Ilia Shumailov

Orcid: 0000-0003-3100-0727

According to our database1, Ilia Shumailov authored at least 61 papers between 2017 and 2024.

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Bibliography

2024
Fairness Feedback Loops: Training on Synthetic Data Amplifies Bias.
CoRR, 2024

Inexact Unlearning Needs More Careful Evaluations to Avoid a False Sense of Privacy.
CoRR, 2024

Architectural Neural Backdoors from First Principles.
CoRR, 2024

Buffer Overflow in Mixture of Experts.
CoRR, 2024

2023
Beyond Labeling Oracles: What does it mean to steal ML models?
CoRR, 2023

Human-Producible Adversarial Examples.
CoRR, 2023

SEA: Shareable and Explainable Attribution for Query-based Black-box Attacks.
CoRR, 2023

LLM Censorship: A Machine Learning Challenge or a Computer Security Problem?
CoRR, 2023

Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD.
CoRR, 2023

Machine Learning needs its own Randomness Standard: Randomised Smoothing and PRNG-based attacks.
CoRR, 2023

When Vision Fails: Text Attacks Against ViT and OCR.
CoRR, 2023

The Curse of Recursion: Training on Generated Data Makes Models Forget.
CoRR, 2023

Is Federated Learning a Practical PET Yet?
CoRR, 2023

Tubes Among Us: Analog Attack on Automatic Speaker Identification.
Proceedings of the 32nd USENIX Security Symposium, 2023

Boosting Big Brother: Attacking Search Engines with Encodings.
Proceedings of the 26th International Symposium on Research in Attacks, 2023

Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation.
Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

When the Curious Abandon Honesty: Federated Learning Is Not Private.
Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference?
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Architectural Backdoors in Neural Networks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Revisiting Automated Prompting: Are We Actually Doing Better?
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022
DARTFormer: Finding The Best Type Of Attention.
CoRR, 2022

Wide Attention Is The Way Forward For Transformers.
CoRR, 2022

ImpNet: Imperceptible and blackbox-undetectable backdoors in compiled neural networks.
CoRR, 2022

Augmentation Backdoors.
CoRR, 2022

In Differential Privacy, There is Truth: On Vote Leakage in Ensemble Private Learning.
CoRR, 2022

Efficient Adversarial Training With Data Pruning.
CoRR, 2022

Bounding Membership Inference.
CoRR, 2022

Model Architecture Adaption for Bayesian Neural Networks.
CoRR, 2022

Pipe Overflow: Smashing Voice Authentication for Fun and Profit.
CoRR, 2022

On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning.
Proceedings of the 31st USENIX Security Symposium, 2022

Towards More Robust Keyword Spotting for Voice Assistants.
Proceedings of the 31st USENIX Security Symposium, 2022

Bad Characters: Imperceptible NLP Attacks.
Proceedings of the 43rd IEEE Symposium on Security and Privacy, 2022

Rapid Model Architecture Adaption for Meta-Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

In Differential Privacy, There is Truth: on Vote-Histogram Leakage in Ensemble Private Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Limitations of Stochastic Pre-processing Defenses.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems.
Proceedings of the International Conference on Machine Learning, 2022

2021
ExtremeBB: Enabling Large-Scale Research into Extremism, the Manosphere and Their Correlation by Online Forum Data.
CoRR, 2021

Manipulating SGD with Data Ordering Attacks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Markpainting: Adversarial Machine Learning meets Inpainting.
Proceedings of the 38th International Conference on Machine Learning, 2021

Sponge Examples: Energy-Latency Attacks on Neural Networks.
Proceedings of the IEEE European Symposium on Security and Privacy, 2021

2020
Hey Alexa what did I just type? Decoding smartphone sounds with a voice assistant.
CoRR, 2020

Nudge Attacks on Point-Cloud DNNs.
CoRR, 2020

Not My Deepfake: Towards Plausible Deniability for Machine-Generated Media.
CoRR, 2020

BatNet: Data transmission between smartphones over ultrasound.
CoRR, 2020

Turning Up the Dial: the Evolution of a Cybercrime Market Through Set-up, Stable, and Covid-19 Eras.
Proceedings of the IMC '20: ACM Internet Measurement Conference, 2020

Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information.
Proceedings of the 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2020

Towards Certifiable Adversarial Sample Detection.
Proceedings of the AISec@CCS 2020: Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security, 2020

2019
Hearing your touch: A new acoustic side channel on smartphones.
CoRR, 2019

Sitatapatra: Blocking the Transfer of Adversarial Samples.
CoRR, 2019

Information Security Meets Adversarial Examples.
Proceedings of the IEEE International Workshop on Information Forensics and Security, 2019

Audio CAPTCHA with a Few Cocktails: It's So Noisy I Can't Hear You (Transcript of Discussion).
Proceedings of the Security Protocols XXVII, 2019

Audio CAPTCHA with a Few Cocktails: It's so Noisy I Can't Hear You.
Proceedings of the Security Protocols XXVII, 2019

Snitches Get Stitches: On the Difficulty of Whistleblowing (Transcript of Discussion).
Proceedings of the Security Protocols XXVII, 2019

Snitches Get Stitches: On the Difficulty of Whistleblowing.
Proceedings of the Security Protocols XXVII, 2019

To Compress Or Not To Compress: Understanding The Interactions Between Adversarial Attacks And Neural Network Compression.
Proceedings of Machine Learning and Systems 2019, 2019

Mapping the Underground: Supervised Discovery of Cybercrime Supply Chains.
Proceedings of the 2019 APWG Symposium on Electronic Crime Research, 2019

2018
Towards Automatic Discovery of Cybercrime Supply Chains.
CoRR, 2018

The Taboo Trap: Behavioural Detection of Adversarial Samples.
CoRR, 2018

Making Bitcoin Legal.
Proceedings of the Security Protocols XXVI, 2018

Tendrils of Crime: Visualizing the Diffusion of Stolen Bitcoins.
Proceedings of the 5th International Workshop on Graphical Models for Security, 2018

2017
Computational analysis of valence and arousal in virtual reality gaming using lower arm electromyograms.
Proceedings of the Seventh International Conference on Affective Computing and Intelligent Interaction, 2017


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