-24604 - [c28]Cheng Zhang, Jianyi Cheng, Ilia Shumailov, George A. Constantinides, Yiren Zhao:
Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference? EMNLP 2023: 9988-10006 - [c27]Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot:
When the Curious Abandon Honesty: Federated Learning Is Not Private. EuroS&P 2023: 175-199 - [c26]Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot:
Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation. EuroS&P 2023: 241-257 - [c25]Nicholas Boucher, Luca Pajola, Ilia Shumailov, Ross J. Anderson, Mauro Conti:
Boosting Big Brother: Attacking Search Engines with Encodings. RAID 2023: 700-713 - [c24]Shimaa Ahmed, Yash Wani, Ali Shahin Shamsabadi, Mohammad Yaghini, Ilia Shumailov, Nicolas Papernot, Kassem Fawaz:
Tubes Among Us: Analog Attack on Automatic Speaker Identification. USENIX Security Symposium 2023: 265-282 - [i44]Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot:
Is Federated Learning a Practical PET Yet? CoRR abs/2301.04017 (2023) - [i43]Yulin Zhou, Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Yarin Gal:
Revisiting Automated Prompting: Are We Actually Doing Better? CoRR abs/2304.03609 (2023) - [i42]Nicholas Boucher, Luca Pajola, Ilia Shumailov, Ross J. Anderson, Mauro Conti:
Boosting Big Brother: Attacking Search Engines with Encodings. CoRR abs/2304.14031 (2023) - [i41]Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, Ross J. Anderson:
The Curse of Recursion: Training on Generated Data Makes Models Forget. CoRR abs/2305.17493 (2023) - [i40]Nicholas Boucher, Jenny Blessing, Ilia Shumailov, Ross Anderson, Nicolas Papernot:
When Vision Fails: Text Attacks Against ViT and OCR. CoRR abs/2306.07033 (2023) - [i39]Pranav Dahiya, Ilia Shumailov, Ross J. Anderson:
Machine Learning needs its own Randomness Standard: Randomised Smoothing and PRNG-based attacks. CoRR abs/2306.14043 (2023) - [i38]Anvith Thudi, Hengrui Jia, Casey Meehan, Ilia Shumailov, Nicolas Papernot:
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD. CoRR abs/2307.00310 (2023) - [i37]David Glukhov, Ilia Shumailov, Yarin Gal, Nicolas Papernot, Vardan Papyan:
LLM Censorship: A Machine Learning Challenge or a Computer Security Problem? CoRR abs/2307.10719 (2023) - [i36]Yue Gao, Ilia Shumailov, Kassem Fawaz:
SEA: Shareable and Explainable Attribution for Query-based Black-box Attacks. CoRR abs/2308.11845 (2023) - [i35]David Khachaturov, Yue Gao, Ilia Shumailov, Robert D. Mullins, Ross J. Anderson, Kassem Fawaz:
Human-Producible Adversarial Examples. CoRR abs/2310.00438 (2023) - [i34]Avital Shafran, Ilia Shumailov, Murat A. Erdogdu, Nicolas Papernot:
Beyond Labeling Oracles: What does it mean to steal ML models? CoRR abs/2310.01959 (2023) - [i33]Cheng Zhang, Jianyi Cheng, Ilia Shumailov, George A. Constantinides, Yiren Zhao:
Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference? CoRR abs/2310.05079 (2023) - 2022
- [c23]Yue Gao, Ilia Shumailov, Kassem Fawaz:
Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems. ICML 2022: 7102-7121 - [c22]Yue Gao, Ilia Shumailov, Kassem Fawaz, Nicolas Papernot:
On the Limitations of Stochastic Pre-processing Defenses. NeurIPS 2022 - [c21]Jiaqi Wang, Roei Schuster, Ilia Shumailov, David Lie, Nicolas Papernot:
In Differential Privacy, There is Truth: on Vote-Histogram Leakage in Ensemble Private Learning. NeurIPS 2022 - [c20]Yiren Zhao, Xitong Gao, Ilia Shumailov, Nicolò Fusi, Robert D. Mullins:
Rapid Model Architecture Adaption for Meta-Learning. NeurIPS 2022 - [c19]Nicholas Boucher, Ilia Shumailov, Ross Anderson, Nicolas Papernot:
Bad Characters: Imperceptible NLP Attacks. SP 2022: 1987-2004 - [c18]Shimaa Ahmed, Ilia Shumailov, Nicolas Papernot, Kassem Fawaz:
Towards More Robust Keyword Spotting for Voice Assistants. USENIX Security Symposium 2022: 2655-2672 - [c17]Anvith Thudi, Hengrui Jia, Ilia Shumailov, Nicolas Papernot:
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning. USENIX Security Symposium 2022: 4007-4022 - [i32]Shimaa Ahmed, Yash Wani, Ali Shahin Shamsabadi, Mohammad Yaghini, Ilia Shumailov, Nicolas Papernot, Kassem Fawaz:
