Emily Wenger
Electrical and Computer Engineering
Assistant Professor of Electrical and Computer Engineering
Research Themes
Trustworthy Computing
Education
- B.S. Wheaton College, 2016
- M.S. The University of Chicago, 2020
- Ph.D. The University of Chicago, 2023
Positions
- Assistant Professor of Electrical and Computer Engineering
Courses Taught
- ECE 590: Advanced Topics in Electrical and Computer Engineering
- ECE 291: Projects in Electrical and Computer Engineering
Publications
- Wenger E. AI produces gibberish when trained on too much AI-generated data. Nature. 2024 Jul 25;631(8022):742–3.
- Nolte N, Malhou M, Wenger E, Stevens S, Li C, Charton F, et al. The Cool and the Cruel: Separating Hard Parts of LWE Secrets. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2024. p. 428–53.
- Li CY, Malhou M, Sotáková J, Garcelon E, Lauter K, Wenger E, et al. Salsa Picante: A Machine Learning Attack On LWE with Binary Secrets. In: CCS 2023 - Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security. 2023. p. 2606–20.
- Wenger E, Shan S, Zheng H, Zhao BY. SoK: Anti-Facial Recognition Technology. In: Proceedings - IEEE Symposium on Security and Privacy. 2023. p. 864–81.
- Shan S, Cryan J, Wenger E, Zheng H, Hanocka R, Zhao BY. Glaze: Protecting Artists from Style Mimicry by Text-to-Image Models. In: 32nd USENIX Security Symposium, USENIX Security 2023. 2023. p. 2187–204.
- Li CY, Wenger E, Allen-Zhu Z, Charton F, Lauter K. SALSA VERDE: a machine learning attack on Learning With Errors with sparse small secrets. In: Advances in Neural Information Processing Systems. 2023. p. 53343–61.
- Shan S, Ding W, Wenger E, Zheng H, Zhao BY. Post-breach Recovery: Protection against White-box Adversarial Examples for Leaked DNN Models. In: Proceedings of the ACM Conference on Computer and Communications Security. 2022. p. 2611–25.
- Pham A, Samragh M, Wagh S, Wenger E. Private movie recommendations for children. In: Protecting Privacy through Homomorphic Encryption. 2022. p. 163–7.
- Wenger E, Bhattacharjee R, Bhagoji AN, Passananti J, Andere E, Zheng H, et al. Finding Naturally Occurring Physical Backdoors in Image Datasets. In: Advances in Neural Information Processing Systems. 2022.
- Wenger E, Chen M, Charton F, Lauter K. SALSA: Attacking Lattice Cryptography with Transformers. In: Advances in Neural Information Processing Systems. 2022.
- Li H, Shan S, Wenger E, Zhang J, Zheng H, Zhao BY. Blacklight: Scalable Defense for Neural Networks against Query-Based Black-Box Attacks. In: Proceedings of the 31st USENIX Security Symposium, Security 2022. 2022. p. 2117–34.
- Wenger E, Bronckers M, Cianfarani C, Cryan J, Sha A, Zheng H, et al. "hello, It's Me": Deep Learning-based Speech Synthesis Attacks in the Real World. In: Proceedings of the ACM Conference on Computer and Communications Security. 2021. p. 235–51.
- Wenger E, Passananti J, Bhagoji AN, Yao Y, Zheng H, Zhao BY. Backdoor Attacks Against Deep Learning Systems in the Physical World. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2021. p. 6202–11.
- Shan S, Wenger E, Wang B, Li B, Zheng H, Zhao BY. Gotta Catch'Em All: Using Honeypots to Catch Adversarial Attacks on Neural Networks. In: Proceedings of the ACM Conference on Computer and Communications Security. 2020. p. 67–83.
- Shan S, Wenger E, Zhang J, Li H, Zheng H, Zhao BY. Fawkes: Protecting privacy against unauthorized deep learning models. In: Proceedings of the 29th USENIX Security Symposium. 2020. p. 1589–604.
In The News
- AI is the Biggest Cybersecurity Question Mark. Is It Also the Answer? (Nov 12, 2024 | Pratt School of Engineering)