60 citations · 307 across the 18 of their papers we have counts for
19 papers
Unveiling the Potential of Knowledge-Prompted ChatGPT for Enhancing Drug Trafficking Detection on Social Media
Chuanbo Hu, Bin Liu, Xin Li +1
Social media platforms such as Instagram and Twitter have emerged as critical channels for drug marketing and illegal sale. Detecting and labeling online illicit drug trafficking a…
Graph Mining for Cybersecurity: A Survey
Bo Yan, Cheng Yang, Chuan Shi +4
The explosive growth of cyber attacks nowadays, such as malware, spam, and intrusions, caused severe consequences on society. Securing cyberspace has become an utmost concern for o…
Disentangled Spatiotemporal Graph Generative Models
Yuanqi Du, Xiaojie Guo, Hengning Cao +2
Spatiotemporal graph represents a crucial data structure where the nodes and edges are embedded in a geometric space and can evolve dynamically over time. Nowadays, spatiotemporal…
Black-box Node Injection Attack for Graph Neural Networks
Mingxuan Ju, Yujie Fan, Yanfang Ye +1
Graph Neural Networks (GNNs) have drawn significant attentions over the years and been broadly applied to vital fields that require high security standard such as product recommend…
Adaptive Kernel Graph Neural Network
Mingxuan Ju, Shifu Hou, Yujie Fan +3
Graph neural networks (GNNs) have demonstrated great success in representation learning for graph-structured data. The layer-wise graph convolution in GNNs is shown to be powerful…
Heterogeneous Temporal Graph Neural Network
Yujie Fan, Mingxuan Ju, Chuxu Zhang +2
Graph neural networks (GNNs) have been broadly studied on dynamic graphs for their representation learning, majority of which focus on graphs with homogeneous structures in the spa…
Knowledge-aware Coupled Graph Neural Network for Social Recommendation
Chao Huang, Huance Xu, Yong Xu +7
Social recommendation task aims to predict users' preferences over items with the incorporation of social connections among users, so as to alleviate the sparse issue of collaborat…
Detection of Illicit Drug Trafficking Events on Instagram: A Deep Multimodal Multilabel Learning Approach
Chuanbo Hu, Minglei Yin, Bin Liu +2
Social media such as Instagram and Twitter have become important platforms for marketing and selling illicit drugs. Detection of online illicit drug trafficking has become critical…
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources
Xiao Wang, Deyu Bo, Chuan Shi +3
Heterogeneous graphs (HGs) also known as heterogeneous information networks have become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn representat…
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement
Xiaojie Guo, Liang Zhao, Zhao Qin +3
Disentangled representation learning has recently attracted a significant amount of attention, particularly in the field of image representation learning. However, learning the dis…
Arms Race in Adversarial Malware Detection: A Survey
Deqiang Li, Qianmu Li, Yanfang Ye +1
Malicious software (malware) is a major cyber threat that has to be tackled with Machine Learning (ML) techniques because millions of new malware examples are injected into cybersp…
A Framework for Enhancing Deep Neural Networks Against Adversarial Malware
Deqiang Li, Qianmu Li, Yanfang Ye +1
Machine learning-based malware detection is known to be vulnerable to adversarial evasion attacks. The state-of-the-art is that there are no effective defenses against these attack…
-Satellite: An AI-driven System and Benchmark Datasets for Hierarchical Community-level Risk Assessment to Help Combat COVID-19
Yanfang Ye, Shifu Hou, Yujie Fan +5
The novel coronavirus and its deadly outbreak have posed grand challenges to human society: as of March 26, 2020, there have been 85,377 confirmed cases and 1,293 reported deaths i…
Hyperbolic Graph Attention Network
Yiding Zhang, Xiao Wang, Xunqiang Jiang +2
Graph neural network (GNN) has shown superior performance in dealing with graphs, which has attracted considerable research attention recently. However, most of the existing GNN mo…
Joint Demosaicing and Super-Resolution (JDSR): Network Design and Perceptual Optimization
Xuan Xu, Yanfang Ye, Xin Li
Image demosaicing and super-resolution are two important tasks in color imaging pipeline. So far they have been mostly independently studied in the open literature of deep learning…
Temporal Network Embedding with Micro- and Macro-dynamics
Yuanfu Lu, Xiao Wang, Chuan Shi +2
Network embedding aims to embed nodes into a low-dimensional space, while capturing the network structures and properties. Although quite a few promising network embedding methods…
Heterogeneous Graph Attention Network
Xiao Wang, Houye Ji, Chuan Shi +4
Graph neural network, as a powerful graph representation technique based on deep learning, has shown superior performance and attracted considerable research interest. However, it…
Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples: Principles, Framework, and AICS'2019 Challenge
Deqiang Li, Qianmu Li, Yanfang Ye +1
Malware continues to be a major cyber threat, despite the tremendous effort that has been made to combat them. The number of malware in the wild steadily increases over time, meani…
AiDroid: When Heterogeneous Information Network Marries Deep Neural Network for Real-time Android Malware Detection
Yanfang Ye, Shifu Hou, Lingwei Chen +5
The explosive growth and increasing sophistication of Android malware call for new defensive techniques that are capable of protecting mobile users against novel threats. In this p…