15 citations · 32 across the 11 of their papers we have counts for
18 papers
Safety Analysis of Autonomous Driving Systems Based on Model Learning
Renjue Li, Tianhang Qin, Pengfei Yang +3
We present a practical verification method for safety analysis of the autonomous driving system (ADS). The main idea is to build a surrogate model that quantitatively depicts the b…
VeriFi: Towards Verifiable Federated Unlearning
Xiangshan Gao, Xingjun Ma, Jingyi Wang +5
Federated learning (FL) is a collaborative learning paradigm where participants jointly train a powerful model without sharing their private data. One desirable property for FL is…
VPN: Verification of Poisoning in Neural Networks
Youcheng Sun, Muhammad Usman, Divya Gopinath +1
Neural networks are successfully used in a variety of applications, many of them having safety and security concerns. As a result researchers have proposed formal verification tech…
AntidoteRT: Run-time Detection and Correction of Poison Attacks on Neural Networks
Muhammad Usman, Youcheng Sun, Divya Gopinath +1
We study backdoor poisoning attacks against image classification networks, whereby an attacker inserts a trigger into a subset of the training data, in such a way that at test time…
Tutorials on Testing Neural Networks
Nicolas Berthier, Youcheng Sun, Wei Huang +3
Deep learning achieves remarkable performance on pattern recognition, but can be vulnerable to defects of some important properties such as robustness and security. This tutorial i…
NNrepair: Constraint-based Repair of Neural Network Classifiers
Muhammad Usman, Divya Gopinath, Youcheng Sun +2
We present NNrepair, a constraint-based technique for repairing neural network classifiers. The technique aims to fix the logic of the network at an intermediate layer or at the la…