A Matlab toolbox for visualization of image manifolds. - Kevin Eykholt; Marco F. Duarte (GlobalSIP, 2013)

Heimdall: A Privacy-Respecting Implicit Preference Collection Framework. - Amir Rahmati; Earlence Fernandes; Kevin Eykholt; Xinheng Chen; Atul Prakash 001 (MobiSys, 2017)

Ensuring Authorized Updates in Multi-user Database-Backed Applications. - Kevin Eykholt; Atul Prakash 001; Barzan Mozafari (USENIX Security Symposium, 2017)

Robust Physical-World Attacks on Machine Learning Models. - Ivan Evtimov; Kevin Eykholt; Earlence Fernandes; Tadayoshi Kohno; Bo Li 026; Atul Prakash 001; Amir Rahmati; Dawn Song (CoRR, 2017)

Note on Attacking Object Detectors with Adversarial Stickers. - Kevin Eykholt; Ivan Evtimov; Earlence Fernandes; Bo Li 026; Dawn Song; Tadayoshi Kohno; Amir Rahmati; Atul Prakash 001; Florian Tramèr (CoRR, 2017)

Internet of Things Security Research: A Rehash of Old Ideas or New Intellectual Challenges? - Earlence Fernandes; Amir Rahmati; Kevin Eykholt; Atul Prakash 001 (IEEE Secur. Priv., 2017)

Robust Physical-World Attacks on Deep Learning Visual Classification. - Kevin Eykholt; Ivan Evtimov; Earlence Fernandes; Bo Li 026; Amir Rahmati; Chaowei Xiao; Atul Prakash 001; Tadayoshi Kohno; Dawn Song (CVPR, 2018)

Tyche: A Risk-Based Permission Model for Smart Homes. - Amir Rahmati; Earlence Fernandes; Kevin Eykholt; Atul Prakash 001 (SecDev, 2018)

Physical Adversarial Examples for Object Detectors. - Dawn Song; Kevin Eykholt; Ivan Evtimov; Earlence Fernandes; Bo Li 026; Amir Rahmati; Florian Tramèr; Atul Prakash 001; Tadayoshi Kohno (WOOT @ USENIX Security Symposium, 2018)

Tyche: Risk-Based Permissions for Smart Home Platforms. - Amir Rahmati; Earlence Fernandes; Kevin Eykholt; Atul Prakash 001 (CoRR, 2018)

Designing Adversarially Resilient Classifiers using Resilient Feature Engineering. - Kevin Eykholt; Atul Prakash 001 (CoRR, 2018)

Robust Classification using Robust Feature Augmentation. - Kevin Eykholt; Swati Gupta 001; Atul Prakash 001; Haizhong Zheng (CoRR, 2019)

Transferable Adversarial Robustness using Adversarially Trained Autoencoders. - Pratik Vaishnavi; Kevin Eykholt; Atul Prakash 001; Amir Rahmati (CoRR, 2019)

Can Attention Masks Improve Adversarial Robustness? - Pratik Vaishnavi; Tianji Cong; Kevin Eykholt; Atul Prakash 001; Amir Rahmati (CoRR, 2019)

Designing and Evaluating Physical Adversarial Attacks and Defenses for Machine Learning Algorithms. - Kevin Eykholt (2019)

Adaptive Verifiable Training Using Pairwise Class Similarity. - Shiqi Wang 002; Kevin Eykholt; Taesung Lee; Jiyong Jang; Ian M. Molloy (AAAI, 2021)

Separation of Powers in Federated Learning (Poster Paper). - Pau-Chen Cheng; Kevin Eykholt; Zhongshu Gu; Hani Jamjoom; K. R. Jayaram; Enriquillo Valdez; Ashish Verma 001 (ResilientFL, 2021)

Separation of Powers in Federated Learning. - Pau-Chen Cheng; Kevin Eykholt; Zhongshu Gu; Hani Jamjoom; K. R. Jayaram; Enriquillo Valdez; Ashish Verma 001 (CoRR, 2021)

Accelerating Certified Robustness Training via Knowledge Transfer. - Pratik Vaishnavi; Kevin Eykholt; Amir Rahmati (NeurIPS, 2022)

Ares: A System-Oriented Wargame Framework for Adversarial ML. - Farhan Ahmed; Pratik Vaishnavi; Kevin Eykholt; Amir Rahmati (SP (Workshops), 2022)

Transferring Adversarial Robustness Through Robust Representation Matching. - Pratik Vaishnavi; Kevin Eykholt; Amir Rahmati (USENIX Security Symposium, 2022)

EdgeTorrent: Real-time Temporal Graph Representations for Intrusion Detection. - Isaiah J. King; Xiaokui Shu; Jiyong Jang; Kevin Eykholt; Taesung Lee; H. Howie Huang (RAID, 2023)

Benchmarking the Effect of Poisoning Defenses on the Security and Bias of Deep Learning Models. - Nathalie Baracaldo; Farhan Ahmed; Kevin Eykholt; Yi Zhou 015; Shriti Priya; Taesung Lee; Swanand Kadhe; Mike Tan; Sridevi Polavaram; Sterling Suggs; Yuyang Gao; David Slater (SP (Workshops), 2023)

URET: Universal Robustness Evaluation Toolkit (for Evasion). - Kevin Eykholt; Taesung Lee; Douglas Lee Schales; Jiyong Jang; Ian M. Molloy; Masha Zorin (USENIX Security Symposium, 2023)

DeTA: Minimizing Data Leaks in Federated Learning via Decentralized and Trustworthy Aggregation. - Pau-Chen Cheng; Kevin Eykholt; Zhongshu Gu; Hani Jamjoom; K. R. Jayaram; Enriquillo Valdez; Ashish Verma 001 (EuroSys, 2024)

Taking off the Rose-Tinted Glasses: A Critical Look at Adversarial ML Through the Lens of Evasion Attacks. - Kevin Eykholt; Farhan Ahmed; Pratik Vaishnavi; Amir Rahmati (CoRR, 2024)

A Study of the Effects of Transfer Learning on Adversarial Robustness. - Pratik Vaishnavi; Kevin Eykholt; Amir Rahmati (Trans. Mach. Learn. Res., 2024)