Ryan Feng

According to our database, Ryan Feng authored at least 17 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles.

Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

Theoretically Principled Trade-off for Stateful Defenses against Query-Based Black-Box Attacks.

Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash

CoRR, 2023

Investigating Stateful Defenses Against Black-Box Adversarial Examples.

Ryan Feng, Ashish Hooda, Neal Mangaokar, Kassem Fawaz, Somesh Jha, Atul Prakash

CoRR, 2023

Concept-based Explanations for Out-of-Distribution Detectors.

Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash

Proceedings of the International Conference on Machine Learning, 2023

Stateful Defenses for Machine Learning Models Are Not Yet Secure Against Black-box Attacks.

Ryan Feng, Ashish Hooda, Neal Mangaokar, Kassem Fawaz, Somesh Jha, Atul Prakash

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023

2022

Constraining the Attack Space of Machine Learning Models with Distribution Clamping Preprocessing.

Ryan Feng, Somesh Jha, Atul Prakash

CoRR, 2022

Towards Adversarially Robust Deepfake Detection: An Ensemble Approach.

Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash

CoRR, 2022

GRAPHITE: Generating Automatic Physical Examples for Machine-Learning Attacks on Computer Vision Systems.

Ryan Feng, Neal Mangaokar, Jiefeng Chen, Earlence Fernandes, Somesh Jha, Atul Prakash

Proceedings of the 7th IEEE European Symposium on Security and Privacy, 2022

2021

Using Anomaly Feature Vectors for Detecting, Classifying and Warning of Outlier Adversarial Examples.

Nelson Manohar-Alers, Ryan Feng, Sahib Singh, Jiguo Song, Atul Prakash

CoRR, 2021

Smart Black Box 2.0: Efficient High-Bandwidth Driving Data Collection Based on Video Anomalies.

Ryan Feng, Yu Yao, Ella M. Atkins

Algorithms, 2021

2020

Essential Features: Reducing the Attack Surface of Adversarial Perturbations with Robust Content-Aware Image Preprocessing.

Ryan Feng, Wu-chi Feng, Atul Prakash

CoRR, 2020

Query-Efficient Physical Hard-Label Attacks on Deep Learning Visual Classification.

Ryan Feng, Jiefeng Chen, Nelson R. Manohar, Earlence Fernandes, Somesh Jha, Atul Prakash

CoRR, 2020

2019

Robot-Assisted Feeding: Generalizing Skewering Strategies across Food Items on a Realistic Plate.

Ryan Feng, Youngsun Kim, Gilwoo Lee, Ethan K. Gordon, Matt Schmittle, Shivaum Kumar, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa

CoRR, 2019

Robot-Assisted Feeding: Generalizing Skewering Strategies Across Food Items on a Plate.

Ryan Feng, Youngsun Kim, Gilwoo Lee, Ethan K. Gordon, Matt Schmittle, Shivaum Kumar, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa

Proceedings of the Robotics Research, 2019

Leveraging Image Processing Techniques to Thwart Adversarial Attacks in Image Classification.

Yeganeh Jalalpour, Li-Yun Wang, Ryan Feng, Wu-chi Feng

Proceedings of the IEEE International Symposium on Multimedia, 2019

2018

ISIFT: extracting incremental results from SIFT.

Ben Hamlin, Ryan Feng, Wu-chi Feng

Proceedings of the 9th ACM Multimedia Systems Conference, 2018

2016

Understanding the Impact of Compression on Feature Detection and Matching in Computer Vision.

Wu-chi Feng, Ryan Feng, Paul Wyatt, Feng Liu

Proceedings of the IEEE International Symposium on Multimedia, 2016