{"id":"https://openalex.org/W7165932944","doi":"https://doi.org/10.48550/arxiv.2606.25589","title":"Leaking Circuit Secrets: Gradient Leakage Attacks on Graph Neural Networks","display_name":"Leaking Circuit Secrets: Gradient Leakage Attacks on Graph Neural Networks","publication_year":2026,"publication_date":"2026-06-24","ids":{"openalex":"https://openalex.org/W7165932944","doi":"https://doi.org/10.48550/arxiv.2606.25589"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.25589","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25589","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.25589","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139316459","display_name":"Rupesh Raj Karn","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karn, Rupesh Raj","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139379803","display_name":"Johann Knechtel","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Knechtel, Johann","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139343312","display_name":"Ozgur Sinanoglu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sinanoglu, Ozgur","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.8791999816894531,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.8791999816894531,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.093299999833107,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/netlist","display_name":"Netlist","score":0.7287999987602234},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4140999913215637},{"id":"https://openalex.org/keywords/threat-model","display_name":"Threat model","score":0.414000004529953},{"id":"https://openalex.org/keywords/vulnerability","display_name":"Vulnerability (computing)","score":0.40709999203681946},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3869999945163727},{"id":"https://openalex.org/keywords/leakage","display_name":"Leakage (economics)","score":0.3720000088214874},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.35359999537467957},{"id":"https://openalex.org/keywords/vulnerability-assessment","display_name":"Vulnerability assessment","score":0.3481999933719635},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3280999958515167}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.734000027179718},{"id":"https://openalex.org/C177650935","wikidata":"https://www.wikidata.org/wiki/Q1760303","display_name":"Netlist","level":2,"score":0.7287999987602234},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4140999913215637},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.414000004529953},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.40709999203681946},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3869999945163727},{"id":"https://openalex.org/C2777042071","wikidata":"https://www.wikidata.org/wiki/Q6509304","display_name":"Leakage (economics)","level":2,"score":0.3720000088214874},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.35359999537467957},{"id":"https://openalex.org/C167063184","wikidata":"https://www.wikidata.org/wiki/Q1400839","display_name":"Vulnerability assessment","level":3,"score":0.3481999933719635},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.328000009059906},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C2780873074","wikidata":"https://www.wikidata.org/wiki/Q5656397","display_name":"Hardware Trojan","level":3,"score":0.3118000030517578},{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.305400013923645},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.2980000078678131},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29089999198913574},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2881999909877777},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C49289754","wikidata":"https://www.wikidata.org/wiki/Q2267081","display_name":"Side channel attack","level":3,"score":0.2851000130176544},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.2824000120162964},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C174333608","wikidata":"https://www.wikidata.org/wiki/Q19635","display_name":"Trojan","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.26820001006126404},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2563999891281128},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.25589","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25589","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.25589","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.25589","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"As":[0],"graph":[1],"neural":[2],"networks":[3],"(GNNs)":[4],"become":[5],"standard":[6,64],"tools":[7],"for":[8,71,185],"critical":[9],"tasks":[10],"in":[11,38,99,163],"circuit":[12],"design":[13],"and":[14,18,40,60,69,89,152,166,181,188,196],"analysis,":[15],"their":[16,72],"security":[17],"privacy":[19],"risks":[20,114],"require":[21],"careful":[22],"attention.":[23],"Here,":[24],"we":[25],"present":[26],"the":[27,183],"first":[28],"comprehensive":[29],"evaluation":[30],"of":[31,92],"gradient":[32,144],"leakage":[33],"attacks":[34],"(GLAs)":[35],"on":[36,63],"GNNs":[37,180],"circuit-design":[39],"hardware-security":[41],"tasks,":[42],"a":[43],"practical":[44],"threat":[45],"that":[46,79,112,157],"has":[47],"been":[48],"largely":[49],"overlooked.":[50],"We":[51,77,134,155,191],"assess":[52],"state-of-the-art":[53],"(SOTA)":[54],"GNNs,":[55],"including":[56,141],"GraphSAGE,":[57],"GCN,":[58],"GIN,":[59],"GAT,":[61],"trained":[62],"netlist":[65],"benchmarks":[66],"(ISCAS'85,":[67],"EPFL,":[68],"TrustHub),":[70],"fundamental":[73],"vulnerability":[74],"to":[75],"GLAs.":[76],"find":[78,156],"GLAs":[80],"can":[81,167],"expose":[82],"sensitive":[83],"information,":[84],"such":[85],"as":[86],"gate":[87],"types":[88],"distinctive":[90],"properties":[91],"hardware":[93],"Trojans,":[94],"which":[95],"may":[96],"assist":[97],"adversaries":[98],"analyzing":[100],"logic":[101],"locking":[102],"schemes":[103],"or":[104],"evading":[105],"Trojan":[106],"detection":[107],"mechanisms.":[108],"Our":[109],"analysis":[110],"shows":[111],"these":[113,158],"are":[115],"influenced":[116],"by":[117],"architectural":[118],"features,":[119],"with":[120,150],"attention":[121],"mechanisms":[122],"(GAT)":[123],"exacerbating":[124],"leakage,":[125],"while":[126],"injective":[127],"aggregation":[128],"(GIN)":[129],"provides":[130,175],"comparatively":[131],"stronger":[132],"resilience.":[133],"further":[135],"evaluate":[136],"several":[137],"SOTA":[138],"defense":[139],"techniques,":[140],"differential":[142],"privacy,":[143],"clipping,":[145],"secure":[146],"aggregation,":[147],"model":[148,170],"compression":[149],"quantization,":[151],"adversarial":[153],"training.":[154],"techniques":[159],"improve":[160],"resilience":[161],"only":[162],"specific":[164],"settings":[165],"also":[168],"compromise":[169],"performance.":[171],"Overall,":[172],"our":[173,193],"work":[174],"key":[176],"insights":[177],"toward":[178],"privacy-preserving":[179],"highlights":[182],"need":[184],"more":[186],"robust":[187],"efficient":[189],"defenses.":[190],"release":[192],"full":[194],"methodology":[195],"artifacts.":[197]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-26T00:00:00"}