{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T10:59:08Z","timestamp":1780657148298,"version":"3.54.1"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,2,11]],"date-time":"2022-02-11T00:00:00Z","timestamp":1644537600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,2,11]]},"DOI":"10.1145\/3488560.3498481","type":"proceedings-article","created":{"date-parts":[[2022,2,15]],"date-time":"2022-02-15T21:42:57Z","timestamp":1644961377000},"page":"591-598","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks"],"prefix":"10.1145","author":[{"given":"Zihan","family":"Liu","sequence":"first","affiliation":[{"name":"Zhejiang University & Westlake University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yun","family":"Luo","sequence":"additional","affiliation":[{"name":"Westlake university, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zelin","family":"Zang","sequence":"additional","affiliation":[{"name":"Westlake University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stan Z.","family":"Li","sequence":"additional","affiliation":[{"name":"Westlake University, Hangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,2,15]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"The isomap algorithm and topological stability. Science 295, 5552","author":"Balasubramanian Mukund","year":"2002","unstructured":"Mukund Balasubramanian, Eric L Schwartz, Joshua B Tenenbaum, Vin de Silva, and John C Langford. 2002. The isomap algorithm and topological stability. Science 295, 5552 (2002), 7--7."},{"key":"e_1_3_2_2_2_1","volume-title":"International Conference on Machine Learning. PMLR, 695--704","author":"Bojchevski Aleksandar","year":"2019","unstructured":"Aleksandar Bojchevski and Stephan G\u00fcnnemann. 2019. Adversarial attacks on node embeddings via graph poisoning. In International Conference on Machine Learning. PMLR, 695--704."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5741"},{"key":"e_1_3_2_2_4_1","volume-title":"International conference on machine learning. PMLR, 1115--1124","author":"Dai Hanjun","year":"2018","unstructured":"Hanjun Dai, Hui Li, Tian Tian, Xin Huang, Lin Wang, Jun Zhu, and Le Song. 2018. Adversarial attack on graph structured data. In International conference on machine learning. PMLR, 1115--1124."},{"key":"e_1_3_2_2_5_1","volume-title":"Convolutional neural networks on graphs with fast localized spectral filtering. arXiv preprint arXiv:1606.09375","author":"Defferrard Micha\u00ebl","year":"2016","unstructured":"Micha\u00ebl Defferrard, Xavier Bresson, and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. arXiv preprint arXiv:1606.09375 (2016)."},{"key":"e_1_3_2_2_6_1","volume-title":"Adversarial Attack on Network Embeddings via Supervised Network Poisoning. arXiv preprint arXiv:2102.07164","author":"Gupta Viresh","year":"2021","unstructured":"Viresh Gupta and Tanmoy Chakraborty. 2021. Adversarial Attack on Network Embeddings via Supervised Network Poisoning. arXiv preprint arXiv:2102.07164 (2021)."},{"key":"e_1_3_2_2_7_1","volume-title":"Inductive representation learning on large graphs. arXiv preprint arXiv:1706.02216","author":"Hamilton William L","year":"2017","unstructured":"William L Hamilton, Rex Ying, and Jure Leskovec. 2017. Inductive representation learning on large graphs. arXiv preprint arXiv:1706.02216 (2017)."},{"key":"e_1_3_2_2_8_1","volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","author":"Kipf Thomas N","year":"2016","unstructured":"Thomas N Kipf and MaxWelling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380171"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3320269.3384750"},{"key":"e_1_3_2_2_11_1","volume-title":"Exploratory Adversarial Attacks on Graph Neural Networks. In 2020 IEEE International Conference on Data Mining (ICDM). IEEE, 1136--1141","author":"Lin Xixun","year":"2020","unstructured":"Xixun Lin, Chuan Zhou, Hong Yang, Jia Wu, Haibo Wang, Yanan Cao, and Bin Wang. 2020. Exploratory Adversarial Attacks on Graph Neural Networks. In 2020 IEEE International Conference on Data Mining (ICDM). IEEE, 1136--1141."},{"key":"e_1_3_2_2_12_1","volume-title":"Towards More Practical Adversarial Attacks on Graph Neural Networks. Advances in neural information processing systems","author":"Ma Jiaqi","year":"2020","unstructured":"Jiaqi Ma, Shuangrui Ding, and Qiaozhu Mei. 2020. Towards More Practical Adversarial Attacks on Graph Neural Networks. Advances in neural information processing systems (2020)."},{"key":"e_1_3_2_2_13_1","volume-title":"Attacking graph convolutional networks via rewiring. arXiv preprint arXiv:1906.03750","author":"Ma Yao","year":"2019","unstructured":"Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, and Jiliang Tang. 2019. Attacking graph convolutional networks via rewiring. arXiv preprint arXiv:1906.03750 (2019)."