{"id":"https://openalex.org/W3015697750","doi":"https://doi.org/10.1109/icassp40776.2020.9053419","title":"Classifying Anomalies for Network Security","display_name":"Classifying Anomalies for Network Security","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015697750","doi":"https://doi.org/10.1109/icassp40776.2020.9053419","mag":"3015697750"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053419","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5013172264","display_name":"Hill Emily","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Emily H. Do","raw_affiliation_strings":["EECS, Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"EECS, Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043450560","display_name":"Vijay Gadepally","orcid":"https://orcid.org/0000-0002-4598-2808"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]},{"id":"https://openalex.org/I4210122954","display_name":"MIT Lincoln Laboratory","ror":"https://ror.org/022z6jk58","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vijay N. Gadepally","raw_affiliation_strings":["Lincoln Laboratory, Massachusetts Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Lincoln Laboratory, Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I4210122954","https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013172264"],"corresponding_institution_ids":["https://openalex.org/I63966007"],"apc_list":null,"apc_paid":null,"fwci":1.696,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.85059921,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":1.0,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9995999932289124,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/computer-science","display_name":"Computer science","score":0.8085999488830566},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6566821336746216},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6140064001083374},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.5938031673431396},{"id":"https://openalex.org/keywords/network-security","display_name":"Network security","score":0.5669307708740234},{"id":"https://openalex.org/keywords/traffic-classification","display_name":"Traffic classification","score":0.5466251969337463},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5461954474449158},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5326233506202698},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.511552631855011},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.48019421100616455},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.46879491209983826},{"id":"https://openalex.org/keywords/deep-packet-inspection","display_name":"Deep packet inspection","score":0.4170491099357605},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41102707386016846},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.21610212326049805},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.09523254632949829}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8085999488830566},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6566821336746216},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6140064001083374},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.5938031673431396},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.5669307708740234},{"id":"https://openalex.org/C169988225","wikidata":"https://www.wikidata.org/wiki/Q7832484","display_name":"Traffic classification","level":3,"score":0.5466251969337463},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5461954474449158},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5326233506202698},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.511552631855011},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.48019421100616455},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.46879491209983826},{"id":"https://openalex.org/C204679922","wikidata":"https://www.wikidata.org/wiki/Q734252","display_name":"Deep packet inspection","level":3,"score":0.4170491099357605},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41102707386016846},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.21610212326049805},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.09523254632949829},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053419","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W7191366","https://openalex.org/W1591480890","https://openalex.org/W2031163547","https://openalex.org/W2040333627","https://openalex.org/W2053550965","https://openalex.org/W2164210932","https://openalex.org/W2168388331","https://openalex.org/W2183325936","https://openalex.org/W2251322477","https://openalex.org/W2292233307","https://openalex.org/W2519887557","https://openalex.org/W2607918523","https://openalex.org/W2775103799","https://openalex.org/W2809097945","https://openalex.org/W2809932464","https://openalex.org/W2883672905","https://openalex.org/W2883778034","https://openalex.org/W2886020981","https://openalex.org/W2888240712","https://openalex.org/W2903199860","https://openalex.org/W2903266766","https://openalex.org/W2905224888","https://openalex.org/W2912119603","https://openalex.org/W2963695795","https://openalex.org/W2964015378","https://openalex.org/W2975370684","https://openalex.org/W2976036999","https://openalex.org/W3103749384","https://openalex.org/W3106525532","https://openalex.org/W3152893301","https://openalex.org/W6691504563","https://openalex.org/W6726873649","https://openalex.org/W6748799445","https://openalex.org/W6756622538","https://openalex.org/W6757374366"],"related_works":["https://openalex.org/W2041550843","https://openalex.org/W2537489883","https://openalex.org/W1976515580","https://openalex.org/W2017644937","https://openalex.org/W2917586021","https://openalex.org/W2012465643","https://openalex.org/W3011161512","https://openalex.org/W2928278548","https://openalex.org/W4301866626","https://openalex.org/W2062731068"],"abstract_inverted_index":{"Detecting":[0],"and":[1,26,59,69],"classifying":[2],"anomalous":[3],"behaviors":[4],"in":[5,48,102],"computer":[6],"networks":[7,23],"remains":[8],"a":[9,15,28,45,57],"formidable":[10],"challenge.":[11],"This":[12],"work":[13],"outlines":[14],"machine":[16,91],"learning":[17,92],"technique":[18],"that":[19,38,40,89],"uses":[20],"deep":[21],"neural":[22],"to":[24],"detect":[25],"classify":[27],"variety":[29],"of":[30,50,66,111],"network":[31,42,52,100],"attacks.":[32],"Our":[33],"approach":[34],"is":[35],"based":[36],"on":[37],"hypothesis":[39],"different":[41,67],"attacks":[43,65,101],"generate":[44,56],"distinguishable":[46],"change":[47],"entropy":[49],"certain":[51],"flow":[53],"features.":[54],"To":[55],"training":[58],"validation":[60],"dataset,":[61],"we":[62],"inject":[63],"synthetic":[64],"types":[68],"intensities":[70,105],"into":[71],"raw":[72],"packet":[73],"capture":[74],"data":[75],"collected":[76],"from":[77],"an":[78],"internet":[79],"backbone":[80],"link":[81],"by":[82],"the":[83],"MAWI":[84],"group.":[85],"Experimental":[86],"results":[87],"show":[88],"our":[90],"classification":[93],"model":[94],"can":[95],"achieve":[96],"high":[97],"accuracy":[98],"for":[99],"which":[103],"attack":[104],"are":[106],"as":[107,109],"low":[108],"5%":[110],"overall":[112],"traffic.":[113]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
