activity
20182023
most citedPOBA-GA: Perturbation Optimized Black-Box Adversarial Attacks via Genetic Algorithm

78 citations · 157 across the 23 of their papers we have counts for

collaborators
Showing 2019Show all

8 papers · 1 filter

cs.SI2019

Time-aware Gradient Attack on Dynamic Network Link Prediction

Jinyin Chen, Jian Zhang, Zhi Chen +2

In network link prediction, it is possible to hide a target link from being predicted with a small perturbation on network structure. This observation may be exploited in many real…

cs.SI2019

Multiscale Evolutionary Perturbation Attack on Community Detection

Jinyin Chen, Yixian Chen, Lihong Chen +2

Community detection, aiming to group nodes based on their connections, plays an important role in network analysis, since communities, treated as meta-nodes, allow us to create a l…

cs.CR2019★ 4 cited

Open DNN Box by Power Side-Channel Attack

Yun Xiang, Zhuangzhi Chen, Zuohui Chen +7

Deep neural networks are becoming popular and important assets of many AI companies. However, recent studies indicate that they are also vulnerable to adversarial attacks. Adversar…

cs.CR2019★ 78 cited

POBA-GA: Perturbation Optimized Black-Box Adversarial Attacks via Genetic Algorithm

Jinyin Chen, Mengmeng Su, Shijing Shen +2

Most deep learning models are easily vulnerable to adversarial attacks. Various adversarial attacks are designed to evaluate the robustness of models and develop defense model. Cur…

cs.SI2019

Unsupervised Euclidean Distance Attack on Network Embedding

Shanqing Yu, Jun Zheng, Jinhuan Wang +6

Considering the wide application of network embedding methods in graph data mining, inspired by the adversarial attack in deep learning, this paper proposes a Genetic Algorithm (GA…

cs.IR2019★ 1 cited

N2VSCDNNR: A Local Recommender System Based on Node2vec and Rich Information Network

Jinyin Chen, Yangyang Wu, Lu Fan +4

Recommender systems are becoming more and more important in our daily lives. However, traditional recommendation methods are challenged by data sparsity and efficiency, as the numb…