{"id":"https://openalex.org/W4224069029","doi":"https://doi.org/10.1145/3544015","title":"AdaTest: Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection","display_name":"AdaTest: Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection","publication_year":2022,"publication_date":"2022-06-14","ids":{"openalex":"https://openalex.org/W4224069029","doi":"https://doi.org/10.1145/3544015"},"language":"en","primary_location":{"id":"doi:10.1145/3544015","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3544015","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3544015","source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3544015","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101449721","display_name":"Huili Chen","orcid":"https://orcid.org/0000-0001-5828-2942"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Huili Chen","raw_affiliation_strings":["University of California, San Diego, USA"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010458097","display_name":"Xinqiao Zhang","orcid":"https://orcid.org/0000-0002-2785-2321"},"institutions":[{"id":"https://openalex.org/I26538001","display_name":"San Diego State University","ror":"https://ror.org/0264fdx42","country_code":"US","type":"education","lineage":["https://openalex.org/I26538001"]},{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xinqiao Zhang","raw_affiliation_strings":["San Diego State University & University of California, San Diego, California, USA"],"affiliations":[{"raw_affiliation_string":"San Diego State University & University of California, San Diego, California, USA","institution_ids":["https://openalex.org/I26538001","https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101967980","display_name":"Ke Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I26538001","display_name":"San Diego State University","ror":"https://ror.org/0264fdx42","country_code":"US","type":"education","lineage":["https://openalex.org/I26538001"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ke Huang","raw_affiliation_strings":["San Diego State University, San Diego, California, USA"],"affiliations":[{"raw_affiliation_string":"San Diego State University, San Diego, California, USA","institution_ids":["https://openalex.org/I26538001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019931011","display_name":"Farinaz Koushanfar","orcid":"https://orcid.org/0000-0003-0798-3794"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Farinaz Koushanfar","raw_affiliation_strings":["University of California, San Diego, California, USA"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego, California, USA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101449721"],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":6.302,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.97324475,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"22","issue":"2","first_page":"1","last_page":"23"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9936000108718872,"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"}},{"id":"https://openalex.org/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9830999970436096,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.836240291595459},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7091361880302429},{"id":"https://openalex.org/keywords/hardware-trojan","display_name":"Hardware Trojan","score":0.6404138207435608},{"id":"https://openalex.org/keywords/emulation","display_name":"Emulation","score":0.6254745125770569},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6032488346099854},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.579303503036499},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5178332924842834},{"id":"https://openalex.org/keywords/trojan","display_name":"Trojan","score":0.5005125999450684},{"id":"https://openalex.org/keywords/automatic-test-pattern-generation","display_name":"Automatic test pattern generation","score":0.467529296875},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4557482898235321},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4554145336151123},{"id":"https://openalex.org/keywords/adaptive-sampling","display_name":"Adaptive sampling","score":0.4328180253505707},{"id":"https://openalex.org/keywords/code-coverage","display_name":"Code coverage","score":0.41508638858795166},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.40309661626815796},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.33451366424560547},{"id":"https://openalex.org/keywords/electronic-circuit","display_name":"Electronic circuit","score":0.2714155316352844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26419946551322937}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.836240291595459},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7091361880302429},{"id":"https://openalex.org/C2780873074","wikidata":"https://www.wikidata.org/wiki/Q5656397","display_name":"Hardware Trojan","level":3,"score":0.6404138207435608},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.6254745125770569},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6032488346099854},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.579303503036499},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5178332924842834},{"id":"https://openalex.org/C174333608","wikidata":"https://www.wikidata.org/wiki/Q19635","display_name":"Trojan","level":2,"score":0.5005125999450684},{"id":"https://openalex.org/C17626397","wikidata":"https://www.wikidata.org/wiki/Q837455","display_name":"Automatic test pattern generation","level":3,"score":0.467529296875},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4557482898235321},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4554145336151123},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.4328180253505707},{"id":"https://openalex.org/C53942775","wikidata":"https://www.wikidata.org/wiki/Q1211721","display_name":"Code coverage","level":3,"score":0.41508638858795166},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.40309661626815796},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.33451366424560547},{"id":"https://openalex.org/C134146338","wikidata":"https://www.wikidata.org/wiki/Q1815901","display_name":"Electronic