Pipe Overflow: Smashing Voice Authentication for Fun and Profit. CoRR abs/2202.02751 (2022) - [i31]Duo Wang, Yiren Zhao, Ilia Shumailov, Robert D. Mullins:
Model Architecture Adaption for Bayesian Neural Networks. CoRR abs/2202.04392 (2022) - [i30]Anvith Thudi, Ilia Shumailov, Franziska Boenisch, Nicolas Papernot:
Bounding Membership Inference. CoRR abs/2202.12232 (2022) - [i29]Mikel Bober-Irizar, Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Nicolas Papernot:
Architectural Backdoors in Neural Networks. CoRR abs/2206.07840 (2022) - [i28]Yue Gao, Ilia Shumailov, Kassem Fawaz, Nicolas Papernot:
On the Limitations of Stochastic Pre-processing Defenses. CoRR abs/2206.09491 (2022) - [i27]Maximilian Kaufmann, Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Nicolas Papernot:
Efficient Adversarial Training With Data Pruning. CoRR abs/2207.00694 (2022) - [i26]Jiaqi Wang, Roei Schuster, Ilia Shumailov, David Lie, Nicolas Papernot:
In Differential Privacy, There is Truth: On Vote Leakage in Ensemble Private Learning. CoRR abs/2209.10732 (2022) - [i25]Joseph Rance, Yiren Zhao, Ilia Shumailov, Robert D. Mullins:
Augmentation Backdoors. CoRR abs/2209.15139 (2022) - [i24]Tim Clifford, Ilia Shumailov, Yiren Zhao, Ross J. Anderson, Robert D. Mullins:
ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks. CoRR abs/2210.00108 (2022) - [i23]Jason Ross Brown, Yiren Zhao, Ilia Shumailov, Robert D. Mullins:
Wide Attention Is The Way Forward For Transformers. CoRR abs/2210.00640 (2022) - [i22]Jason Ross Brown, Yiren Zhao, Ilia Shumailov, Robert D. Mullins:
DARTFormer: Finding The Best Type Of Attention. CoRR abs/2210.00641 (2022) - 2021
- [c16]Ilia Shumailov, Yiren Zhao, Daniel Bates, Nicolas Papernot, Robert D. Mullins, Ross Anderson:
Sponge Examples: Energy-Latency Attacks on Neural Networks. EuroS&P 2021: 212-231 - [c15]David Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross J. Anderson:
Markpainting: Adversarial Machine Learning meets Inpainting. ICML 2021: 5409-5419 - [c14]Ilia Shumailov, Zakhar Shumaylov, Dmitry Kazhdan, Yiren Zhao, Nicolas Papernot, Murat A. Erdogdu, Ross J. Anderson:
Manipulating SGD with Data Ordering Attacks. NeurIPS 2021: 18021-18032 - [i21]Ilia Shumailov, Zakhar Shumaylov, Dmitry Kazhdan, Yiren Zhao, Nicolas Papernot, Murat A. Erdogdu, Ross J. Anderson:
Manipulating SGD with Data Ordering Attacks. CoRR abs/2104.09667 (2021) - [i20]David Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross J. Anderson:
Markpainting: Adversarial Machine Learning meets Inpainting. CoRR abs/2106.00660 (2021) - [i19]Nicholas Boucher, Ilia Shumailov, Ross J. Anderson, Nicolas Papernot:
Bad Characters: Imperceptible NLP Attacks. CoRR abs/2106.09898 (2021) - [i18]Yiren Zhao, Xitong Gao, Ilia Shumailov, Nicolò Fusi, Robert D. Mullins:
Rapid Model Architecture Adaption for Meta-Learning. CoRR abs/2109.04925 (2021) - [i17]Anvith Thudi, Hengrui Jia, Ilia Shumailov, Nicolas Papernot:
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning. CoRR abs/2110.11891 (2021) - [i16]Anh V. Vu, Lydia Wilson, Yi Ting Chua, Ilia Shumailov, Ross J. Anderson:
ExtremeBB: Enabling Large-Scale Research into Extremism, the Manosphere and Their Correlation by Online Forum Data. CoRR abs/2111.04479 (2021) - [i15]Franziska Boenisch, Adam Dziedzic, Roei Schuster, Ali Shahin Shamsabadi, Ilia Shumailov, Nicolas Papernot:
When the Curious Abandon Honesty: Federated Learning Is Not Private. CoRR abs/2112.02918 (2021) - 2020
- [c13]Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Ross J. Anderson:
Towards Certifiable Adversarial Sample Detection. AISec@CCS 2020: 13-24 - [c12]Yiren Zhao, Ilia Shumailov, Han Cui, Xitong Gao, Robert D. Mullins, Ross J. Anderson:
Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information. DSN Workshops 2020: 16-24 - [c11]Anh V. Vu, Jack Hughes, Ildiko Pete, Ben Collier, Yi Ting Chua, Ilia Shumailov, Alice Hutchings:
Turning Up the Dial: the Evolution of a Cybercrime Market Through Set-up, Stable, and Covid-19 Eras. Internet Measurement Conference 2020: 551-566 - [i14]Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Ross J. Anderson:
