{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T03:37:52Z","timestamp":1782790672572,"version":"3.54.5"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>Recently, Graph Neural Network (GNN) has achieved remarkable progresses in various real-world tasks on graph data, consisting of node features and the adjacent information between different nodes. High-performance GNN models always depend on both rich features and complete edge information in graph. However, such information could possibly be isolated by different data holders in practice, which is the so-called data isolation problem. To solve this problem, in this paper, we propose VFGNN, a federated GNN learning paradigm for privacy-preserving node classification task under data vertically partitioned setting, which can be generalized to existing GNN models. Specifically, we split the computation graph into two parts. We leave the private data (i.e., features, edges, and labels) related computations on data holders, and delegate the rest of computations to a semi-honest server. We also propose to apply differential privacy to prevent potential information leakage from the server. We conduct experiments on three benchmarks and the results demonstrate the effectiveness of VFGNN.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/272","type":"proceedings-article","created":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T02:55:56Z","timestamp":1657940156000},"page":"1959-1965","source":"Crossref","is-referenced-by-count":48,"title":["Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification"],"prefix":"10.24963","author":[{"given":"Chaochao","family":"Chen","sequence":"first","affiliation":[{"name":"Zhejiang University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Zhou","sequence":"additional","affiliation":[{"name":"Zhejiang University"},{"name":"Ant Group"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longfei","family":"Zheng","sequence":"additional","affiliation":[{"name":"Ant Group"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huiwen","family":"Wu","sequence":"additional","affiliation":[{"name":"Ant Group"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingjuan","family":"Lyu","sequence":"additional","affiliation":[{"name":"Sony AI"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia","family":"Wu","sequence":"additional","affiliation":[{"name":"Macquarie University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bingzhe","family":"Wu","sequence":"additional","affiliation":[{"name":"Peking University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziqi","family":"Liu","sequence":"additional","affiliation":[{"name":"Ant Group"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Wang","sequence":"additional","affiliation":[{"name":"Ant Group"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolin","family":"Zheng","sequence":"additional","affiliation":[{"name":"Zhejiang University"},{"name":"JZTData Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","theme":"Artificial Intelligence","location":"Vienna, Austria","acronym":"IJCAI-2022","number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2022,7,23]]},"end":{"date-parts":[[2022,7,29]]}},"container-title":["Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T11:08:44Z","timestamp":1658142524000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/272"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2022\/272","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}