{"id":"https://openalex.org/W4416956213","doi":"https://doi.org/10.1145/3769102.3774437","title":"Saliency-Guided Lightweight Backdoor Defense for Edge Intelligence","display_name":"Saliency-Guided Lightweight Backdoor Defense for Edge Intelligence","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W4416956213","doi":"https://doi.org/10.1145/3769102.3774437"},"language":null,"primary_location":{"id":"doi:10.1145/3769102.3774437","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3769102.3774437","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3769102.3774437","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth ACM/IEEE Symposium on Edge Computing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3769102.3774437","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038983036","display_name":"Z. Y. Zhang","orcid":"https://orcid.org/0009-0009-9122-1637"},"institutions":[{"id":"https://openalex.org/I43579087","display_name":"University of Wisconsin\u2013Milwaukee","ror":"https://ror.org/031q21x57","country_code":"US","type":"education","lineage":["https://openalex.org/I43579087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zijian Zhang","raw_affiliation_strings":["SIDC, University of Wisconsin-Milwaukee, Milwaukee, WI, USA"],"raw_orcid":"https://orcid.org/0009-0009-9122-1637","affiliations":[{"raw_affiliation_string":"SIDC, University of Wisconsin-Milwaukee, Milwaukee, WI, USA","institution_ids":["https://openalex.org/I43579087"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Liang Wu","orcid":"https://orcid.org/0009-0009-1546-8144"},"institutions":[{"id":"https://openalex.org/I43579087","display_name":"University of Wisconsin\u2013Milwaukee","ror":"https://ror.org/031q21x57","country_code":"US","type":"education","lineage":["https://openalex.org/I43579087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Wu","raw_affiliation_strings":["SIDC, University of Wisconsin-Milwaukee, Milwaukee, WI, USA"],"raw_orcid":"https://orcid.org/0009-0009-1546-8144","affiliations":[{"raw_affiliation_string":"SIDC, University of Wisconsin-Milwaukee, Milwaukee, WI, USA","institution_ids":["https://openalex.org/I43579087"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100360185","display_name":"Zhen Zeng","orcid":"https://orcid.org/0000-0002-7877-292X"},"institutions":[{"id":"https://openalex.org/I43579087","display_name":"University of Wisconsin\u2013Milwaukee","ror":"https://ror.org/031q21x57","country_code":"US","type":"education","lineage":["https://openalex.org/I43579087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhen Zeng","raw_affiliation_strings":["SIDC, University of Wisconsin-Milwaukee, Milwaukee, WI, USA"],"raw_orcid":"https://orcid.org/0000-0002-7877-292X","affiliations":[{"raw_affiliation_string":"SIDC, University of Wisconsin-Milwaukee, Milwaukee, WI, USA","institution_ids":["https://openalex.org/I43579087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057478629","display_name":"Zhongshu Gu","orcid":"https://orcid.org/0000-0001-9624-2669"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhongshu Gu","raw_affiliation_strings":["IBM Research, New York, USA"],"raw_orcid":"https://orcid.org/0000-0001-9624-2669","affiliations":[{"raw_affiliation_string":"IBM Research, New York, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.7829999923706055,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.7829999923706055,"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/T11424","display_name":"Security and Verification in Computing","score":0.061500001698732376,"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/T11498","display_name":"Security in Wireless Sensor Networks","score":0.019600000232458115,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/backdoor","display_name":"Backdoor","score":0.9930999875068665},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5680999755859375},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42410001158714294},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.41110000014305115},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.3955000042915344},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.3930000066757202},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.3921999931335449}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9930999875068665},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6353999972343445},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5680999755859375},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42410001158714294},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.41110000014305115},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.3955000042915344},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.3930000066757202},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3921999931335449},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.38920000195503235},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3711000084877014},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3634999990463257},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.3580000102519989},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.32269999384880066},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30559998750686646},{"id":"https://openalex.org/C66989864","wikidata":"https://www.wikidata.org/wiki/Q594646","display_name":"Paillier cryptosystem","level":5,"score":0.2980000078678131},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.287200003862381},{"id":"https://openalex.org/C157170001","wikidata":"https://www.wikidata.org/wiki/Q4781507","display_name":"Applications of artificial intelligence","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C2910806092","wikidata":"https://www.wikidata.org/wiki/Q245016","display_name":"Military Base","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.26019999384880066}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3769102.3774437","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3769102.3774437","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3769102.3774437","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth ACM/IEEE Symposium on Edge Computing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3769102.3774437","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3769102.3774437","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3769102.3774437","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth ACM/IEEE Symposium on Edge Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416956213.pdf","grobid_xml":"https://content.openalex.org/works/W4416956213.grobid-xml"},"referenced_works_count":4,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2807363941","https://openalex.org/W3096831136","https://openalex.org/W4252979261"],"related_works":[],"abstract_inverted_index":{"The":[0,106,153],"expansion":[1],"of":[2,149],"edge":[3,50,77,116,122,183],"intelligence":[4,184],"across":[5],"diverse":[6],"devices":[7],"and":[8,36,45,138,169],"sites":[9],"significantly":[10],"broadens":[11],"the":[12,41,76,88,93,146,150],"attack":[13],"surface,":[14],"making":[15],"backdoor":[16,23,60,125,198],"attacks":[17,126],"a":[18,58,83,101,112,120,163,175],"critical":[19],"security":[20],"threat.":[21],"Existing":[22],"trigger":[24,64],"mitigation":[25,65],"methods":[26],"rely":[27],"heavily":[28],"on":[29,111,162,174],"model":[30,86,103],"retraining":[31],"or":[32],"computationally":[33],"intensive":[34],"filtering,":[35],"thus":[37],"fail":[38],"to":[39,49,91,193],"meet":[40],"stringent":[42],"resource,":[43],"latency,":[44],"privacy":[46],"constraints":[47],"inherent":[48],"deployments.":[51],"To":[52],"address":[53],"this":[54],"gap,":[55],"we":[56],"propose":[57],"saliency-guided":[59],"defense":[61,155,199],"that":[62,118],"treats":[63],"as":[66,195],"an":[67,196],"in-place,":[68],"distribution-aware":[69],"input":[70],"preprocessing":[71],"problem":[72],"integrated":[73],"directly":[74],"into":[75],"inference":[78],"pipeline.":[79],"This":[80,187],"method":[81,108,156],"leverages":[82],"lightweight":[84],"generation-based":[85],"at":[87],"local":[89],"node":[90,165],"purify":[92],"suspicious":[94],"samples,":[95],"which":[96],"are":[97,136,142],"then":[98],"validated":[99,110],"by":[100],"task":[102,151],"for":[104],"inference.":[105],"proposed":[107,154],"is":[109],"4-node":[113],"Raspberry":[114],"Pi":[115],"cluster":[117,176],"emulates":[119],"minimal":[121],"setting,":[123],"where":[124],"have":[127],"been":[128],"effectively":[129],"mitigated":[130],"both":[131],"when":[132,139],"only":[133],"partial":[134],"nodes":[135,141],"affected":[137],"all":[140],"compromised,":[143],"while":[144],"maintaining":[145],"clean":[147],"accuracy":[148],"model.":[152],"adds":[157],"17":[158],"ms":[159,171],"per":[160,172],"image":[161,173],"single":[164],"(batch":[166,177],"size":[167,178],"1)":[168],"0.028":[170],"512),":[179],"well":[180],"within":[181],"typical":[182],"latency":[185],"budgets.":[186],"low":[188],"overhead":[189],"makes":[190],"it":[191],"feasible":[192],"operate":[194],"online":[197],"solution.":[200]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-12-03T00:00:00"}
