{"id":"https://openalex.org/W4225907520","doi":"https://doi.org/10.1109/les.2022.3159541","title":"Novel Hardware Trojan Attack on Activation Parameters of FPGA-Based DNN Accelerators","display_name":"Novel Hardware Trojan Attack on Activation Parameters of FPGA-Based DNN Accelerators","publication_year":2022,"publication_date":"2022-03-15","ids":{"openalex":"https://openalex.org/W4225907520","doi":"https://doi.org/10.1109/les.2022.3159541"},"language":"en","primary_location":{"id":"doi:10.1109/les.2022.3159541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/les.2022.3159541","pdf_url":null,"source":{"id":"https://openalex.org/S22443479","display_name":"IEEE Embedded Systems Letters","issn_l":"1943-0663","issn":["1943-0663","1943-0671"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Embedded Systems Letters","raw_type":"journal-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/A5077271082","display_name":"Rijoy Mukherjee","orcid":"https://orcid.org/0000-0002-8432-3418"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Rijoy Mukherjee","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India"],"raw_orcid":"https://orcid.org/0000-0002-8432-3418","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049426113","display_name":"Rajat Subhra Chakraborty","orcid":"https://orcid.org/0000-0003-3588-163X"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajat Subhra Chakraborty","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India"],"raw_orcid":"https://orcid.org/0000-0003-3588-163X","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5077271082"],"corresponding_institution_ids":["https://openalex.org/I145894827"],"apc_list":null,"apc_paid":null,"fwci":5.129,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.96376032,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"14","issue":"3","first_page":"131","last_page":"134"},"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":0.9972000122070312,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9934999942779541,"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/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.866466760635376},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8394176959991455},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6133184432983398},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.6034097671508789},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5607779622077942},{"id":"https://openalex.org/keywords/hardware-trojan","display_name":"Hardware Trojan","score":0.5285990238189697},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.512780487537384},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.48818284273147583},{"id":"https://openalex.org/keywords/trojan","display_name":"Trojan","score":0.48379820585250854},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.4277363419532776},{"id":"https://openalex.org/keywords/gate-array","display_name":"Gate array","score":0.4137519299983978},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24769407510757446},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.12999176979064941},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.12912556529045105}],"concepts":[{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.866466760635376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8394176959991455},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6133184432983398},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.6034097671508789},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5607779622077942},{"id":"https://openalex.org/C2780873074","wikidata":"https://www.wikidata.org/wiki/Q5656397","display_name":"Hardware Trojan","level":3,"score":0.5285990238189697},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.512780487537384},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.48818284273147583},{"id":"https://openalex.org/C174333608","wikidata":"https://www.wikidata.org/wiki/Q19635","display_name":"Trojan","level":2,"score":0.48379820585250854},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.4277363419532776},{"id":"https://openalex.org/C114237110","wikidata":"https://www.wikidata.org/wiki/Q114901","display_name":"Gate array","level":3,"score":0.4137519299983978},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24769407510757446},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.12999176979064941},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.12912556529045105}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/les.2022.3159541","is_oa":false,"landing_page_url":"https://doi.org/10.1109/les.2022.3159541","pdf_url":null,"source":{"id":"https://openalex.org/S22443479","display_name":"IEEE Embedded Systems Letters","issn_l":"1943-0663","issn":["1943-0663","1943-0671"],"is_oa":false,"is_in_doaj":false,"is_core":true,"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 Embedded Systems Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2129474264","https://openalex.org/W2151668694","https://openalex.org/W2161998562","https://openalex.org/W2750884072","https://openalex.org/W2899915146","https://openalex.org/W2903582334","https://openalex.org/W2946801000","https://openalex.org/W2962939738","https://openalex.org/W2964265626","https://openalex.org/W3008936127","https://openalex.org/W3036286896","https://openalex.org/W3092516112","https://openalex.org/W4242053016","https://openalex.org/W4252148401","https://openalex.org/W4288083644","https://openalex.org/W6763559720","https://openalex.org/W6767525790","https://openalex.org/W6776294083"],"related_works":["https://openalex.org/W4385434494","https://openalex.org/W3159333627","https://openalex.org/W3004467197","https://openalex.org/W2999465529","https://openalex.org/W2382172865","https://openalex.org/W1500594134","https://openalex.org/W4321062229","https://openalex.org/W4206269447","https://openalex.org/W2740504204","https://openalex.org/W1984975890"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"network":[2],"(DNN)":[3],"hardware":[4,47],"accelerators":[5,18],"are":[6],"being":[7,25],"deployed":[8,26],"widely":[9],"to":[10,69],"accelerate":[11],"the":[12,51,55,70,74,80],"inference":[13,95],"process.":[14],"Security":[15],"of":[16,54,73],"such":[17,30],"is":[19,67,83],"a":[20,58],"major":[21],"challenge,":[22],"especially":[23],"when":[24,87],"in":[27,57,91,94],"safety-critical":[28],"systems":[29],"as":[31],"autonomous":[32],"vehicles.":[33],"In":[34],"this":[35],"letter,":[36],"we":[37],"present":[38],"novel":[39],"Hardware":[40],"Trojan":[41],"(HT)":[42],"attacks":[43],"on":[44],"two":[45],"DNN":[46,56],"accelerators,":[48],"which":[49],"modifies":[50],"activation":[52],"parameters":[53],"field-programmable":[59],"gate":[60],"array-based":[61],"accelerator":[62],"implementation.":[63],"The":[64],"proposed":[65,81],"HT":[66,82],"agnostic":[68],"detailed":[71],"architecture":[72],"DNN.":[75],"Experimental":[76],"results":[77],"demonstrate":[78],"that":[79],"extremely":[84],"stealthy,":[85],"and":[86],"activated":[88],"can":[89],"result":[90],"significant":[92],"degradation":[93],"accuracy.":[96]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6}],"updated_date":"2026-05-19T08:33:51.333923","created_date":"2025-10-10T00:00:00"}