{"id":"https://openalex.org/W2420927655","doi":"https://doi.org/10.1145/2882903.2882956","title":"Privacy Preserving Subgraph Matching on Large Graphs in Cloud","display_name":"Privacy Preserving Subgraph Matching on Large Graphs in Cloud","publication_year":2016,"publication_date":"2016-06-14","ids":{"openalex":"https://openalex.org/W2420927655","doi":"https://doi.org/10.1145/2882903.2882956","mag":"2420927655"},"language":"en","primary_location":{"id":"doi:10.1145/2882903.2882956","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2882903.2882956","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 International Conference on Management of Data","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101789729","display_name":"Zhao Chang","orcid":"https://orcid.org/0000-0002-6846-7614"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Zhao Chang","raw_affiliation_strings":["Peking University; University of Utah, Beijing, China","Peking University"],"affiliations":[{"raw_affiliation_string":"Peking University; University of Utah, Beijing, China","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I223532165"]},{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033785339","display_name":"Lei Zou","orcid":"https://orcid.org/0000-0002-8586-4400"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zou","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100450462","display_name":"Li Fei-Fei","orcid":"https://orcid.org/0000-0002-7481-0810"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feifei Li","raw_affiliation_strings":["University of Utah, Salt Lake City, USA"],"affiliations":[{"raw_affiliation_string":"University of Utah, Salt Lake City, USA","institution_ids":["https://openalex.org/I223532165"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101789729"],"corresponding_institution_ids":["https://openalex.org/I20231570","https://openalex.org/I223532165"],"apc_list":null,"apc_paid":null,"fwci":4.7132,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.95300411,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"199","last_page":"213"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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/T10237","display_name":"Cryptography and Data Security","score":0.9979000091552734,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9923999905586243,"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":0.8206855058670044},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5743182897567749},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5217046141624451},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5204553604125977},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4626069962978363},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4610859751701355},{"id":"https://openalex.org/keywords/subgraph-isomorphism-problem","display_name":"Subgraph isomorphism problem","score":0.4471898674964905},{"id":"https://openalex.org/keywords/graph-factorization","display_name":"Graph factorization","score":0.443955659866333},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.334189772605896},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3232879042625427},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.14285597205162048},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12742933630943298},{"id":"https://openalex.org/keywords/graph-power","display_name":"Graph power","score":0.08073395490646362}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8206855058670044},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5743182897567749},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5217046141624451},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5204553604125977},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4626069962978363},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4610859751701355},{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.4471898674964905},{"id":"https://openalex.org/C128115575","wikidata":"https://www.wikidata.org/wiki/Q5597083","display_name":"Graph factorization","level":5,"score":0.443955659866333},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.334189772605896},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3232879042625427},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.14285597205162048},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12742933630943298},{"id":"https://openalex.org/C149530733","wikidata":"https://www.wikidata.org/wiki/Q5597091","display_name":"Graph power","level":4,"score":0.08073395490646362},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2882903.2882956","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2882903.2882956","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 International Conference on Management of Data","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W56293434","https://openalex.org/W1873763122","https://openalex.org/W1896160955","https://openalex.org/W1991514581","https://openalex.org/W1998091733","https://openalex.org/W2017509273","https://openalex.org/W2026160696","https://openalex.org/W2032186932","https://openalex.org/W2085472312","https://openalex.org/W2096296626","https://openalex.org/W2100080493","https://openalex.org/W2102415185","https://openalex.org/W2111607365","https://openalex.org/W2118212234","https://openalex.org/W2124849257","https://openalex.org/W2128248866","https://openalex.org/W2131785201","https://openalex.org/W2138682683","https://openalex.org/W2144143615","https://openalex.org/W2151961366","https://openalex.org/W2153752762","https://openalex.org/W2159024459","https://openalex.org/W2168433392","https://openalex.org/W2241555812","https://openalex.org/W6639805184"],"related_works":["https://openalex.org/W1512756268","https://openalex.org/W2393701947","https://openalex.org/W2886672068","https://openalex.org/W1887488684","https://openalex.org/W2953496651","https://openalex.org/W2532922352","https://openalex.org/W1739013558","https://openalex.org/W167435155","https://openalex.org/W3208942821","https://openalex.org/W4300773579"],"abstract_inverted_index":{"The":[0,53,177],"wide":[1],"presence":[2],"of":[3,11,93,104,126,181],"large":[4],"graph":[5,21,81,87,121],"data":[6,13],"and":[7,63,133,179],"the":[8,15,18,58,91,105,137,143,157,172],"increasing":[9],"popularity":[10],"storing":[12],"in":[14,49,107,136],"cloud":[16,51,62,138],"drive":[17],"needs":[19],"for":[20,66,160],"query":[22,114,134,144],"processing":[23],"on":[24,44,60,190],"a":[25,29,50,84,108,111,120,123,161,167],"remote":[26],"cloud.":[27],"But":[28],"fundamental":[30],"challenge":[31],"is":[32,55],"to":[33,56,146,170],"process":[34],"user":[35],"queries":[36],"without":[37,69],"compromising":[38,70],"sensitive":[39,72],"information.":[40,73],"This":[41,128],"work":[42],"focuses":[43],"privacy":[45,85,96],"preserving":[46,86],"subgraph":[47,67,112,162],"matching":[48,113,163],"server.":[52,139],"goal":[54],"minimize":[57],"overhead":[59],"both":[61,131],"client":[64],"sides":[65],"matching,":[68],"users'":[71],"To":[74,155],"that":[75],"end,":[76],"we":[77,165],"transform":[78],"an":[79,94],"original":[80],"$G$":[82],"into":[83],"Gk,":[88],"which":[89],"meets":[90],"requirement":[92],"existing":[95],"model":[97,169],"known":[98],"as":[99],"k-automorphism.":[100],"By":[101],"making":[102],"use":[103],"symmetry":[106],"k-automorphic":[109],"graph,":[110],"can":[115],"be":[116],"efficiently":[117],"answered":[118],"using":[119,151],"Go,":[122],"small":[124],"subset":[125],"Gk.":[127],"approach":[129],"saves":[130],"space":[132,159],"cost":[135,168],"We":[140],"also":[141],"anonymize":[142],"graphs":[145],"protect":[147],"their":[148],"label":[149,152,175],"information":[150],"generalization":[153],"technique.":[154],"reduce":[156],"search":[158],"query,":[164],"propose":[166],"select":[171],"more":[173],"effective":[174],"combinations.":[176],"effectiveness":[178],"efficiency":[180],"our":[182],"method":[183],"are":[184],"demonstrated":[185],"through":[186],"extensive":[187],"experimental":[188],"results":[189],"real":[191],"datasets.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}