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Phishing behavior detection on different blockchains via adversarial domain adaptation 认领 引用 被引量：1
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作者 Chuyi Yan Xueying Han +3 位作者 Yan Zhu Dan Du Zhigang Lu Yuling Liu 《Cybersecurity》 EI CSCD 2025年第3期244-265,共22页
Despite the growing attention on blockchain,phishing activities have surged,particularly on newly established chains.Acknowledging the challenge of limited intelligence in the early stages of new chains,we propose ADA... Despite the growing attention on blockchain,phishing activities have surged,particularly on newly established chains.Acknowledging the challenge of limited intelligence in the early stages of new chains,we propose ADA-Spearan automatic phishing detection model utilizing adversarial domain adaptive learning which symbolizes the method’s ability to penetrate various heterogeneous blockchains for phishing detection.The model effectively identifies phishing behavior in new chains with limited reliable labels,addressing challenges such as significant distribution drift,low attribute overlap,and limited inter-chain connections.Our approach includes a subgraph construction strategy to align heterogeneous chains,a layered deep learning encoder capturing both temporal and spatial information,and integrated adversarial domain adaptive learning in end-to-end model training.Validation in Ethereum,Bitcoin,and EOSIO environments demonstrates ADA-Spear’s effectiveness,achieving an average F1 score of 77.41 on new chains after knowledge transfer,surpassing existing detection methods. 展开更多
关键词 Blockchain Phishing detection Adversarial domain adaptation Graphetwork transfer learning Hierarchical graph attention Network security
Identifying the skeptics and the undecided through visual cluster analysis of local network geometry 认领 引用 被引量：1
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作者 Shenghui Cheng Joachim Giesen +2 位作者 Tianyi Huang Philipp Lucas Klaus Mueller 《Visual Informatics》 EI 2022年第3期11-22,共12页
By skeptics and undecided we refer to nodes in clustered social networks that cannot be assigned easily to any of the clusters.Such nodes are typically found either at the interface between clusters(the undecided)or a... By skeptics and undecided we refer to nodes in clustered social networks that cannot be assigned easily to any of the clusters.Such nodes are typically found either at the interface between clusters(the undecided)or at their boundaries(the skeptics).Identifying these nodes is relevant in marketing applications like voter targeting,because the persons represented by such nodes are often more likely to be affected in marketing campaigns than nodes deeply within clusters.So far this identification task is not as well studied as other network analysis tasks like clustering,identifying central nodes,and detecting motifs.We approach this task by deriving novel geometric features from the network structure that naturally lend themselves to an interactive visual approach for identifying interface and boundary nodes. 展开更多
关键词 Graphetwork data High dimensional data visualization Visualization in social and information sciences Data clustering coordinated and multiple views
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