{"id":"https://openalex.org/W3097740790","doi":"https://doi.org/10.1109/tcad.2020.3033749","title":"Bias Busters: Robustifying DL-Based Lithographic Hotspot Detectors Against Backdooring Attacks","display_name":"Bias Busters: Robustifying DL-Based Lithographic Hotspot Detectors Against Backdooring Attacks","publication_year":2020,"publication_date":"2020-10-26","ids":{"openalex":"https://openalex.org/W3097740790","doi":"https://doi.org/10.1109/tcad.2020.3033749","mag":"3097740790"},"language":"en","primary_location":{"id":"doi:10.1109/tcad.2020.3033749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcad.2020.3033749","pdf_url":null,"source":{"id":"https://openalex.org/S100835903","display_name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","issn_l":"0278-0070","issn":["0278-0070","1937-4151"],"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 Transactions on Computer-Aided Design of Integrated Circuits and Systems","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/A5100389879","display_name":"Kang Liu","orcid":"https://orcid.org/0000-0001-7231-8315"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kang Liu","raw_affiliation_strings":["New York University, Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069388936","display_name":"Benjamin Tan","orcid":"https://orcid.org/0000-0002-7642-3638"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Benjamin Tan","raw_affiliation_strings":["New York University, Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080942398","display_name":"Gaurav Rajavendra Reddy","orcid":"https://orcid.org/0000-0002-1259-4913"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gaurav Rajavendra Reddy","raw_affiliation_strings":["University of Texas at Dallas, Richardson, TX, USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010950688","display_name":"Siddharth Garg","orcid":"https://orcid.org/0000-0002-6158-9512"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siddharth Garg","raw_affiliation_strings":["New York University, Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078818440","display_name":"Yiorgos Makris","orcid":"https://orcid.org/0000-0002-4322-0068"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiorgos Makris","raw_affiliation_strings":["University of Texas at Dallas, Richardson, TX, USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059648257","display_name":"Ramesh Karri","orcid":"https://orcid.org/0000-0001-7989-5617"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramesh Karri","raw_affiliation_strings":["New York University, Brooklyn, NY, USA"],"affiliations":[{"raw_affiliation_string":"New York University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I57206974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100389879"],"corresponding_institution_ids":["https://openalex.org/I57206974"],"apc_list":null,"apc_paid":null,"fwci":1.0875,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.83168503,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"40","issue":"10","first_page":"2077","last_page":"2089"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9968000054359436,"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":0.9968000054359436,"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9753999710083008,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9742000102996826,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8852442502975464},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6772629022598267},{"id":"https://openalex.org/keywords/hotspot","display_name":"Hotspot (geology)","score":0.6573992371559143},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5121216773986816},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47897911071777344},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4751206040382385},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4430014491081238},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38143759965896606},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3716447353363037},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34902316331863403}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.8852442502975464},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6772629022598267},{"id":"https://openalex.org/C146481406","wikidata":"https://www.wikidata.org/wiki/Q105131","display_name":"Hotspot (geology)","level":2,"score":0.6573992371559143},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5121216773986816},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47897911071777344},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4751206040382385},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4430014491081238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38143759965896606},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3716447353363037},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34902316331863403},{"id":"https://openalex.org/C8058405","wikidata":"https://www.wikidata.org/wiki/Q46255","display_name":"Geophysics","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcad.2020.3033749","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcad.2020.3033749","pdf_url":null,"source":{"id":"https://openalex.org/S100835903","display_name":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","issn_l":"0278-0070","issn":["0278-0070","1937-4151"],"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 