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20172026
most citedInvisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks

226 citations · 873 across the 78 of their papers we have counts for

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Showing cs.CRShow all

5 papers · 1 filter

cs.CR2023★ 4 cited

Towards Generalizable Data Protection With Transferable Unlearnable Examples

Bin Fang, Bo Li, Shuang Wu +4

Artificial Intelligence (AI) is making a profound impact in almost every domain. One of the crucial factors contributing to this success has been the access to an abundance of high…

cs.CR2023★ 2 cited

Re-thinking Data Availablity Attacks Against Deep Neural Networks

Bin Fang, Bo Li, Shuang Wu +3

The unauthorized use of personal data for commercial purposes and the clandestine acquisition of private data for training machine learning models continue to raise concerns. In re…

cs.CR2021

MG-DVD: A Real-time Framework for Malware Variant Detection Based on Dynamic Heterogeneous Graph Learning

Chen Liu, Bo Li, Jun Zhao +2

Detecting the newly emerging malware variants in real time is crucial for mitigating cyber risks and proactively blocking intrusions. In this paper, we propose MG-DVD, a novel dete…

cs.CR2021★ 226 cited

Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks

Yulong Cao*, Ningfei Wang*, Chaowei Xiao* +6

In Autonomous Driving (AD) systems, perception is both security and safety critical. Despite various prior studies on its security issues, all of them only consider attacks on came…

cs.CR2018

MeshAdv: Adversarial Meshes for Visual Recognition

Chaowei Xiao, Dawei Yang, Bo Li +2

Highly expressive models such as deep neural networks (DNNs) have been widely applied to various applications. However, recent studies show that DNNs are vulnerable to adversarial…