Tiny noise, big mistakes: Adversarial perturbations induce errors in Brain-Computer Interface spellers
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Abstract (arXiv)
An electroencephalogram (EEG) based brain-computer interface (BCI) speller allows a user to input text to a computer by thought. It is particularly useful to severely disabled individuals, e.g., amyotrophic lateral sclerosis patients, who have no other effective means of communication with another person or a computer. Most studies so far focused on making EEG-based BCI spellers faster and more reliable; however, few have considered their security. This study, for the first time, shows that P300 and steady-state visual evoked potential BCI spellers are very vulnerable, i.e., they can be severely attacked by adversarial perturbations, which are too tiny to be noticed when added to EEG signals, but can mislead the spellers to spell anything the attacker wants. The consequence could range from merely user frustration to severe misdiagnosis in clinical applications. We hope our research can attract more attention to the security of EEG-based BCI spellers, and more broadly, EEG-based BCIs, which has received little attention before.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jan 2020.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 2; 2024: 5; 2025: 1; 2026: 2.
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- 2022Deep Learning for Brain Age Estimation: A Systematic Reviewcited by 12
- 2023Interpretable and Robust AI in EEG Systems: A Surveycited by 10
- 2021Adversarial Attacks and Defenses in Physiological Computing: A Systematic Reviewcited by 7
- 2025Revisiting Euclidean Alignment for Transfer Learning in EEG-Based Brain-Computer Interfacescited by 7
- 2023Explainable artificial intelligence approaches for brain-computer interfaces: a review and design spacecited by 5
- 2024Alignment-Based Adversarial Training (ABAT) for Improving the Robustness and Accuracy of EEG-Based BCIscited by 5
- 2024User-wise Perturbations for User Identity Protection in EEG-Based BCIscited by 5
- 2022Adversarial Artifact Detection in EEG-Based Brain-Computer Interfacescited by 4
- 2024"Forgetting" in Machine Learning and Beyond: A Surveycited by 2
- 2024PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decodingcited by 2
- 2022Enhancing the Security & Privacy of Wearable Brain-Computer Interfacescited by 1
- 2024Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer Interfacescited by 1
- 2026SW-ProxyCE: Zero-Query Adversarial Transfer from Public EEG Encoders to Private Downstream Models5 Aug 2026
- 2026SAFE: Secure and Accurate Federated Learning for Privacy-Preserving Brain-Computer Interfaces9 Jan 2026
- 2025Revisiting Euclidean Alignment for Transfer Learning in EEG-Based Brain-Computer Interfaces13 Feb 2025
- 2024PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding16 Dec 2024
- 2024Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer Interfaces10 Dec 2024
- 2024User-wise Perturbations for User Identity Protection in EEG-Based BCIs4 Nov 2024
- 2024Alignment-Based Adversarial Training (ABAT) for Improving the Robustness and Accuracy of EEG-Based BCIs4 Nov 2024
- 2024"Forgetting" in Machine Learning and Beyond: A Survey31 May 2024
- 2023Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space20 Dec 2023
- 2023Interpretable and Robust AI in EEG Systems: A Survey21 Apr 2023
- 2022Deep Learning for Brain Age Estimation: A Systematic Review7 Dec 2022
- 2022Adversarial Artifact Detection in EEG-Based Brain-Computer Interfaces28 Nov 2022
- 2022Deep Learning for Brain Age Estimation: A Systematic Reviewcited by 12
- 2023Interpretable and Robust AI in EEG Systems: A Surveycited by 10
- 2021Adversarial Attacks and Defenses in Physiological Computing: A Systematic Reviewcited by 7
- 2025Revisiting Euclidean Alignment for Transfer Learning in EEG-Based Brain-Computer Interfacescited by 7
- 2023Explainable artificial intelligence approaches for brain-computer interfaces: a review and design spacecited by 5
- 2024Alignment-Based Adversarial Training (ABAT) for Improving the Robustness and Accuracy of EEG-Based BCIscited by 5
- 2024User-wise Perturbations for User Identity Protection in EEG-Based BCIscited by 5
- 2022Adversarial Artifact Detection in EEG-Based Brain-Computer Interfacescited by 4
- 2024"Forgetting" in Machine Learning and Beyond: A Surveycited by 2
- 2024PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decodingcited by 2
- 2022Enhancing the Security & Privacy of Wearable Brain-Computer Interfacescited by 1
- 2024Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer Interfacescited by 1
12 most cited of 14 All 14 (JSON)
- 2026SW-ProxyCE: Zero-Query Adversarial Transfer from Public EEG Encoders to Private Downstream Models5 Aug 2026
- 2026SAFE: Secure and Accurate Federated Learning for Privacy-Preserving Brain-Computer Interfaces9 Jan 2026
- 2025Revisiting Euclidean Alignment for Transfer Learning in EEG-Based Brain-Computer Interfaces13 Feb 2025
- 2024PAT: Privacy-Preserving Adversarial Transfer for Accurate, Robust and Privacy-Preserving EEG Decoding16 Dec 2024
- 2024Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer Interfaces10 Dec 2024
- 2024User-wise Perturbations for User Identity Protection in EEG-Based BCIs4 Nov 2024
- 2024Alignment-Based Adversarial Training (ABAT) for Improving the Robustness and Accuracy of EEG-Based BCIs4 Nov 2024
- 2024"Forgetting" in Machine Learning and Beyond: A Survey31 May 2024
- 2023Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space20 Dec 2023
- 2023Interpretable and Robust AI in EEG Systems: A Survey21 Apr 2023
- 2022Deep Learning for Brain Age Estimation: A Systematic Review7 Dec 2022
- 2022Adversarial Artifact Detection in EEG-Based Brain-Computer Interfaces28 Nov 2022
12 newest of 14 All 14 (JSON)