{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:56:19Z","timestamp":1777892179562,"version":"3.51.4"},"reference-count":39,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFB1805603"],"award-info":[{"award-number":["2020YFB1805603"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computer Networks"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.comnet.2026.112075","type":"journal-article","created":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T00:28:00Z","timestamp":1769819280000},"page":"112075","update-policy":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Graph-based fast-flux domain detection using graph neural networks"],"prefix":"10.1016","volume":"278","author":[{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0000-0001-9391-9603","authenticated-orcid":false,"given":"Wei","family":"Xiong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0000-0002-2650-2725","authenticated-orcid":false,"given":"Yang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0009-0004-4373-5717","authenticated-orcid":false,"given":"Haiyang","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0009-0007-3290-4767","authenticated-orcid":false,"given":"Hongtao","family":"Guan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.comnet.2026.112075_bib0001","doi-asserted-by":"crossref","DOI":"10.1016\/j.comnet.2020.107699","article-title":"Domain name system security and privacy: a contemporary survey","volume":"185","author":"Khormali","year":"2021","journal-title":"Comput. Netw."},{"key":"10.1016\/j.comnet.2026.112075_bib0002","series-title":"ACM Symposium on Information, Computer and Communications Security (ICICS)","first-page":"101","article-title":"Fast-flux service network detection based on spatial snapshot mechanism for delay-free detection","author":"Huang","year":"2010"},{"issue":"1","key":"10.1016\/j.comnet.2026.112075_bib0003","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1504\/IJAHUC.2021.112981","article-title":"Botnet detection used fast-flux technique, based on adaptive dynamic evolving spiking neural network algorithm","volume":"36","author":"Almomani","year":"2021","journal-title":"INT. J. AD. HOC. UBIQ. CO"},{"issue":"4","key":"10.1016\/j.comnet.2026.112075_bib0004","first-page":"1061","article-title":"Detecting malicious fast-Flux domains using feature-based classification techniques","volume":"21","author":"Truong","year":"2020","journal-title":"J. Internet. Technol"},{"key":"10.1016\/j.comnet.2026.112075_bib0005","series-title":"International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment (DIMVA)","first-page":"186","article-title":"Fluxor: detecting and monitoring fast-flux service networks","author":"Passerini","year":"2008"},{"key":"10.1016\/j.comnet.2026.112075_bib0006","article-title":"A machine learning approach for detecting fast flux phishing hostnames","volume":"65","author":"Nagunwa","year":"2022","journal-title":"J. Inf. Secur. Appl."},{"key":"10.1016\/j.comnet.2026.112075_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.cose.2021.102431","article-title":"PASSVM: A highly accurate fast flux detection system","volume":"110","author":"Al-Duwairi","year":"2021","journal-title":"Comput. Secur."},{"key":"10.1016\/j.comnet.2026.112075_bib0008","series-title":"Technical Report","article-title":"How powerful are graph neural networks?","author":"Xu","year":"2018"},{"key":"10.1016\/j.comnet.2026.112075_bib0009","series-title":"Technical Report","article-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2016"},{"key":"10.1016\/j.comnet.2026.112075_bib0010","series-title":"Technical Report","article-title":"Graph attention networks","author":"Veli\u010dkovi\u0107","year":"2017"},{"key":"10.1016\/j.comnet.2026.112075_bib0011","article-title":"An end-to-end deep learning architecture for graph classification","volume":"32","author":"Zhang","year":"2018","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.comnet.2026.112075_bib0012","series-title":"Conference on Neural Information Processing System (NeurIPS)","first-page":"31","article-title":"Hierarchical graph representation learning with differentiable pooling","author":"Ying","year":"2018"},{"key":"10.1016\/j.comnet.2026.112075_bib0013","series-title":"International Conference on Machine Learning (ICML)","first-page":"2083","article-title":"Graph u-nets","author":"Gao","year":"2019"},{"key":"10.1016\/j.comnet.2026.112075_bib0014","series-title":"International Conference on Machine Learning (ICML)","first-page":"3734","article-title":"Self-attention graph pooling","author":"Lee","year":"2019"},{"key":"10.1016\/j.comnet.2026.112075_bib0015","series-title":"Conference on Neural Information Processing System (NeurIPS)","first-page":"30","article-title":"Inductive representation learning on large graphs","author":"Hamilton","year":"2017"},{"key":"10.1016\/j.comnet.2026.112075_bib0016","series-title":"ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD)","first-page":"974","article-title":"Graph convolutional neural networks for web-scale recommender systems","author":"Ying","year":"2018"},{"key":"10.1016\/j.comnet.2026.112075_bib0017","series-title":"International Conference on Malicious and Unwanted Software (MALWARE)","first-page":"24","article-title":"As the net churns: fast-flux botnet observations","author":"Nazario","year":"2008"},{"key":"10.1016\/j.comnet.2026.112075_bib0018","series-title":"Cybersecurity Applications & Technology Conference for Homeland Security","first-page":"285","article-title":"Real-time detection of fast flux service networks","author":"Caglayan","year":"2009"},{"key":"10.1016\/j.comnet.2026.112075_bib0019","series-title":"International Symposium on Recent Advances in Intrusion Detection","first-page":"464","article-title":"Fast-flux bot detection in real time","author":"Hsu","year":"2010"},{"issue":"7","key":"10.1016\/j.comnet.2026.112075_bib0020","doi-asserted-by":"crossref","first-page":"483","DOI":"10.1007\/s00521-016-2531-1","article-title":"Fast-flux hunter: a system for filtering online fast-flux botnet","volume":"29","author":"Almomani","year":"2018","journal-title":"Neural. Comput. Appl."