{"id":"https://openalex.org/W2896842194","doi":"https://doi.org/10.1109/icci-cc.2018.8482019","title":"Extracting Features from Both the Input and the Output of a Convolutional Neural Network to Detect Distributed Denial of Service Attacks","display_name":"Extracting Features from Both the Input and the Output of a Convolutional Neural Network to Detect Distributed Denial of Service Attacks","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2896842194","doi":"https://doi.org/10.1109/icci-cc.2018.8482019","mag":"2896842194"},"language":"en","primary_location":{"id":"doi:10.1109/icci-cc.2018.8482019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2018.8482019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 17th International Conference on Cognitive Informatics &amp; Cognitive Computing (ICCI*CC)","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/A5103872286","display_name":"Maryam Ghanbari","orcid":null},"institutions":[{"id":"https://openalex.org/I46247651","display_name":"University of Manitoba","ror":"https://ror.org/02gfys938","country_code":"CA","type":"education","lineage":["https://openalex.org/I46247651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Maryam Ghanbari","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Manitoba Winnipeg, Manitoba, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Manitoba Winnipeg, Manitoba, Canada","institution_ids":["https://openalex.org/I46247651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038834884","display_name":"Witold Kinsner","orcid":"https://orcid.org/0000-0002-6759-1410"},"institutions":[{"id":"https://openalex.org/I46247651","display_name":"University of Manitoba","ror":"https://ror.org/02gfys938","country_code":"CA","type":"education","lineage":["https://openalex.org/I46247651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Witold Kinsner","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Manitoba Winnipeg, Manitoba, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Manitoba Winnipeg, Manitoba, Canada","institution_ids":["https://openalex.org/I46247651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I46247651"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"138","last_page":"144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9997000098228455,"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":0.9997000098228455,"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/T10917","display_name":"Smart Grid Security and Resilience","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9973999857902527,"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/denial-of-service-attack","display_name":"Denial-of-service attack","score":0.9255760908126831},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8106648921966553},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6895838975906372},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6361359357833862},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47714802622795105},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4558575749397278},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.43547314405441284},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.431182324886322},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.4153457283973694},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.3722854554653168},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.36708128452301025},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.12662065029144287}],"concepts":[{"id":"https://openalex.org/C38822068","wikidata":"https://www.wikidata.org/wiki/Q131406","display_name":"Denial-of-service attack","level":3,"score":0.9255760908126831},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8106648921966553},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6895838975906372},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6361359357833862},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47714802622795105},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4558575749397278},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.43547314405441284},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.431182324886322},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.4153457283973694},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3722854554653168},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.36708128452301025},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.12662065029144287},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icci-cc.2018.8482019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icci-cc.2018.8482019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 17th International Conference on Cognitive Informatics &amp; Cognitive Computing (ICCI*CC)","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1470137088","https://openalex.org/W1605029620","https://openalex.org/W1910221752","https://openalex.org/W1967975009","https://openalex.org/W2055271538","https://openalex.org/W2119531181","https://openalex.org/W2121511513","https://openalex.org/W2785504727","https://openalex.org/W4395686181","https://openalex.org/W6748211623"],"related_works":["https://openalex.org/W2163073107","https://openalex.org/W3193301557","https://openalex.org/W2371096191","https://openalex.org/W2041246122","https://openalex.org/W2890138326","https://openalex.org/W1577789985","https://openalex.org/W4223656335","https://openalex.org/W2148116311","https://openalex.org/W2158240667","https://openalex.org/W2075963752"],"abstract_inverted_index":{"Distributed":[0],"Denial-of-Service":[1],"(DDoS)":[2],"attacks":[3],"are":[4],"serious":[5],"threats":[6],"to":[7,71,88,95],"a":[8,32,36,54],"smart":[9,37],"grid":[10],"infrastructure":[11],"services'":[12],"availability,":[13],"and":[14,50,92],"can":[15],"cause":[16],"massive":[17],"blackouts.":[18],"This":[19,39],"study":[20],"describes":[21],"an":[22],"anomaly":[23],"detection":[24,29],"method":[25],"for":[26,109],"improving":[27],"the":[28,45,48,63,76,89,93,115],"rate":[30],"of":[31,47,62],"DDoS":[33,116],"attack":[34,117],"in":[35,53],"grid.":[38],"improvement":[40],"was":[41,69,86,107],"achieved":[42],"by":[43],"increasing":[44],"classification":[46],"training":[49],"testing":[51],"phases":[52],"convolutional":[55],"neural":[56],"network":[57],"(CNN).":[58],"An":[59],"improved":[60],"version":[61],"variance":[64],"fractal":[65,78],"dimension":[66],"trajectory":[67],"(VFDTv2)":[68],"used":[70,108],"extract":[72,96],"inherent":[73],"features":[74,98],"from":[75],"non-pure":[77],"input":[79,90],"data.":[80],"A":[81,102],"discrete":[82],"wavelet":[83],"transform":[84],"(DWT)":[85],"applied":[87],"data":[91,100],"VFDTv2":[94],"distinguishing":[97],"during":[99],"pre-processing.":[101],"support":[103],"vector":[104],"machine":[105],"(SVM)":[106],"post":[110],"data-processing.":[111],"The":[112],"implementation":[113],"detected":[114],"with":[118],"87.35%":[119],"accuracy.":[120]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
