{"id":"https://openalex.org/W7130716495","doi":"https://doi.org/10.1109/lca.2026.3666823","title":"FeatureBleed: Inferring Private Enriched Attributes From Sparsity-Optimized AI Accelerators","display_name":"FeatureBleed: Inferring Private Enriched Attributes From Sparsity-Optimized AI Accelerators","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7130716495","doi":"https://doi.org/10.1109/lca.2026.3666823"},"language":"en","primary_location":{"id":"doi:10.1109/lca.2026.3666823","doi":"https://doi.org/10.1109/lca.2026.3666823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lca.2026.3666823","pdf_url":null,"source":{"id":"https://openalex.org/S17643076","display_name":"IEEE Computer Architecture Letters","issn_l":"1556-6056","issn":["1556-6056","1556-6064","2473-2575"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","norway-1","poland-70","russia-white-list-2"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Computer Architecture Letters","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2602.18304","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071121218","display_name":"Darsh Asher","orcid":"https://orcid.org/0009-0007-3325-0224","observed_orcids":["https://orcid.org/0009-0007-3325-0224"]},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Darsh Asher","raw_affiliation_strings":["ECE Department, NC State University, Raleigh, USA"],"raw_orcid":"https://orcid.org/0009-0007-3325-0224","affiliations":[{"raw_affiliation_string":"ECE Department, NC State University, Raleigh, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116447672","display_name":"Farshad Dizani","orcid":"https://orcid.org/0009-0005-8136-5320","observed_orcids":["https://orcid.org/0009-0005-8136-5320"]},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Farshad Dizani","raw_affiliation_strings":["ECE Department, NC State University, Raleigh, USA"],"raw_orcid":"https://orcid.org/0009-0005-8136-5320","affiliations":[{"raw_affiliation_string":"ECE Department, NC State University, Raleigh, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008019619","display_name":"Joshua Kalyanapu","orcid":"https://orcid.org/0009-0002-3186-5069","observed_orcids":["https://orcid.org/0009-0002-3186-5069"]},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joshua Kalyanapu","raw_affiliation_strings":["ECE Department, NC State University, Raleigh, USA"],"raw_orcid":"https://orcid.org/0009-0002-3186-5069","affiliations":[{"raw_affiliation_string":"ECE Department, NC State University, Raleigh, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085883266","display_name":"Rosario Cammarota","orcid":"https://orcid.org/0000-0002-2965-8987","observed_orcids":["https://orcid.org/0000-0002-2965-8987","https://orcid.org/0000-0001-5927-8902"]},"institutions":[{"id":"https://openalex.org/I204250578","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771","country_code":"US","type":"education","lineage":["https://openalex.org/I204250578"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rosario Cammarota","raw_affiliation_strings":["UC Irvine, CA, USA"],"raw_orcid":"https://orcid.org/0000-0001-5927-8902","affiliations":[{"raw_affiliation_string":"UC Irvine, CA, USA","institution_ids":["https://openalex.org/I204250578"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062027964","display_name":"Ayd\u0131n Aysu","orcid":"https://orcid.org/0000-0002-5530-8710","observed_orcids":["https://orcid.org/0000-0002-5530-8710"]},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aydin Aysu","raw_affiliation_strings":["ECE Department, NC State University, Raleigh, USA"],"raw_orcid":"https://orcid.org/0000-0002-5530-8710","affiliations":[{"raw_affiliation_string":"ECE Department, NC State University, Raleigh, USA","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014384780","display_name":"Samira Mirbagher Ajorpaz","orcid":"https://orcid.org/0009-0008-4997-5980","observed_orcids":["https://orcid.org/0009-0008-4997-5980"]},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samira Mirbagher Ajorpaz","raw_affiliation_strings":["ECE Department, NC State University, Raleigh, USA"],"raw_orcid":"https://orcid.org/0009-0008-4997-5980","affiliations":[{"raw_affiliation_string":"ECE Department, NC State