2 citations · 11 across the 25 of their papers we have counts for
10 papers · 1 filter
Efficiency Boosting of Secure Cross-platform Recommender Systems over Sparse Data
Hao Ren, Guowen Xu, Tianwei Zhang +4
Fueled by its successful commercialization, the recommender system (RS) has gained widespread attention. However, as the training data fed into the RS models are often highly sensi…
A Benchmark of Long-tailed Instance Segmentation with Noisy Labels
Guanlin Li, Guowen Xu, Tianwei Zhang
In this paper, we consider the instance segmentation task on a long-tailed dataset, which contains label noise, i.e., some of the annotations are incorrect. There are two main reas…
New Secure Sparse Inner Product with Applications to Machine Learning
Guowen Xu, Shengmin Xu, Jianting Ning +4
Sparse inner product (SIP) has the attractive property of overhead being dominated by the intersection of inputs between parties, independent of the actual input size. It has intri…
VerifyML: Obliviously Checking Model Fairness Resilient to Malicious Model Holder
Guowen Xu, Xingshuo Han, Gelei Deng +5
In this paper, we present VerifyML, the first secure inference framework to check the fairness degree of a given Machine learning (ML) model. VerifyML is generic and is immune to a…
Hercules: Boosting the Performance of Privacy-preserving Federated Learning
Guowen Xu, Xingshuo Han, Shengmin Xu +4
In this paper, we address the problem of privacy-preserving federated neural network training with users. We present Hercules, an efficient and high-precision training framewor…
Privacy-preserving Decentralized Deep Learning with Multiparty Homomorphic Encryption
Guowen Xu, Guanlin Li, Shangwei Guo +2
Decentralized deep learning plays a key role in collaborative model training due to its attractive properties, including tolerating high network latency and less prone to single-po…
A Secure Fingerprinting Framework for Distributed Image Classification
Guowen Xu, Xingshuo Han, Anguo Zhang +1
The deep learning (DL) technology has been widely used for image classification in many scenarios, e.g., face recognition and suspect tracking. Such a highly commercialized applica…
SIMC 2.0: Improved Secure ML Inference Against Malicious Clients
Guowen Xu, Xingshuo Han, Tianwei Zhang +5
In this paper, we study the problem of secure ML inference against a malicious client and a semi-trusted server such that the client only learns the inference output while the serv…
ShiftNAS: Towards Automatic Generation of Advanced Mulitplication-Less Neural Networks
Xiaoxuan Lou, Guowen Xu, Kangjie Chen +3
Multiplication-less neural networks significantly reduce the time and energy cost on the hardware platform, as the compute-intensive multiplications are replaced with lightweight b…
Physical Backdoor Attacks to Lane Detection Systems in Autonomous Driving
Xingshuo Han, Guowen Xu, Yuan Zhou +3
Modern autonomous vehicles adopt state-of-the-art DNN models to interpret the sensor data and perceive the environment. However, DNN models are vulnerable to different types of adv…