{"id":"https://openalex.org/W3002799500","doi":"https://doi.org/10.1109/icce-berlin47944.2019.8966236","title":"IP Core Identification in FPGA Configuration Files using Machine Learning Techniques","display_name":"IP Core Identification in FPGA Configuration Files using Machine Learning Techniques","publication_year":2019,"publication_date":"2019-09-08","ids":{"openalex":"https://openalex.org/W3002799500","doi":"https://doi.org/10.1109/icce-berlin47944.2019.8966236","mag":"3002799500"},"language":"en","primary_location":{"id":"doi:10.1109/icce-berlin47944.2019.8966236","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-berlin47944.2019.8966236","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 9th International Conference on Consumer Electronics (ICCE-Berlin)","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/A5071483236","display_name":"Safdar Mahmood","orcid":"https://orcid.org/0000-0001-7714-510X"},"institutions":[{"id":"https://openalex.org/I51783024","display_name":"Brandenburg University of Technology Cottbus-Senftenberg","ror":"https://ror.org/02wxx3e24","country_code":"DE","type":"education","lineage":["https://openalex.org/I51783024"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Safdar Mahmood","raw_affiliation_strings":["Brandenburg University of Technology,Computer Engineering,Cottbus,Germany","Computer Engineering, Brandenburg University of Technology, Cottbus, Germany"],"affiliations":[{"raw_affiliation_string":"Brandenburg University of Technology,Computer Engineering,Cottbus,Germany","institution_ids":["https://openalex.org/I51783024"]},{"raw_affiliation_string":"Computer Engineering, Brandenburg University of Technology, Cottbus, Germany","institution_ids":["https://openalex.org/I51783024"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053320135","display_name":"Jens Rettkowski","orcid":"https://orcid.org/0009-0002-4926-1984"},"institutions":[{"id":"https://openalex.org/I4210145666","display_name":"Embedded Systems (United States)","ror":"https://ror.org/04742eh45","country_code":"US","type":"company","lineage":["https://openalex.org/I4210145666"]},{"id":"https://openalex.org/I904495901","display_name":"Ruhr University Bochum","ror":"https://ror.org/04tsk2644","country_code":"DE","type":"education","lineage":["https://openalex.org/I904495901"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"Jens Rettkowski","raw_affiliation_strings":["Ruhr-University,Embedded Systems of Information Technology,Bochum,Germany","Embedded Systems of Information Technology, Ruhr-University, Bochum, Germany"],"affiliations":[{"raw_affiliation_string":"Ruhr-University,Embedded Systems of Information Technology,Bochum,Germany","institution_ids":["https://openalex.org/I4210145666","https://openalex.org/I904495901"]},{"raw_affiliation_string":"Embedded Systems of Information Technology, Ruhr-University, Bochum, Germany","institution_ids":["https://openalex.org/I904495901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051505653","display_name":"Arij Shallufa","orcid":null},"institutions":[{"id":"https://openalex.org/I904495901","display_name":"Ruhr University Bochum","ror":"https://ror.org/04tsk2644","country_code":"DE","type":"education","lineage":["https://openalex.org/I904495901"]},{"id":"https://openalex.org/I4210145666","display_name":"Embedded Systems (United States)","ror":"https://ror.org/04742eh45","country_code":"US","type":"company","lineage":["https://openalex.org/I4210145666"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"Arij Shallufa","raw_affiliation_strings":["Ruhr-University,Embedded Systems of Information Technology,Bochum,Germany","Embedded Systems of Information Technology, Ruhr-University, Bochum, Germany"],"affiliations":[{"raw_affiliation_string":"Ruhr-University,Embedded Systems of Information Technology,Bochum,Germany","institution_ids":["https://openalex.org/I4210145666","https://openalex.org/I904495901"]},{"raw_affiliation_string":"Embedded Systems of Information Technology, Ruhr-University, Bochum, Germany","institution_ids":["https://openalex.org/I904495901"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108437484","display_name":"Michael H\u00fcbner","orcid":"https://orcid.org/0000-0003-3785-7959"},"institutions":[{"id":"https://openalex.org/I51783024","display_name":"Brandenburg University of Technology Cottbus-Senftenberg","ror":"https://ror.org/02wxx3e24","country_code":"DE","type":"education","lineage":["https://openalex.org/I51783024"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael H\u00fcbner","raw_affiliation_strings":["Brandenburg University of Technology,Computer Engineering,Cottbus,Germany","Computer Engineering, Brandenburg University of Technology, Cottbus, Germany"],"affiliations":[{"raw_affiliation_string":"Brandenburg University of Technology,Computer Engineering,Cottbus,Germany","institution_ids":["https://openalex.org/I51783024"]},{"raw_affiliation_string":"Computer Engineering, Brandenburg University of Technology, Cottbus, Germany","institution_ids":["https://openalex.org/I51783024"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060626530","display_name":"Diana G\u00f6hringer","orcid":"https://orcid.org/0000-0003-2571-8441"},"institutions":[{"id":"https://openalex.org/I4210140143","display_name":"Dynamic Systems (United States)","ror":"https://ror.org/043vm9914","country_code":"US","type":"company","lineage":["https://openalex.org/I4210140143"]},{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"Diana G\u00f6hringer","raw_affiliation_strings":["Technische Universität,Adaptive Dynamic Systems,Dresden,Germany","Adaptive Dynamic Systems, Technische Universit\u00e4t, Dresden, Germany"],"affiliations":[{"raw_affiliation_string":"Technische Universität,Adaptive Dynamic Systems,Dresden,Germany","institution_ids":["https://openalex.org/I4210140143"]},{"raw_affiliation_string":"Adaptive Dynamic Systems, Technische