University, Raleigh, USA","institution_ids":["https://openalex.org/I137902535"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06956522,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":"1","first_page":"77","last_page":"80"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11424","display_name":"Security and Verification in Computing","score":0.9506999850273132,"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/T11424","display_name":"Security and Verification in Computing","score":0.9506999850273132,"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/T10951","display_name":"Cryptographic Implementations and Security","score":0.02590000070631504,"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":0.006500000134110451,"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/timing-side-channel","display_name":"timing side channels","score":0.5820000171661377},{"id":"https://openalex.org/keywords/ai-hardware","display_name":"AI accelerators","score":0.8320000171661377},{"id":"https://openalex.org/keywords/privacy-leakage","display_name":"privacy leakage","score":0.42800000309944153},{"id":"https://openalex.org/keywords/nvidia-a100","display_name":"NVIDIA A100","score":0.9869999885559082},{"id":"https://openalex.org/keywords/privacy-performance-trade-off","display_name":"privacy-performance trade-off","score":0.671999990940094},{"id":"https://openalex.org/keywords/medical-data-confidentiality","display_name":"medical data confidentiality","score":0.628000020980835}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8628000020980835},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7466999888420105},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6545000076293945},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5637000203132629},{"id":"https://openalex.org/C71745522","wikidata":"https://www.wikidata.org/wiki/Q2476929","display_name":"Confidentiality","level":2,"score":0.5331000089645386},{"id":"https://openalex.org/C2779201187","wikidata":"https://www.wikidata.org/wiki/Q2775060","display_name":"Information leakage","level":2,"score":0.41290000081062317},{"id":"https://openalex.org/C2777042071","wikidata":"https://www.wikidata.org/wiki/Q6509304","display_name":"Leakage (economics)","level":2,"score":0.41280001401901245},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.37209999561309814},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.36489999294281006},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.3402999937534332},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3393000066280365},{"id":"https://openalex.org/C46743427","wikidata":"https://www.wikidata.org/wiki/Q1341685","display_name":"Inference engine","level":3,"score":0.33570000529289246},{"id":"https://openalex.org/C2984118289","wikidata":"https://www.wikidata.org/wiki/Q29954","display_name":"Power consumption","level":3,"score":0.3156000077724457},{"id":"https://openalex.org/C99221444","wikidata":"https://www.wikidata.org/wiki/Q1532069","display_name":"Private information retrieval","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.29910001158714294},{"id":"https://openalex.org/C168522837","wikidata":"https://www.wikidata.org/wiki/Q679552","display_name":"Branch predictor","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C49289754","wikidata":"https://www.wikidata.org/wiki/Q2267081","display_name":"Side channel attack","level":3,"score":0.27239999175071716},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26820001006126404},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.2614000141620636},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.26109999418258667},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25769999623298645}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/lca.2026.3666823","doi":"https://doi.org/10.1109/lca.2026.3666823","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lca.2026.3666823","pdf_url":null,"source":{"id":"https://openalex.org/S17643076","display_name":"IEEE Computer Architecture Letters","issn_l":"1556-6056","issn":["1556-6056","1556-6064","2473-2575"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","norway-1","poland-70","russia-white-list-2"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Computer