{"id":"https://openalex.org/W4401583884","doi":"https://doi.org/10.1145/3688846","title":"On the Inference of Original Graph Information from Graph Embeddings","display_name":"On the Inference of Original Graph Information from Graph Embeddings","publication_year":2024,"publication_date":"2024-08-14","ids":{"openalex":"https://openalex.org/W4401583884","doi":"https://doi.org/10.1145/3688846"},"language":"en","primary_location":{"id":"doi:10.1145/3688846","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3688846","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3688846","source":{"id":"https://openalex.org/S170502224","display_name":"ACM Transactions on Sensor Networks","issn_l":"1550-4859","issn":["1550-4859","1550-4867"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Sensor Networks","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3688846","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100754583","display_name":"Yantao Li","orcid":"https://orcid.org/0000-0001-7648-5671"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yantao Li","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077622002","display_name":"Xinyang Li","orcid":"https://orcid.org/0009-0000-6806-8704"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyang Li","raw_affiliation_strings":["College of Computer Science, Chongqing University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013666525","display_name":"Xinyu Lei","orcid":"https://orcid.org/0000-0001-8799-7875"},"institutions":[{"id":"https://openalex.org/I11957088","display_name":"Michigan Technological University","ror":"https://ror.org/0036rpn28","country_code":"US","type":"education","lineage":["https://openalex.org/I11957088"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinyu Lei","raw_affiliation_strings":["Department of Computer Science, Michigan Technological University, Houghton, United States"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Michigan Technological University, Houghton, United States","institution_ids":["https://openalex.org/I11957088"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054571269","display_name":"Huafeng Qin","orcid":"https://orcid.org/0000-0003-4911-0393"},"institutions":[{"id":"https://openalex.org/I145581781","display_name":"Chongqing Technology and Business University","ror":"https://ror.org/05hqf1284","country_code":"CN","type":"education","lineage":["https://openalex.org/I145581781"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huafeng Qin","raw_affiliation_strings":["School of Computer Science and Information Engineering, Chongqing Technology and Business University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Engineering, Chongqing Technology and Business University, Chongqing, China","institution_ids":["https://openalex.org/I145581781"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101847575","display_name":"Yiwen Hu","orcid":"https://orcid.org/0000-0002-8790-5579"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiwen Hu","raw_affiliation_strings":["Department of Computer Science and Engineering, Michigan State University, East Lansing, United States"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Michigan State University, East Lansing, United States","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054814122","display_name":"Gang Zhou","orcid":"https://orcid.org/0000-0002-4425-9837"},"institutions":[{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]},{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gang Zhou","raw_affiliation_strings":["Computer Science Department, William &amp; Mary, Williamsburg, United States"],"affiliations":[{"raw_affiliation_string":"Computer Science Department, William &amp; Mary, Williamsburg, United States","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100754583"],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11202634,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":"5","first_page":"1","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7602983713150024},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5034489035606384},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5000202655792236},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.49992847442626953},{"id":"https://openalex.org/keywords/graph-database","display_name":"Graph database","score":0.4289237856864929}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7602983713150024},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5034489035606384},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5000202655792236},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.49992847442626953},{"id":"https://openalex.org/C176225458","wikidata":"https://www.wikidata.org/wiki/Q595971","display_name":"Graph database","level":3,"score":0.4289237856864929}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3688846","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3688846","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3688846","source":{"id":"https://openalex.org/S170502224","display_name":"ACM Transactions on Sensor Networks","issn_l":"1550-4859","issn":["1550-4859","1550-4867"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Sensor