{"id":"https://openalex.org/W4406461651","doi":"https://doi.org/10.1109/bigdata62323.2024.10825799","title":"Leveraging Graph Clustering for Differentially Private Graph Neural Networks","display_name":"Leveraging Graph Clustering for Differentially Private Graph Neural Networks","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406461651","doi":"https://doi.org/10.1109/bigdata62323.2024.10825799"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5115940193","display_name":"Sager Kudrick","orcid":null},"institutions":[{"id":"https://openalex.org/I186803428","display_name":"Brock University","ror":"https://ror.org/056am2717","country_code":"CA","type":"education","lineage":["https://openalex.org/I186803428"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Sager Kudrick","raw_affiliation_strings":["Brock University,Computer Science Department,Canada"],"affiliations":[{"raw_affiliation_string":"Brock University,Computer Science Department,Canada","institution_ids":["https://openalex.org/I186803428"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078237873","display_name":"Renata Dividino","orcid":null},"institutions":[{"id":"https://openalex.org/I186803428","display_name":"Brock University","ror":"https://ror.org/056am2717","country_code":"CA","type":"education","lineage":["https://openalex.org/I186803428"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Renata Dividino","raw_affiliation_strings":["Brock University,Computer Science Department,Canada"],"affiliations":[{"raw_affiliation_string":"Brock University,Computer Science Department,Canada","institution_ids":["https://openalex.org/I186803428"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5115940193"],"corresponding_institution_ids":["https://openalex.org/I186803428"],"apc_list":null,"apc_paid":null,"fwci":0.3637,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.70880754,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"8731","last_page":"8733"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9984999895095825,"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":0.998199999332428,"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":0.7043935060501099},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5576663017272949},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5051572918891907},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35066673159599304},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.343061625957489}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7043935060501099},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5576663017272949},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5051572918891907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35066673159599304},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.343061625957489}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1873763122","https://openalex.org/W2070232376","https://openalex.org/W2473418344","https://openalex.org/W2900470550","https://openalex.org/W2945827377","https://openalex.org/W2964015378","https://openalex.org/W3101553402","https://openalex.org/W3196012972","https://openalex.org/W4297733535","https://openalex.org/W4308641868","https://openalex.org/W4313484456","https://openalex.org/W4318812505","https://openalex.org/W4362496271","https://openalex.org/W4384389844","https://openalex.org/W4392384795","https://openalex.org/W4396736342","https://openalex.org/W6699364125","https://openalex.org/W6726873649","https://openalex.org/W6754929296","https://openalex.org/W6756561102","https://openalex.org/W6790497228","https://openalex.org/W6804928337","https://openalex.org/W6810023037","https://openalex.org/W6849241315","https://openalex.org/W6854323709"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Differential":[0],"Privacy":[1],"is":[2,16,99,177],"a":[3,49,66,136],"standard":[4],"approach":[5,176],"for":[6,138],"ensuring":[7],"privacy":[8,64,166,198],"in":[9],"deep":[10],"learning":[11],"models,":[12],"but":[13,124],"its":[14],"effectiveness":[15],"less":[17],"certain":[18],"when":[19],"applied":[20],"to":[21,56,116,129,131],"message-passing":[22],"Graph":[23],"Neural":[24],"Networks":[25],"(GNNs).":[26],"GNNs,":[27],"which":[28,183],"process":[29],"graph-structured":[30],"data,":[31,93,194],"generate":[32],"node":[33,121],"representations":[34],"by":[35,88,142,179],"aggregating":[36],"information":[37,47,75],"from":[38,120,146],"neighboring":[39],"nodes.":[40],"At":[41],"the":[42,63,92,96,147,152,165,192],"k-th":[43],"layer,":[44],"GNNs":[45],"propagate":[46],"across":[48],"node\u2019s":[50],"k-hop":[51],"neighborhood,":[52],"causing":[53],"interconnected":[54],"nodes":[55,169],"influence":[57],"each":[58,156],"other\u2019s":[59],"representations.":[60],"Consequently,":[61],"protecting":[62],"of":[65,167],"single":[67],"node,":[68],"edge,":[69],"or":[70],"feature":[71],"often":[72,127],"requires":[73],"safeguarding":[74],"about":[76],"related":[77],"graph":[78,174],"elements":[79],"as":[80,158],"well.":[81],"Previous":[82],"methods":[83],"have":[84],"addressed":[85],"this":[86],"issue":[87],"injecting":[89],"noise":[90,103,107],"into":[91],"though":[94],"finding":[95],"right":[97],"balance":[98],"challenging;":[100],"while":[101,200],"more":[102],"increases":[104],"privacy,":[105],"excessive":[106],"degrades":[108],"model":[109,202],"output.":[110],"Other":[111],"approaches":[112],"use":[113],"custom":[114],"architectures":[115],"decouple":[117],"neighborhood":[118],"aggregation":[119],"representation":[122],"learning,":[123],"these":[125],"solutions":[126],"struggle":[128],"scale":[130],"large":[132],"graphs.":[133],"We":[134],"propose":[135],"strategy":[137],"training":[139,148,193],"subgraph-level":[140],"DP-GNNs":[141],"extracting":[143],"disjoint":[144],"subgraphs":[145],"dataset":[149],"and":[150,170],"applying":[151],"DP-SGD":[153],"algorithm,":[154],"treating":[155],"subgraph":[157],"an":[159],"independent":[160],"sample.":[161],"This":[162],"method":[163],"protects":[164],"target":[168],"their":[171],"neighbors.":[172],"Our":[173],"partitioning":[175],"inspired":[178],"community":[180],"detection":[181],"techniques,":[182],"help":[184],"preserve":[185],"relevant":[186],"connections":[187],"within":[188],"partitions.":[189],"By":[190],"restructuring":[191],"our":[195],"solution":[196],"enhances":[197],"protection":[199],"maintaining":[201],"utility,":[203],"ultimately":[204],"outperforming":[205],"existing":[206],"techniques.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