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009953814988"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.21105\/joss.00861"},{"key":"e_1_3_2_2_16_1","volume-title":"Collective classification in network data. AI magazine 29, 3","author":"Sen Prithviraj","year":"2008","unstructured":"Prithviraj Sen, Galileo Namata, Mustafa Bilgic, Lise Getoor, Brian Galligher, and Tina Eliassi-Rad. 2008. Collective classification in network data. AI magazine 29, 3 (2008), 93--93."},{"key":"e_1_3_2_2_17_1","volume-title":"Node injection attacks on graphs via reinforcement learning. arXiv preprint arXiv:1909.06543","author":"Sun Yiwei","year":"2019","unstructured":"Yiwei Sun, Suhang Wang, Xianfeng Tang, Tsung-Yu Hsieh, and Vasant Honavar. 2019. Node injection attacks on graphs via reinforcement learning. arXiv preprint arXiv:1909.06543 (2019)."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380149"},{"key":"e_1_3_2_2_19_1","article-title":"Visualizing data using t-SNE","volume":"9","author":"der Maaten Laurens Van","year":"2008","unstructured":"Laurens Van der Maaten and Geoffrey Hinton. 2008. Visualizing data using t-SNE. Journal of machine learning research 9, 11 (2008).","journal-title":"Journal of machine learning research"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3354206"},{"key":"e_1_3_2_2_21_1","volume-title":"Attack graph convolutional networks by adding fake nodes. arXiv preprint arXiv:1810.10751","author":"Wang Xiaoyun","year":"2018","unstructured":"Xiaoyun Wang, Minhao Cheng, Joe Eaton, Cho-Jui Hsieh, and Felix Wu. 2018. Attack graph convolutional networks by adding fake nodes. arXiv preprint arXiv:1810.10751 (2018)."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380186"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41562-017-0290-3"},{"key":"e_1_3_2_2_24_1","volume-title":"Adversarial examples on graph data: Deep insights into attack and defense. arXiv preprint arXiv:1903.01610","author":"Tyshetskiy Yuriy","year":"2019","unstructured":"HuijunWu, ChenWang, Yuriy Tyshetskiy, Andrew Docherty, Kai Lu, and Liming Zhu. 2019. Adversarial examples on graph data: Deep insights into attack and defense. arXiv preprint arXiv:1903.01610 (2019)."},{"key":"e_1_3_2_2_25_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"33","author":"Tang Yuyuan","year":"2019","unstructured":"ShuWu, Yuyuan Tang, Yanqiao Zhu, LiangWang, Xing Xie, and Tieniu Tan. 2019. Session-based recommendation with graph neural networks. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 33. 346--353."},{"key":"e_1_3_2_2_26_1","volume-title":"Topology attack and defense for graph neural networks: An optimization perspective. arXiv preprint arXiv:1906.04214","author":"Xu Kaidi","year":"2019","unstructured":"Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, and Xue Lin. 2019. Topology attack and defense for graph neural networks: An optimization perspective. arXiv preprint arXiv:1906.04214 (2019)."},{"key":"e_1_3_2_2_27_1","volume-title":"Adversarial examples: Attacks and defenses for deep learning","author":"Yuan Xiaoyong","year":"2019","unstructured":"Xiaoyong Yuan, Pan He, Qile Zhu, and Xiaolin Li. 2019. Adversarial examples: Attacks and defenses for deep learning. IEEE transactions on neural networks and learning systems 30, 9 (2019), 2805--2824."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2993876"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.01.001"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220078"},{"key":"e_1_3_2_2_31_1","volume-title":"International Conference on Learning Representations.","author":"Z\u00fcgner Daniel","year":"2018","unstructured":"Daniel Z\u00fcgner and Stephan G\u00fcnnemann. 2018. Adversarial Attacks on Graph Neural Networks via Meta Learning. In International Conference on Learning Representations."}],"event":{"name":"WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining","location":"Virtual Event AZ USA","acronym":"WSDM '22","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3488560.3498481","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3488560.3498481","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:31:19Z","timestamp":1750188679000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3488560.3498481"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,11]]},"references-count":31,"alternative-id":["10.1145\/3488560.3498481","10.1145\/3488560"],"URL":"https:\/\/doi.org\/10.1145\/3488560.3498481","relation":{},"subject":[],"published":{"date-parts":[[2022,2,11]]},"assertion":[{"value":"2022-02-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}