Networks","raw_type":"journal-article"},{"id":"pmh:oai:digitalcommons.mtu.edu:michigantech-p2-2130","is_oa":false,"landing_page_url":"https://digitalcommons.mtu.edu/michigantech-p2/1130","pdf_url":null,"source":{"id":"https://openalex.org/S4377196391","display_name":"Digital Commons - Michigan Tech (Michigan Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I11957088","host_organization_name":"Michigan Technological University","host_organization_lineage":["https://openalex.org/I11957088"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Michigan Tech Publications","raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3688846","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3688846","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3688846","source":{"id":"https://openalex.org/S170502224","display_name":"ACM Transactions on Sensor Networks","issn_l":"1550-4859","issn":["1550-4859","1550-4867"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Sensor Networks","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3928534416","display_name":null,"funder_award_id":"62072061, 61976030 and U20A20176","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401583884.pdf"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1608718905","https://openalex.org/W1662382123","https://openalex.org/W1888005072","https://openalex.org/W2006829201","https://openalex.org/W2040211532","https://openalex.org/W2112796928","https://openalex.org/W2138399168","https://openalex.org/W2153803020","https://openalex.org/W2154851992","https://openalex.org/W2186222003","https://openalex.org/W2471554257","https://openalex.org/W2612445135","https://openalex.org/W2750384547","https://openalex.org/W2758068744","https://openalex.org/W2767613317","https://openalex.org/W2768308213","https://openalex.org/W2798724621","https://openalex.org/W2806331055","https://openalex.org/W2962711740","https://openalex.org/W2962756421","https://openalex.org/W2962833907","https://openalex.org/W2963101956","https://openalex.org/W2963622436","https://openalex.org/W2970183009","https://openalex.org/W2970535055","https://openalex.org/W2982802130","https://openalex.org/W3004507689","https://openalex.org/W3015616869","https://openalex.org/W3031478966","https://openalex.org/W3083690005","https://openalex.org/W3091473186","https://openalex.org/W3100330855","https://openalex.org/W3103513278","https://openalex.org/W3104097132","https://openalex.org/W3184900565","https://openalex.org/W3189551349","https://openalex.org/W3215430231","https://openalex.org/W4230692091","https://openalex.org/W4236965008","https://openalex.org/W4283810514","https://openalex.org/W4283810673","https://openalex.org/W4285727651","https://openalex.org/W4293088673","https://openalex.org/W4297775537","https://openalex.org/W4303426745","https://openalex.org/W4312581915","https://openalex.org/W4319663821","https://openalex.org/W4367394480","https://openalex.org/W4392561312","https://openalex.org/W6754929296"],"related_works":["https://openalex.org/W3149439221","https://openalex.org/W4287763734","https://openalex.org/W3115442681","https://openalex.org/W3035116611","https://openalex.org/W2007838763","https://openalex.org/W2391000461","https://openalex.org/W2972311463","https://openalex.org/W3211302945","https://openalex.org/W2932872266","https://openalex.org/W4312932141"],"abstract_inverted_index":{"Graph":[0],"embedding":[1,90,191],"converts":[2],"a":[3,7,68,148],"graph":[4,15,18,32,45,51,54,60,64,84,89,111,186,190],"data":[5,19,52],"into":[6],"low":[8],"dimensional":[9],"space":[10],"to":[11,26,37,80,102,127],"preserve":[12],"the":[13,43,49,58,82,96,104,109,117,142,155,163,168,176,184,189],"original":[14,44,50,59,83,110,185],"information.":[16],"However,":[17],"can":[20,47,75,182],"be":[21,76],"reconstructed":[22],"by":[23,78],"malicious":[24],"adversaries":[25,79],"train":[27],"machine":[28],"learning":[29],"models":[30],"from":[31,53,63,86,188],"embeddings.":[33,55],"This":[34],"paper":[35],"studies":[36],"what":[38],"extent":[39],"an":[40,87,129],"adversary":[41],"(without":[42],"data)":[46],"recover":[48],"To":[56,115,139],"quantify":[57],"information":[61,85,187],"leakage":[62],"embeddings,":[65],"we":[66,94,121,146],"develop":[67],"deep":[69],"neural":[70],"network":[71],"model":[72],"InferNet":[73,105,133,171,181],"that":[74,152,180],"used":[77],"infer":[81,183],"adversary-accessible":[88],"database.":[91],"More":[92],"specifically,":[93],"propose":[95],"data-free":[97],"reversed":[98],"knowledge":[99],"distillation":[100],"technique":[101],"support":[103],"training":[106,131,150],"even":[107],"if":[108],"dataset":[112,192],"is":[113],"absent.":[114],"ensure":[116],"performance":[118,143,169],"of":[119,132,137,144,170],"InferNet,":[120,145,159],"design":[122],"two":[123],"cycle-consistency":[124],"loss":[125],"functions":[126],"have":[128],"interactive":[130],"over":[134],"three":[135,173],"series":[136],"datasets.":[138],"further":[140],"enhance":[141],"provide":[147],"joint":[149],"algorithm":[151],"simultaneously":[153],"trains":[154],"pseudo-sample":[156],"generator":[157],"and":[158,175],"which":[160],"significantly":[161],"reduces":[162],"storage":[164],"space.":[165],"We":[166],"evaluate":[167],"on":[172],"datasets,":[174],"intensive":[177],"experiments":[178],"demonstrate":[179],"with":[193],"high":[194],"accuracy.":[195]},"counts_by_year":[],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
