K
Kejiang Chen
Researcher at University of Science and Technology of China
Publications - 62
Citations - 684
Kejiang Chen is an academic researcher from University of Science and Technology of China. The author has contributed to research in topics: Steganography & Computer science. The author has an hindex of 10, co-authored 39 publications receiving 334 citations.
Papers
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Proceedings ArticleDOI
DUP-Net: Denoiser and Upsampler Network for 3D Adversarial Point Clouds Defense
TL;DR: A Denoiser and UPsampler Network (DUP-Net) structure as defenses for 3D adversarial point cloud classification, where the two modules reconstruct surface smoothness by dropping or adding points.
Proceedings ArticleDOI
Adversarial Examples Against Deep Neural Network based Steganalysis
TL;DR: A new strategy is proposed that constructs enhanced covers against neural networks with the technique of adversarial examples and makes a tradeoff between the two analysis systems to improve the comprehensive security.
Proceedings ArticleDOI
LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud Based Deep Networks
Hang Zhou,Dongdong Chen,Jing Liao,Kejiang Chen,Xiaoyi Dong,Kunlin Liu,Weiming Zhang,Gang Hua,Nenghai Yu +8 more
TL;DR: The proposed LG-GAN can support flexible targeted attack on the fly while guaranteeing good attack performance and higher efficiency simultaneously, and is the first generation based 3D point cloud attack method.
Journal ArticleDOI
Reversible Data Hiding in Color Image With Grayscale Invariance
TL;DR: The unchanged gray version is utilized efficiently in both the embedding processes and the extracting processes, and the reversibility and the property of grayscale invariance are both achieved.
Journal ArticleDOI
Robust adaptive steganography based on generalized dither modulation and expanded embedding domain
TL;DR: The purpose of this paper is to refine the robust steganographic scheme by considering asymmetric costs for different modification polarities and expanding the embedding domain for digital images, aiming to aggregate the modifications on the elements with small costs.