Towards Certifiable Adversarial Sample Detection. CoRR abs/2002.08740 (2020) - [i13]Ilia Shumailov, Yiren Zhao, Daniel Bates, Nicolas Papernot, Robert D. Mullins, Ross J. Anderson:
Sponge Examples: Energy-Latency Attacks on Neural Networks. CoRR abs/2006.03463 (2020) - [i12]Mansoor Ahmed-Rengers, Ross J. Anderson, Darija Halatova, Ilia Shumailov:
Snitches Get Stitches: On The Difficulty of Whistleblowing. CoRR abs/2006.14407 (2020) - [i11]Almos Zarandy, Ilia Shumailov, Ross J. Anderson:
BatNet: Data transmission between smartphones over ultrasound. CoRR abs/2008.00136 (2020) - [i10]Baiwu Zhang, Jin Peng Zhou, Ilia Shumailov, Nicolas Papernot:
Not My Deepfake: Towards Plausible Deniability for Machine-Generated Media. CoRR abs/2008.09194 (2020) - [i9]Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Ross J. Anderson:
Nudge Attacks on Point-Cloud DNNs. CoRR abs/2011.11637 (2020) - [i8]Almos Zarandy, Ilia Shumailov, Ross J. Anderson:
Hey Alexa what did I just type? Decoding smartphone sounds with a voice assistant. CoRR abs/2012.00687 (2020)
2010 – 2019
- 2019
- [c10]Rasika Bhalerao, Maxwell Aliapoulios, Ilia Shumailov, Sadia Afroz, Damon McCoy:
Mapping the Underground: Supervised Discovery of Cybercrime Supply Chains. eCrime 2019: 1-16 - [c9]Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Ross Anderson:
To Compress Or Not To Compress: Understanding The Interactions Between Adversarial Attacks And Neural Network Compression. SysML 2019 - [c8]Benjamin Maximilian Reinheimer, Fairooz Islam, Ilia Shumailov:
Audio CAPTCHA with a Few Cocktails: It's so Noisy I Can't Hear You. Security Protocols Workshop 2019: 20-40 - [c7]Benjamin Maximilian Reinheimer, Fairooz Islam, Ilia Shumailov:
Audio CAPTCHA with a Few Cocktails: It's So Noisy I Can't Hear You (Transcript of Discussion). Security Protocols Workshop 2019: 41-47 - [c6]Mansoor Ahmed-Rengers, Ross J. Anderson, Darija Halatova, Ilia Shumailov:
Snitches Get Stitches: On the Difficulty of Whistleblowing. Security Protocols Workshop 2019: 289-303 - [c5]Mansoor Ahmed-Rengers, Ross J. Anderson, Darija Halatova, Ilia Shumailov:
Snitches Get Stitches: On the Difficulty of Whistleblowing (Transcript of Discussion). Security Protocols Workshop 2019: 304-312 - [c4]Matthias Kirchner, Cecilia Pasquini, Ilia Shumailov:
Information Security Meets Adversarial Examples. WIFS 2019: 1-2 - [i7]Mansoor Ahmed-Rengers, Ilia Shumailov, Ross Anderson:
Tendrils of Crime: Visualizing the Diffusion of Stolen Bitcoins. CoRR abs/1901.01769 (2019) - [i6]Ilia Shumailov, Xitong Gao, Yiren Zhao, Robert D. Mullins, Ross Anderson, Cheng-Zhong Xu:
Sitatapatra: Blocking the Transfer of Adversarial Samples. CoRR abs/1901.08121 (2019) - [i5]Ilia Shumailov, Laurent Simon, Jeff Yan, Ross Anderson:
Hearing your touch: A new acoustic side channel on smartphones. CoRR abs/1903.11137 (2019) - [i4]Yiren Zhao, Ilia Shumailov, Han Cui, Xitong Gao, Robert D. Mullins, Ross J. Anderson:
Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information. CoRR abs/1909.02918 (2019) - 2018
- [c3]Mansoor Ahmed-Rengers, Ilia Shumailov, Ross Anderson:
Tendrils of Crime: Visualizing the Diffusion of Stolen Bitcoins. GraMSec@FLoC 2018: 1-12 - [c2]Ross Anderson, Ilia Shumailov, Mansoor Ahmed-Rengers:
Making Bitcoin Legal. Security Protocols Workshop 2018: 243-253 - [i3]Yiren Zhao, Ilia Shumailov, Robert D. Mullins, Ross Anderson:
To compress or not to compress: Understanding the Interactions between Adversarial Attacks and Neural Network Compression. CoRR abs/1810.00208 (2018) - [i2]Ilia Shumailov, Yiren Zhao, Robert D. Mullins, Ross Anderson:
The Taboo Trap: Behavioural Detection of Adversarial Samples. CoRR abs/1811.07375 (2018) - [i1]Rasika Bhalerao, Maxwell Aliapoulios, Ilia Shumailov, Sadia Afroz, Damon McCoy:
Towards Automatic Discovery of Cybercrime Supply Chains. CoRR abs/1812.00381 (2018) - 2017
- [c1]Ilia Shumailov, Hatice Gunes:
Computational analysis of valence and arousal in virtual reality gaming using lower arm electromyograms. ACII 2017: 164-169
Coauthor Index
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