{"id":"https://openalex.org/W3121429093","doi":"https://doi.org/10.1109/igsc51522.2020.9291232","title":"Conversion of an Unsupervised Anomaly Detection System to Spiking Neural Network for Car Hacking Identification","display_name":"Conversion of an Unsupervised Anomaly Detection System to Spiking Neural Network for Car Hacking Identification","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3121429093","doi":"https://doi.org/10.1109/igsc51522.2020.9291232","mag":"3121429093"},"language":"en","primary_location":{"id":"doi:10.1109/igsc51522.2020.9291232","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igsc51522.2020.9291232","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 11th International Green and Sustainable Computing Workshops (IGSC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5045304705","display_name":"Yassine Jaoudi","orcid":null},"institutions":[{"id":"https://openalex.org/I127591826","display_name":"University of Dayton","ror":"https://ror.org/021v3qy27","country_code":"US","type":"education","lineage":["https://openalex.org/I127591826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yassine Jaoudi","raw_affiliation_strings":["University of Dayton,Dept. of Electrical and Computer Engineering,Dayton,OH,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Dayton,Dept. of Electrical and Computer Engineering,Dayton,OH,USA","institution_ids":["https://openalex.org/I127591826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055959085","display_name":"Chris Yakopcic","orcid":"https://orcid.org/0000-0001-6401-272X"},"institutions":[{"id":"https://openalex.org/I127591826","display_name":"University of Dayton","ror":"https://ror.org/021v3qy27","country_code":"US","type":"education","lineage":["https://openalex.org/I127591826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chris Yakopcic","raw_affiliation_strings":["University of Dayton,Dept. of Electrical and Computer Engineering,Dayton,OH,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Dayton,Dept. of Electrical and Computer Engineering,Dayton,OH,USA","institution_ids":["https://openalex.org/I127591826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104090957","display_name":"Tarek M. Taha","orcid":null},"institutions":[{"id":"https://openalex.org/I127591826","display_name":"University of Dayton","ror":"https://ror.org/021v3qy27","country_code":"US","type":"education","lineage":["https://openalex.org/I127591826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tarek Taha","raw_affiliation_strings":["University of Dayton,Dept. of Electrical and Computer Engineering,Dayton,OH,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Dayton,Dept. of Electrical and Computer Engineering,Dayton,OH,USA","institution_ids":["https://openalex.org/I127591826"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I127591826"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.998199999332428,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.998199999332428,"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/T10581","display_name":"Neural dynamics and brain function","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9926000237464905,"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/autoencoder","display_name":"Autoencoder","score":0.8925607204437256},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.8537614941596985},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7705829739570618},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.7690736055374146},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6590383648872375},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5891202092170715},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.56538987159729},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5312680006027222},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44187504053115845},{"id":"https://openalex.org/keywords/hacker","display_name":"Hacker","score":0.43065890669822693},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4135643541812897},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4110584855079651},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34200045466423035},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.1958043873310089}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8925607204437256},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.8537614941596985},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7705829739570618},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.7690736055374146},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6590383648872375},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5891202092170715},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.56538987159729},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5312680006027222},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44187504053115845},{"id":"https://openalex.org/C86844869","wikidata":"https://www.wikidata.org/wiki/Q2798820","display_name":"Hacker","level":2,"score":0.43065890669822693},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4135643541812897},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4110584855079651},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34200045466423035},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.1958043873310089},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igsc51522.2020.9291232","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igsc51522.2020.9291232","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 11th International Green and Sustainable Computing Workshops (IGSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8600000143051147}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2106595237","https://openalex.org/W2122646361","https://openalex.org/W2133854595","https://openalex.org/W2296701710","https://openalex.org/W2414564754","https://openalex.org/W2561208905","https://openalex.org/W2620661538","https://openalex.org/W2775079417","https://openalex.org/W2783525259","https://openalex.org/W2790864385","https://openalex.org/W2814079182","https://openalex.org/W2890707978","https://openalex.org/W2897929592","https://openalex.org/W2959120033","https://openalex.org/W2963150511","https://openalex.org/W3105105644","https://openalex.org/W6950685506"],"related_works":["https://openalex.org/W3089892344","https://openalex.org/W4386227293","https://openalex.org/W4313442939","https://openalex.org/W4372267706","https://openalex.org/W2885510266","https://openalex.org/W2960220682","https://openalex.org/W4288055417","https://openalex.org/W4287758233","https://openalex.org/W4205804651","https://openalex.org/W3023142506"],"abstract_inverted_index":{"Across":[0],"industry,":[1],"there":[2],"is":[3,13,131],"an":[4,24,37,95,121],"increasing":[5],"availability":[6],"of":[7,27,61,80],"streaming,":[8],"time-varying":[9],"data,":[10],"where":[11],"it":[12],"important":[14],"to":[15,56,98,135],"detect":[16],"anomalous":[17,33],"behavior.":[18],"These":[19],"data":[20],"are":[21],"found":[22],"in":[23,30,40,85,129],"enormous":[25],"number":[26],"sensor-based":[28],"applications,":[29],"cybersecurity":[31],"(where":[32],"behavior":[34],"could":[35],"indicate":[36],"attack),":[38],"and":[39,120],"finance.":[41],"Spiking":[42],"Neural":[43],"Networks":[44],"(SNNs)":[45],"have":[46],"come":[47],"under":[48],"the":[49,57,68,78,109],"spotlight":[50],"for":[51,84],"machine":[52],"learning":[53,104],"applications":[54],"due":[55],"extreme":[58],"energy":[59],"efficiency":[60],"their":[62],"implementation":[63],"on":[64],"neuromorphic":[65],"processors":[66],"like":[67],"Intel":[69],"Loihi":[70],"research":[71],"chip.":[72],"In":[73],"this":[74],"paper":[75],"we":[76],"explore":[77],"applicability":[79],"spiking":[81,99],"neural":[82],"networks":[83],"vehicle":[86],"cyberattack":[87],"detection.":[88],"We":[89,101],"show":[90],"exemplary":[91],"results":[92],"by":[93],"converting":[94],"autoencoder":[96,112],"model":[97,105],"form.":[100],"present":[102],"a":[103,114,126,136],"comparison":[106],"that":[107],"shows":[108],"proposed":[110],"SNN":[111],"outperforms":[113],"One":[115],"Class":[116],"Support":[117],"Vector":[118],"Machine":[119],"Isolation":[122],"Forest.":[123],"Furthermore,":[124],"only":[125],"slight":[127],"reduction":[128],"accuracy":[130],"observed":[132],"when":[133],"compared":[134],"traditional":[137],"autoencoder.":[138]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
