63 citations · 75 across the 19 of their papers we have counts for
5 papers · 1 filter
Temporal Misalignment Attacks against Multimodal Perception in Autonomous Driving
Md Hasan Shahriar, Md Mohaimin Al Barat, Harshavardhan Sundar +4
Multimodal fusion (MMF) plays a critical role in the perception of autonomous driving, which primarily fuses camera and LiDAR streams for a comprehensive and efficient scene unders…
MedLeak: Multimodal Medical Data Leakage in Secure Federated Learning with Crafted Models
Shanghao Shi, Md Shahedul Haque, Abhijeet Parida +5
Federated learning (FL) allows participants to collaboratively train machine learning models while keeping their data local, making it ideal for collaborations among healthcare ins…
BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning
Zhengyuan Jiang, Xingyu Lyu, Shanghao Shi +5
Federated learning, while being a promising approach for collaborative model training, is susceptible to backdoor attacks due to its decentralized nature. Backdoor attacks have sho…
Let the Noise Speak: Harnessing Noise for a Unified Defense Against Adversarial and Backdoor Attacks
Md Hasan Shahriar, Ning Wang, Naren Ramakrishnan +2
The exponential adoption of machine learning (ML) is propelling the world into a future of distributed and intelligent automation and data-driven solutions. However, the proliferat…
Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction
Shanghao Shi, Ning Wang, Yang Xiao +4
Federated learning is known for its capability to safeguard the participants' data privacy. However, recently emerged model inversion attacks (MIAs) have shown that a malicious par…