Transactions on Computer-Aided Design of Integrated Circuits and Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1346521723","display_name":null,"funder_award_id":"2810.025","funder_id":"https://openalex.org/F4320306087","funder_display_name":"Semiconductor Research Corporation"},{"id":"https://openalex.org/G2989255803","display_name":null,"funder_award_id":"1553419","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3480130277","display_name":null,"funder_award_id":"1801495","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4226726185","display_name":null,"funder_award_id":"N00014-18-1-2058","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306087","display_name":"Semiconductor Research Corporation","ror":"https://ror.org/047z4n946"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1673923490","https://openalex.org/W1945616565","https://openalex.org/W2187089797","https://openalex.org/W2346205343","https://openalex.org/W2750396644","https://openalex.org/W2753783305","https://openalex.org/W2773446523","https://openalex.org/W2774423163","https://openalex.org/W2794271438","https://openalex.org/W2804151869","https://openalex.org/W2806976363","https://openalex.org/W2807108439","https://openalex.org/W2807363941","https://openalex.org/W2889752222","https://openalex.org/W2934843808","https://openalex.org/W2936148765","https://openalex.org/W2942091739","https://openalex.org/W2945381924","https://openalex.org/W2946443981","https://openalex.org/W2949736877","https://openalex.org/W2954996726","https://openalex.org/W2962793481","https://openalex.org/W2963207607","https://openalex.org/W2963343288","https://openalex.org/W2963389226","https://openalex.org/W2964153729","https://openalex.org/W2964253222","https://openalex.org/W2970200861","https://openalex.org/W2986013765","https://openalex.org/W2990270730","https://openalex.org/W2998417722","https://openalex.org/W3007437825","https://openalex.org/W3014404070","https://openalex.org/W3035808436","https://openalex.org/W3041574178","https://openalex.org/W3119492148","https://openalex.org/W4247200422","https://openalex.org/W4288079630","https://openalex.org/W4288093767","https://openalex.org/W4293846201","https://openalex.org/W4298140072","https://openalex.org/W6637162671","https://openalex.org/W6640425456","https://openalex.org/W6729756640","https://openalex.org/W6739868092","https://openalex.org/W6750462152","https://openalex.org/W6751445234","https://openalex.org/W6767183785"],"related_works":["https://openalex.org/W4320031223","https://openalex.org/W2989852175","https://openalex.org/W3094566724","https://openalex.org/W3015716673","https://openalex.org/W4288797976","https://openalex.org/W4287183950","https://openalex.org/W3132644649","https://openalex.org/W3213133223","https://openalex.org/W4205710429","https://openalex.org/W3000197790"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"(DL)":[2],"offers":[3],"potential":[4],"improvements":[5],"throughout":[6],"the":[7,97,102,117,120,127,132],"CAD":[8],"tool-flow,":[9],"one":[10],"promising":[11],"application":[12],"being":[13],"lithographic":[14],"hotspot":[15,51],"detection.":[16],"However,":[17],"DL":[18],"techniques":[19],"have":[20],"been":[21],"shown":[22],"to":[23,27,138],"be":[24],"especially":[25],"vulnerable":[26],"inference":[28],"and":[29],"training":[30,55,80,103,112],"time":[31],"adversarial":[32],"attacks.":[33,91],"Recent":[34],"work":[35],"has":[36],"demonstrated":[37],"that":[38,58,126],"a":[39,49,69,78,85],"small":[40],"fraction":[41],"of":[42,110,119],"malicious":[43],"physical":[44],"designers":[45],"can":[46,129],"stealthily":[47],"\u201cbackdoor\u201d":[48],"DL-based":[50],"detector":[52],"during":[53],"its":[54],"phase":[56],"such":[57,89],"it":[59],"accurately":[60],"classifies":[61],"regular":[62],"layout":[63],"clips":[64],"but":[65,105],"predicts":[66],"hotspots":[67],"containing":[68],"specially":[70],"crafted":[71],"trigger":[72],"shape":[73],"as":[74,84],"nonhotspots.":[75],"We":[76],"propose":[77],"novel":[79],"data":[81,104],"augmentation":[82],"strategy":[83],"powerful":[86],"defense":[87,93,128],"against":[88],"backdooring":[90],"The":[92],"works":[94],"by":[95],"eliminating":[96],"intentional":[98],"biases":[99],"introduced":[100],"in":[101],"does":[106],"not":[107],"require":[108],"knowledge":[109],"which":[111],"samples":[113],"are":[114],"poisoned":[115],"or":[116],"nature":[118],"backdoor":[121],"trigger.":[122],"Our":[123],"results":[124],"show":[125],"drastically":[130],"reduce":[131],"attack":[133],"success":[134],"rate":[135],"from":[136],"84%":[137],"~0%.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