circuit","level":2,"score":0.2714155316352844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26419946551322937},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3544015","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3544015","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3544015","source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3544015","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3544015","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3544015","source":{"id":"https://openalex.org/S136160450","display_name":"ACM Transactions on Embedded Computing Systems","issn_l":"1539-9087","issn":["1539-9087","1558-3465"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Embedded Computing Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G2200512414","display_name":null,"funder_award_id":"CCF-2112665","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5197792821","display_name":null,"funder_award_id":"2016737","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5921281487","display_name":null,"funder_award_id":"number","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7906245503","display_name":null,"funder_award_id":"211266","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4224069029.pdf","grobid_xml":"https://content.openalex.org/works/W4224069029.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1965148046","https://openalex.org/W1976955200","https://openalex.org/W1977294468","https://openalex.org/W2001441503","https://openalex.org/W2045818632","https://openalex.org/W2050241597","https://openalex.org/W2101246871","https://openalex.org/W2112173236","https://openalex.org/W2116238498","https://openalex.org/W2148357146","https://openalex.org/W2151668694","https://openalex.org/W2160130484","https://openalex.org/W2161998562","https://openalex.org/W2185857575","https://openalex.org/W2207233201","https://openalex.org/W2236833104","https://openalex.org/W2274193143","https://openalex.org/W2282885268","https://openalex.org/W2293426816","https://openalex.org/W2328867239","https://openalex.org/W2343475170","https://openalex.org/W2442974303","https://openalex.org/W2464661970","https://openalex.org/W2532898432","https://openalex.org/W2606854262","https://openalex.org/W2752013983","https://openalex.org/W2754667819","https://openalex.org/W2771999643","https://openalex.org/W2790282160","https://openalex.org/W2823310453","https://openalex.org/W2952435030","https://openalex.org/W3035159621","https://openalex.org/W3111157406","https://openalex.org/W3128775242","https://openalex.org/W4214717370","https://openalex.org/W4245281178","https://openalex.org/W4253001802","https://openalex.org/W4255527997","https://openalex.org/W4298857966","https://openalex.org/W6637967152"],"related_works":["https://openalex.org/W4385434494","https://openalex.org/W3159333627","https://openalex.org/W3004467197","https://openalex.org/W1500594134","https://openalex.org/W2091750459","https://openalex.org/W2999465529","https://openalex.org/W3084939900","https://openalex.org/W2382172865","https://openalex.org/W1526642037","https://openalex.org/W4321062229"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"AdaTest,":[3],"a":[4,21,71,138],"novel":[5],"adaptive":[6,107,192],"test":[7,75,81,95,111,171,186,227,234],"pattern":[8],"generation":[9,228],"framework":[10],"for":[11,117,131,185,213],"efficient":[12],"and":[13,46,57,99,142,191,202,230],"reliable":[14],"Hardware":[15],"Trojan":[16,250],"(HT)":[17],"detection.":[18,215],"HT":[19,39,118,200,214],"is":[20,97],"backdoor":[22],"attack":[23],"that":[24,113,209,219],"tampers":[25],"with":[26,83,137,205],"the":[27,37,53,94,122,128,152,170,240,245],"design":[28],"of":[29,44,48,55,74,124,169,226,233],"victim":[30],"integrated":[31],"circuits":[32],"(ICs)":[33],".":[34],"AdaTest":[35,64,105,136,179,220],"improves":[36],"existing":[38],"detection":[40,251],"techniques":[41],"in":[42,52,87,155,178],"terms":[43],"scalability":[45],"accuracy":[47],"detecting":[49],"smaller":[50],"Trojans":[51],"presence":[54],"noise":[56],"variations.":[58],"To":[59],"achieve":[60],"high":[61,84],"trigger":[62],"coverage,":[63],"leverages":[65],"Reinforcement":[66],"Learning":[67],"(RL)":[68],"to":[69,109,165,223,239],"produce":[70],"diverse":[72],"set":[73,96,235],"inputs.":[76],"Particularly,":[77],"we":[78],"progressively":[79],"generate":[80],"vectors":[82],"\u2018reward\u2019":[85],"values":[86],"an":[88,144],"iterative":[89],"manner.":[90],"In":[91],"each":[92,175],"iteration,":[93],"evaluated":[98],"adaptively":[100],"expanded":[101],"as":[102],"needed.":[103],"Furthermore,":[104],"integrates":[106],"sampling":[108],"prioritize":[110],"samples":[112,125],"provide":[114,143],"more":[115],"information":[116],"detection,":[119],"thus":[120],"reducing":[121],"number":[123],"while":[126,243],"improving":[127],"samples\u2019":[129],"quality":[130],"faster":[132],"exploration.":[133],"We":[134,194],"develop":[135],"Software/Hardware":[139],"co-design":[140],"principle":[141],"optimized":[145],"on-chip":[146],"architecture":[147,150],"solution.":[148],"AdaTest\u2019s":[149,196],"minimizes":[151],"hardware":[153,164],"overhead":[154],"two":[156,206,224,231],"ways:":[157],"(i)":[158],"Deploying":[159],"circuit":[160,184],"emulation":[161],"on":[162,198],"programmable":[163],"accelerate":[166],"reward":[167,189],"evaluation":[168],"input;":[172],"(ii)":[173],"Pipelining":[174],"computation":[176],"stage":[177],"by":[180],"automatically":[181],"constructing":[182],"auxiliary":[183],"input":[187],"generation,":[188],"evaluation,":[190],"sampling.":[193],"evaluate":[195],"performance":[197],"various":[199],"benchmarks":[201],"compare":[203],"it":[204],"prior":[207,241],"works":[208,242],"use":[210],"logic":[211],"testing":[212],"Experimental":[216],"results":[217],"show":[218],"engenders":[221],"up":[222],"orders":[225,232],"speedup":[229],"size":[236],"reduction":[237],"compared":[238],"achieving":[244],"same":[246],"level":[247],"or":[248],"higher":[249],"rate.":[252]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}