Architecture Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2602.18304","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2602.18304","pdf_url":"https://arxiv.org/pdf/2602.18304","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2602.18304","doi":"https://doi.org/10.48550/arxiv.2602.18304","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2602.18304","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2602.18304","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2602.18304","pdf_url":"https://arxiv.org/pdf/2602.18304","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G6115220380","display_name":null,"funder_award_id":"2025-HW-3306","funder_id":"https://openalex.org/F4320306087","funder_display_name":"Semiconductor Research Corporation"}],"funders":[{"id":"https://openalex.org/F4320306087","display_name":"Semiconductor Research Corporation","ror":"https://ror.org/047z4n946"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7130716495.pdf","grobid_xml":"https://content.openalex.org/works/W7130716495.grobid-xml"},"referenced_works_count":2,"referenced_works":["https://openalex.org/W3196976833","https://openalex.org/W4398234406"],"related_works":["https://openalex.org/W4416050024","https://openalex.org/W7164359174","https://openalex.org/W4408017777","https://openalex.org/W7197020404","https://openalex.org/W4318541558","https://openalex.org/W4384027004","https://openalex.org/W7159926326","https://openalex.org/W7215117480","https://openalex.org/W3134770507","https://openalex.org/W3205334056"],"abstract_inverted_index":{"Backend":[0],"enrichmentis":[1],"now":[2],"widelydeployed":[3],"in":[4,164],"sensitive":[5],"domains":[6],"such":[7],"as":[8,161],"product":[9],"recommendation":[10],"pipelines,":[11],"healthcare,":[12],"and":[13,22,59,95,103,117,120,126,137,142,207],"finance,":[14],"where":[15],"models":[16],"are":[17],"trained":[18],"on":[19,80],"confidential":[20],"data":[21,57,140],"retrieve":[23],"private":[24,71],"features":[25,73],"whose":[26],"values":[27],"influence":[28],"inference":[29],"behavior":[30],"while":[31],"remaining":[32],"hidden":[33],"from":[34],"the":[35,41,132,155,159,169,197],"API":[36],"caller.":[37],"This":[38],"paper":[39],"presents":[40],"firsthardware-level":[42],"backend":[43],"retrieval":[44],"data-stealing":[45],"attack,":[46],"showing":[47],"that":[48,131,189],"accelerator":[49],"optimizations":[50],"designed":[51],"for":[52],"performance":[53,205],"can":[54],"directly":[55],"undermine":[56],"confidentiality":[58],"bypass":[60],"state-of-the-art":[61],"privacy":[62],"defenses.":[63],"Our":[64],"attack,FeatureBleed,":[65],"exploitszero-skippingin":[66],"AI":[67],"accelerators":[68],"to":[69,196],"infer":[70],"backend-retrieved":[72],"solely":[74],"through":[75],"end-to-end":[76],"timing,":[77],"without":[78],"relying":[79],"power":[81,210],"analysis,":[82],"DVFS":[83],"manipulation,":[84],"or":[85],"shared-cache":[86],"side":[87],"channels.":[88],"We":[89,107,167,184],"evaluateFeatureBleedon":[90],"three":[91,110,121],"datasets":[92],"spanning":[93],"medical":[94],"non-medical":[96],"domains\u2014Texas-100X":[97],"(clinical":[98],"records),":[99],"OrganAMNIST":[100],"(medical":[101],"imaging),":[102],"Census-19":[104],"(socioeconomic":[105],"data).":[106],"further":[108],"evaluateFeatureBleedacross":[109],"hardware":[111],"backends":[112],"(Intel":[113],"AVX,":[114],"Intel":[115,175],"AMX,":[116],"NVIDIA":[118],"A100)":[119],"model":[122],"architectures":[123],"(DNNs,":[124],"CNNs,":[125],"hybrid":[127],"CNN\u2013MLP":[128],"pipelines),":[129],"demonstrating":[130],"leakage":[133,160,192],"generalizes":[134],"across":[135],"CPU":[136],"GPU":[138],"accelerators,":[139],"modalities,":[141],"application":[143],"domains,":[144],"with":[145,203],"an":[146],"adversarial":[147],"advantage":[148],"of":[149,158],"up":[150,180],"to98.87pp.":[151],"Finally,":[152],"we":[153],"identify":[154],"root":[156],"cause":[157],"sparsity-driven":[162],"zero-skipping":[163,173],"modern":[165],"hardware.":[166],"quantify":[168],"privacy\u2013performance\u2013power":[170],"trade-off:":[171],"disabling":[172],"increases":[174],"AMX's":[176],"per-operation":[177],"energy":[178],"by":[179,193],"to25%and":[181],"incurs100%performance":[182],"overhead.":[183],"propose":[185],"a":[186],"padding-based":[187],"defense":[188],"masks":[190],"timing":[191],"equalizing":[194],"responses":[195],"worst-case":[198],"execution":[199],"time,":[200],"achieving":[201],"protection":[202],"only7.24%average":[204],"overhead":[206],"no":[208],"additional":[209],"cost.":[211]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-02-21T00:00:00"}