},{"key":"10.1016\/j.comnet.2026.112075_bib0021","series-title":"IEEE Conference on Communications and Network Security (CNS)","first-page":"755","article-title":"GFlux: A google-based system for fast flux detection","author":"Al-Duwairi","year":"2015"},{"issue":"9","key":"10.1016\/j.comnet.2026.112075_bib0022","doi-asserted-by":"crossref","first-page":"1490","DOI":"10.1587\/transinf.2022OFL0002","article-title":"Malicious domain detection based on decision tree","volume":"106","author":"Thein","year":"2023","journal-title":"IEICE. T. Inf. Syst."},{"key":"10.1016\/j.comnet.2026.112075_bib0023","series-title":"International Conference on Critical Information Infrastructures Security (CRITIS)","first-page":"69","article-title":"Finding fast flux traffic in DNS haystack","author":"Surjanto","year":"2020"},{"key":"10.1016\/j.comnet.2026.112075_bib0024","doi-asserted-by":"crossref","DOI":"10.1016\/j.cose.2023.103260","article-title":"DDOFM: Dynamic malicious domain detection method based on feature mining","volume":"130","author":"Wang","year":"2023","journal-title":"Comput. Secur."},{"key":"10.1016\/j.comnet.2026.112075_bib0025","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TCSS.2025.3635735","article-title":"A scalable multichannel sentiment analysis model with enhanced semantic understanding and redundancy reduction","volume":"99","author":"Liu","year":"2025","journal-title":"IEEE Trans. Comput. Soc. Syst."},{"key":"10.1016\/j.comnet.2026.112075_bib0026","doi-asserted-by":"crossref","DOI":"10.1016\/j.cose.2020.102057","article-title":"Deepdom: malicious domain detection with scalable and heterogeneous graph convolutional networks","volume":"99","author":"Sun","year":"2020","journal-title":"Comput. Secur."},{"key":"10.1016\/j.comnet.2026.112075_bib0027","series-title":"International Performance Computing and Communications Conference (IPCCC)","first-page":"1","article-title":"Malicious domain detection via domain relationship and graph models","author":"He","year":"2019"},{"key":"10.1016\/j.comnet.2026.112075_bib0028","series-title":"IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD)","first-page":"397","article-title":"Attributed heterogeneous graph neural network for malicious domain detection","author":"Zhang","year":"2021"},{"key":"10.1016\/j.comnet.2026.112075_bib0029","series-title":"International Conference on Wireless Algorithms, Systems, and Applications","first-page":"545","article-title":"Malicious domain detection with heterogeneous graph propagation network","author":"Hu","year":"2022"},{"key":"10.1016\/j.comnet.2026.112075_bib0030","series-title":"Conference on Neural Information Processing System (NeurIPS)","first-page":"30","article-title":"Protein interface prediction using graph convolutional networks","author":"Fout","year":"2017"},{"issue":"1","key":"10.1016\/j.comnet.2026.112075_bib0031","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1093\/bioinformatics\/btac759","article-title":"Deeprank-GNN: a graph neural network framework to learn patterns in protein-protein interfaces","volume":"39","author":"R\u00e9au","year":"2023","journal-title":"Bioinformatics"},{"key":"10.1016\/j.comnet.2026.112075_bib0032","series-title":"IEEE International Conference on Computer Communications (INFOCOM)","first-page":"2633","article-title":"Measurement and analysis of global IP-usage patterns of fast-flux botnets","author":"Hu","year":"2011"},{"key":"10.1016\/j.comnet.2026.112075_bib0033","year":"2023"},{"key":"10.1016\/j.comnet.2026.112075_bib0034","series-title":"Artists Against 419: Fake Sites List","year":"2023"},{"key":"10.1016\/j.comnet.2026.112075_bib0035","year":"2023"},{"key":"10.1016\/j.comnet.2026.112075_bib0036","series-title":"Fighting Malware and Cyber Criminality","author":"Malwareurl","year":"2023"},{"key":"10.1016\/j.comnet.2026.112075_bib0037","author":"Weibu"},{"key":"10.1016\/j.comnet.2026.112075_bib0040","series-title":"Cisco Umbrella Top 1 Million Domain","author":"Cisco","year":"2023"},{"key":"10.1016\/j.comnet.2026.112075_bib0041","author":"Github"}],"container-title":["Computer Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S1389128626000873?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S1389128626000873?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T06:22:34Z","timestamp":1777616554000},"score":1,"resource":{"primary":{"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/linkinghub.elsevier.com\/retrieve\/pii\/S1389128626000873"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":39,"alternative-id":["S1389128626000873"],"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/doi.org\/10.1016\/j.comnet.2026.112075","relation":{},"ISSN":["1389-1286"],"issn-type":[{"value":"1389-1286","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Graph-based fast-flux domain detection using graph neural networks","name":"articletitle","label":"Article Title"},{"value":"Computer Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/doi.org\/10.1016\/j.comnet.2026.112075","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"112075"}}