Universit\u00e4t, Dresden, Germany","institution_ids":["https://openalex.org/I78650965"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5071483236"],"corresponding_institution_ids":["https://openalex.org/I51783024"],"apc_list":null,"apc_paid":null,"fwci":1.4446,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.82063658,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"103","last_page":"108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9997000098228455,"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9997000098228455,"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":0.9995999932289124,"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/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.9994999766349792,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.8996646404266357},{"id":"https://openalex.org/keywords/reconfigurability","display_name":"Reconfigurability","score":0.8573676347732544},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7770416736602783},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.6138491034507751},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5991615653038025},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5919640064239502},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.5247145891189575},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5197643637657166},{"id":"https://openalex.org/keywords/fpga-prototype","display_name":"FPGA prototype","score":0.51774662733078},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5008234977722168},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4928124248981476},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4315161108970642},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37161731719970703},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.3238222599029541},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.08834123611450195}],"concepts":[{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.8996646404266357},{"id":"https://openalex.org/C2780149590","wikidata":"https://www.wikidata.org/wiki/Q7302742","display_name":"Reconfigurability","level":2,"score":0.8573676347732544},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7770416736602783},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.6138491034507751},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5991615653038025},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5919640064239502},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.5247145891189575},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5197643637657166},{"id":"https://openalex.org/C203864433","wikidata":"https://www.wikidata.org/wiki/Q5426992","display_name":"FPGA prototype","level":3,"score":0.51774662733078},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5008234977722168},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4928124248981476},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4315161108970642},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37161731719970703},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.3238222599029541},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.08834123611450195}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce-berlin47944.2019.8966236","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce-berlin47944.2019.8966236","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 9th International Conference on Consumer Electronics (ICCE-Berlin)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W83593200","https://openalex.org/W1663973292","https://openalex.org/W1997144957","https://openalex.org/W2005006301","https://openalex.org/W2021705882","https://openalex.org/W2099105559","https://openalex.org/W2115573595","https://openalex.org/W2142659194","https://openalex.org/W2402144811","https://openalex.org/W2485563723","https://openalex.org/W2503894388","https://openalex.org/W2594639291","https://openalex.org/W2618530766","https://openalex.org/W2735766064","https://openalex.org/W2736263403","https://openalex.org/W2766343248","https://openalex.org/W2789876780","https://openalex.org/W2790420673","https://openalex.org/W2811483498","https://openalex.org/W2953384591","https://openalex.org/W2963456262","https://openalex.org/W4297747285","https://openalex.org/W4297785678","https://openalex.org/W6603379257","https://openalex.org/W6629510986","https://openalex.org/W6722478005","https://openalex.org/W6732127223"],"related_works":["https://openalex.org/W2159103767","https://openalex.org/W2998132311","https://openalex.org/W2207067480","https://openalex.org/W4383823603","https://openalex.org/W2082487009","https://openalex.org/W2332075903","https://openalex.org/W1579891439","https://openalex.org/W2291257309","https://openalex.org/W272033699","https://openalex.org/W1692883217"],"abstract_inverted_index":{"In":[0,72],"modern":[1,149],"day":[2],"industry":[3],"and":[4,36,69,81,106],"scientific":[5],"research,":[6],"pertaining":[7],"to":[8,49,56,79,104,148],"experimental":[9],"scenarios,":[10],"real":[11],"world":[12],"applications":[13],"or":[14,63,112,147],"consumer":[15],"electronics,":[16],"Field":[17],"Programmable":[18],"Gate":[19],"Arrays":[20],"(FPGAs)":[21],"are":[22],"becoming":[23],"a":[24,46,108],"popular":[25],"choice.":[26],"The":[27],"very":[28],"distinctive":[29],"nature":[30],"of":[31,38,67,88,130],"FPGAs":[32],"enables":[33],"reconfigurability,":[34],"scalability":[35],"adaptivity":[37],"the":[39],"associated":[40],"embedded":[41],"design":[42],"which":[43],"makes":[44],"it":[45],"remarkable":[47],"alternative":[48],"traditional":[50],"hardware.":[51],"An":[52],"FPGA":[53,83,124,131],"is":[54,77],"able":[55],"dynamically":[57],"reconfigure":[58],"itself":[59],"during":[60],"run-time,":[61],"entirely":[62],"partially,":[64],"by":[65,85,133],"way":[66],"unloading":[68],"loading":[70],"bitstreams.":[71,125],"this":[73],"paper,":[74],"an":[75,113,128],"approach":[76],"introduced":[78],"analyze":[80],"inspect":[82],"bitstreams":[84,132],"making":[86],"use":[87],"supervised":[89],"machine":[90,94],"learning.":[91],"By":[92],"exploiting":[93],"learning,":[95],"we":[96],"demonstrate":[97],"how":[98],"neural":[99],"networks":[100],"can":[101],"be":[102],"trained":[103],"identify":[105],"trace":[107],"certain":[109],"hardware":[110],"module":[111],"IP":[114],"core":[115],"(Intellectual":[116],"Property":[117],"core)":[118],"with":[119],"some":[120],"known":[121],"functionality":[122],"in":[123],"We":[126],"perform":[127],"analysis":[129],"incorporating":[134],"Artificial":[135],"Neural":[136,151],"Networks":[137,152],"(ANNs)":[138],"based":[139],"classification":[140],"ranging":[141],"from":[142],"Multiple":[143],"Layer":[144],"Perceptrons":[145],"(MLPs)":[146],"Convolutional":[150],"(CNNs).":[153]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}