activity
20182023
most citedHow to Prove Your Model Belongs to You: A Blind-Watermark based Framework to Protect Intellectual Property of DNN

142 citations · 170 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2023

RNN-Guard: Certified Robustness Against Multi-frame Attacks for Recurrent Neural Networks

Yunruo Zhang, Tianyu Du, Shouling Ji +2

It is well-known that recurrent neural networks (RNNs), although widely used, are vulnerable to adversarial attacks including one-frame attacks and multi-frame attacks. Though a fe…

cs.CR2022★ 12 cited

An Extensive Study of Residential Proxies in China

Mingshuo Yang, Yunnan Yu, Xianghang Mi +5

We carry out the first in-depth characterization of residential proxies (RESIPs) in China, for which little is studied in previous works. Our study is made possible through a seman…

cs.CR2022★ 13 cited

Seeing is Living? Rethinking the Security of Facial Liveness Verification in the Deepfake Era

Changjiang Li, Li Wang, Shouling Ji +4

Facial Liveness Verification (FLV) is widely used for identity authentication in many security-sensitive domains and offered as Platform-as-a-Service (PaaS) by leading cloud vendor…

cs.CR2021★ 1 cited

SoK: A Modularized Approach to Study the Security of Automatic Speech Recognition Systems

Yuxuan Chen, Jiangshan Zhang, Xuejing Yuan +4

With the wide use of Automatic Speech Recognition (ASR) in applications such as human machine interaction, simultaneous interpretation, audio transcription, etc., its security prot…

cs.CR2019

Learning Symmetric and Asymmetric Steganography via Adversarial Training

Zheng Li, Ge Han, Yunqing Wei +1

Steganography refers to the art of concealing secret messages within multiple media carriers so that an eavesdropper is unable to detect the presence and content of the hidden mess…

cs.CR2019★ 142 cited

How to Prove Your Model Belongs to You: A Blind-Watermark based Framework to Protect Intellectual Property of DNN

Zheng Li, Chengyu Hu, Yang Zhang +1

Deep learning techniques have made tremendous progress in a variety of challenging tasks, such as image recognition and machine translation, during the past decade. Training deep n…

cs.CR2018★ 2 cited

DRLGENCERT: Deep Learning-based Automated Testing of Certificate Verification in SSL/TLS Implementations

Chao Chen, Wenrui Diao, Yingpei Zeng +2

The Secure Sockets Layer (SSL) and Transport Layer Security (TLS) protocols are the foundation of network security. The certificate verification in SSL/TLS implementations is vital…