{"id":"https://openalex.org/W7128627975","doi":"https://doi.org/10.1109/asianhost68425.2025.11370374","title":"Rethinking LLM Safety on Edge Devices: Unearthing Hidden Vulnerabilities through Power Stress","display_name":"Rethinking LLM Safety on Edge Devices: Unearthing Hidden Vulnerabilities through Power Stress","publication_year":2025,"publication_date":"2025-12-19","ids":{"openalex":"https://openalex.org/W7128627975","doi":"https://doi.org/10.1109/asianhost68425.2025.11370374"},"language":null,"primary_location":{"id":"doi:10.1109/asianhost68425.2025.11370374","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asianhost68425.2025.11370374","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Asian Hardware Oriented Security and Trust Symposium (AsianHOST)","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/A5125647189","display_name":"Weimin Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Weimin Fu","raw_affiliation_strings":["Kansas State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kansas State University","institution_ids":["https://openalex.org/I189590672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102635008","display_name":"Zelin Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zelin Lu","raw_affiliation_strings":["University of Maryland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125669608","display_name":"Gang Qu","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gang Qu","raw_affiliation_strings":["University of Maryland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125646948","display_name":"Xiaolong Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaolong Guo","raw_affiliation_strings":["Kansas State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kansas State University","institution_ids":["https://openalex.org/I189590672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.81322348,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.4171000123023987,"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":0.4171000123023987,"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":0.1889999955892563,"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/T11005","display_name":"Radiation Effects in Electronics","score":0.1728000044822693,"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/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5568000078201294},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5426999926567078},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.375900000333786},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.37119999527931213},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.36399999260902405},{"id":"https://openalex.org/keywords/fault-tolerance","display_name":"Fault tolerance","score":0.34139999747276306},{"id":"https://openalex.org/keywords/stress","display_name":"Stress (linguistics)","score":0.31700000166893005}],"concepts":[{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5568000078201294},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5426999926567078},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.49079999327659607},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.45579999685287476},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.43619999289512634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4056999981403351},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.375900000333786},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.37119999527931213},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.36399999260902405},{"id":"https://openalex.org/C63540848","wikidata":"https://www.wikidata.org/wiki/Q3140932","display_name":"Fault tolerance","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C21036866","wikidata":"https://www.wikidata.org/wiki/Q181767","display_name":"Stress (linguistics)","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C140547941","wikidata":"https://www.wikidata.org/wiki/Q7797194","display_name":"Threat model","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.27399998903274536},{"id":"https://openalex.org/C2989121073","wikidata":"https://www.wikidata.org/wiki/Q1309019","display_name":"Transient analysis","level":3,"score":0.2590000033378601}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asianhost68425.2025.11370374","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asianhost68425.2025.11370374","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Asian Hardware Oriented Security and Trust Symposium (AsianHOST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,102],"safety":[1,151],"of":[2,14,116,144],"large":[3],"language":[4],"models":[5,94],"(LLMs)":[6],"under":[7,87],"hardware-induced":[8,137],"perturbations":[9],"remains":[10],"an":[11,113],"underexplored":[12],"dimension":[13],"model":[15,128],"reliability.":[16],"Although":[17],"LLMs":[18,157],"are":[19],"often":[20],"treated":[21],"as":[22,140],"stable":[23],"and":[24,35,48,83,90,127,148,160],"deterministic":[25],"during":[26],"inference,":[27],"transient":[28],"voltage":[29,100],"fluctuations,":[30],"resulting":[31],"from":[32],"battery":[33],"degradation":[34],"computational":[36],"stress":[37,64],"on":[38,73],"edge":[39,162],"devices,":[40],"can":[41],"induce":[42],"faulty":[43],"behavior,":[44],"including":[45],"hallucinations,":[46],"truncation,":[47],"inference":[49],"failure,":[50],"even":[51],"in":[52,158],"non-adversarial":[53],"settings.":[54],"This":[55],"study":[56],"examines":[57],"the":[58,93,133],"extent":[59],"to":[60,99,108,135],"which":[61],"such":[62,150],"power":[63],"reveals":[65],"model-specific":[66],"vulnerabilities.":[67],"Controlled":[68],"undervolting":[69],"experiments":[70],"were":[71],"conducted":[72],"a":[74,120,141],"Raspberry":[75],"Pi":[76],"5":[77],"using":[78],"two":[79],"instruction-tuned":[80],"LLMs:":[81],"google/gemma-3-1b-it":[82],"meta-llama/Llama-3.2-1B.":[84],"Despite":[85],"operating":[86],"identical":[88],"hardware":[89],"load":[91],"conditions,":[92],"exhibited":[95],"significantly":[96],"different":[97],"responses":[98],"degradation.":[101],"observed":[103],"discrepancies":[104],"suggest":[105],"that":[106],"robustness":[107],"physical":[109],"faults":[110],"is":[111,153],"not":[112],"inherent":[114],"characteristic":[115],"LLMs,":[117],"but":[118],"rather":[119],"learned":[121],"property":[122],"influenced":[123],"by":[124],"training":[125],"methodology":[126],"design.":[129],"These":[130],"findings":[131],"underscore":[132],"need":[134],"treat":[136],"fault":[138],"tolerance":[139],"core":[142],"aspect":[143],"LLM":[145],"safety.":[146],"Evaluating":[147],"improving":[149],"properties":[152],"essential":[154],"for":[155],"deploying":[156],"energy-constrained":[159],"long-lived":[161],"environments.":[163]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-12T00:00:00"}