{"id":"https://openalex.org/W2887597525","doi":"https://doi.org/10.1109/hsi.2018.8430788","title":"Toward Explainable Deep Neural Network Based Anomaly Detection","display_name":"Toward Explainable Deep Neural Network Based Anomaly Detection","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2887597525","doi":"https://doi.org/10.1109/hsi.2018.8430788","mag":"2887597525"},"language":"en","primary_location":{"id":"doi:10.1109/hsi.2018.8430788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hsi.2018.8430788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Conference on Human System Interaction (HSI)","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/A5057592818","display_name":"Kasun Amarasinghe","orcid":"https://orcid.org/0000-0001-5143-3031"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kasun Amarasinghe","raw_affiliation_strings":["Virginia Commonwealth University, Richmond, Virginia, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Commonwealth University, Richmond, Virginia, USA","institution_ids":["https://openalex.org/I184840846"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108558832","display_name":"Kevin Kenney","orcid":null},"institutions":[{"id":"https://openalex.org/I2800102766","display_name":"Idaho National Laboratory","ror":"https://ror.org/00ty2a548","country_code":"US","type":"facility","lineage":["https://openalex.org/I1325736334","https://openalex.org/I1330989302","https://openalex.org/I2800102766","https://openalex.org/I2801818860"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin Kenney","raw_affiliation_strings":["Idaho National Laboratory, Idaho Falls, Idaho, USA"],"affiliations":[{"raw_affiliation_string":"Idaho National Laboratory, Idaho Falls, Idaho, USA","institution_ids":["https://openalex.org/I2800102766"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032679061","display_name":"Milos Manic","orcid":"https://orcid.org/0000-0003-1484-7678"},"institutions":[{"id":"https://openalex.org/I184840846","display_name":"Virginia Commonwealth University","ror":"https://ror.org/02nkdxk79","country_code":"US","type":"education","lineage":["https://openalex.org/I184840846"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Milos Manic","raw_affiliation_strings":["Virginia Commonwealth University, Richmond, Virginia, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Commonwealth University, Richmond, Virginia, USA","institution_ids":["https://openalex.org/I184840846"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057592818"],"corresponding_institution_ids":["https://openalex.org/I184840846"],"apc_list":null,"apc_paid":null,"fwci":7.2775,"has_fulltext":false,"cited_by_count":124,"citation_normalized_percentile":{"value":0.9763929,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"311","last_page":"317"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9854999780654907,"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/anomaly-detection","display_name":"Anomaly detection","score":0.6958804130554199},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6867027282714844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5399541854858398},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5089981555938721},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3296751379966736}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6958804130554199},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6867027282714844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5399541854858398},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5089981555938721},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3296751379966736}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hsi.2018.8430788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hsi.2018.8430788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 11th International Conference on Human System Interaction (HSI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5299999713897705,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1787224781","https://openalex.org/W1971751469","https://openalex.org/W2005708641","https://openalex.org/W2016258134","https://openalex.org/W2031032942","https://openalex.org/W2037411704","https://openalex.org/W2064551186","https://openalex.org/W2120617515","https://openalex.org/W2122217421","https://openalex.org/W2122301654","https://openalex.org/W2146196597","https://openalex.org/W2150165932","https://openalex.org/W2158958729","https://openalex.org/W2162275200","https://openalex.org/W2167287136","https://openalex.org/W2186910770","https://openalex.org/W2340896621","https://openalex.org/W2342408547","https://openalex.org/W2398119937","https://openalex.org/W2460849547","https://openalex.org/W2472119793","https://openalex.org/W2559927751","https://openalex.org/W2561208905","https://openalex.org/W2588161617","https://openalex.org/W2657631929","https://openalex.org/W2739349903","https://openalex.org/W2742553656","https://openalex.org/W2743138268","https://openalex.org/W2753415590","https://openalex.org/W2797283471","https://openalex.org/W2919115771","https://openalex.org/W2963542836","https://openalex.org/W4231980343","https://openalex.org/W4297814361","https://openalex.org/W4299408792","https://openalex.org/W6704694796","https://openalex.org/W6733675496"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,21,48,66],"in":[2,26,41,45,126],"industrial":[3,46],"processes":[4],"is":[5,38,84,91],"crucial":[6],"for":[7,62,144],"general":[8],"process":[9,12],"monitoring":[10],"and":[11,88,120,170],"health":[13],"assessment.":[14],"Deep":[15],"Neural":[16],"Networks":[17],"(DNNs)":[18],"based":[19,64,117,162],"anomaly":[20,47,65,118],"has":[22],"received":[23],"increased":[24],"attention":[25],"recent":[27],"work.":[28],"Albeit":[29],"their":[30],"high":[31],"accuracy,":[32],"the":[33,76,92,95,103,106,112,115,127,132,136,140,156],"black-box":[34],"nature":[35],"of":[36,51,70,105,114,135,146,167,172],"DNNs":[37],"a":[39,60],"drawback":[40],"practical":[42],"deployment.":[43],"Especially":[44],"systems,":[49],"explanations":[50,69,153],"DNN":[52,63,116,152,157],"detected":[53,71],"anomalies":[54],"are":[55],"crucial.":[56],"This":[57,129],"paper":[58,130],"presents":[59],"framework":[61,74,96,110,138],"which":[67],"provides":[68],"anomalies.":[72],"The":[73,109],"answers":[75],"following":[77],"questions":[78],"during":[79],"online":[80],"processing:":[81],"1)":[82],"\u201cwhy":[83],"it":[85],"an":[86,177],"anomaly?\u201d":[87],"2)":[89],"\u201cwhat":[90],"confidence?\u201d":[93],"Further,":[94],"can":[97],"be":[98],"used":[99],"offline":[100],"to":[101],"evaluate":[102],"\u201cknowledge\u201d":[104],"trained":[107],"DNN.":[108],"reduces":[111],"opaqueness":[113],"detector":[119],"thus":[121],"improves":[122],"human":[123],"operators'":[124],"trust":[125],"algorithm.":[128],"implements":[131],"first":[133],"steps":[134],"presented":[137],"on":[139,163],"benchmark":[141],"KDD-NSL":[142],"dataset":[143],"Denial":[145],"Service":[147],"(DoS)":[148],"attack":[149],"detection.":[150],"Offline":[151],"showed":[154],"that":[155],"was":[158],"detecting":[159],"DoS":[160],"attacks":[161],"features":[164],"indicating":[165],"destination":[166],"connection,":[168],"frequency":[169],"amount":[171],"data":[173],"transferred":[174],"while":[175],"showing":[176],"accuracy":[178],"around":[179],"97%.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":26},{"year":2021,"cited_by_count":23},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}
