{"id":"https://openalex.org/W3016764799","doi":null,"title":"DETECTION OF DDOS ATTACKS BASED ON DENSE NEURAL NETWORKS, AUTOENCODERS AND PEARSON CORRELATION COEFFICIENT","display_name":"DETECTION OF DDOS ATTACKS BASED ON DENSE NEURAL NETWORKS, AUTOENCODERS AND PEARSON CORRELATION COEFFICIENT","publication_year":2020,"publication_date":"2020-04-16","ids":{"openalex":"https://openalex.org/W3016764799","mag":"3016764799"},"language":"en","primary_location":{"id":"pmh:oai:dal.scholaris.ca:10222/78536","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/10222/78536","pdf_url":null,"source":{"id":"https://openalex.org/S7407064432","display_name":"DalSpace (Dalhousie University)","issn_l":"2041-2096","issn":["2041-2096"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["dongbi-a","poland-140","russia-white-list-1"],"host_organization":"https://openalex.org/I129902397","host_organization_name":"Dalhousie University","host_organization_lineage":["https://openalex.org/I129902397"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5100782051","display_name":"Junhong Li","orcid":"https://orcid.org/0000-0002-4864-0897","observed_orcids":["https://orcid.org/0000-0002-4864-0897","https://orcid.org/0009-0007-3590-9555"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Junhong Li","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-4864-0897","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5100782051"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8478,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.73431811,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"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":0.9994999766349792,"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":0.9994999766349792,"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":0.00019999999494757503,"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/T12326","display_name":"Network Packet Processing and Optimization","score":9.999999747378752e-05,"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/ddos-detection","display_name":"DDoS attack detection","score":0.9890000224113464},{"id":"https://openalex.org/keywords/ddos-attacks","display_name":"DDoS attacks","score":0.9359999895095825},{"id":"https://openalex.org/keywords/dense-neural-networks","display_name":"dense neural networks","score":0.8109999895095825},{"id":"https://openalex.org/keywords/autoencoder","display_name":"autoencoder","score":0.9959999918937683},{"id":"https://openalex.org/keywords/pearson-correlation","display_name":"Pearson correlation","score":0.9959999918937683},{"id":"https://openalex.org/keywords/cicddos2019","display_name":"CICDDoS2019","score":0.9129999876022339},{"id":"https://openalex.org/keywords/pcap-files","display_name":"PCAP files","score":0.5580000281333923},{"id":"https://openalex.org/keywords/network-traffic-classification","display_name":"network traffic classification","score":0.640999972820282},{"id":"https://openalex.org/keywords/attack-classification","display_name":"attack classification","score":0.48100000619888306},{"id":"https://openalex.org/keywords/feature-compression","display_name":"feature compression","score":0.5080000162124634},{"id":"https://openalex.org/keywords/udp-flood","display_name":"UDP flood","score":0.503000020980835},{"id":"https://openalex.org/keywords/syn-flood","display_name":"SYN flood","score":0.6980000138282776}],"concepts":[{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.8295486569404602},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.6797691583633423},{"id":"https://openalex.org/C38822068","wikidata":"https://www.wikidata.org/wiki/Q131406","display_name":"Denial-of-service attack","level":3,"score":0.6536456942558289},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6266847848892212},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5084933042526245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4968924820423126},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4381507635116577},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4234592020511627},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4022999405860901},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2711399495601654},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.07611092925071716},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"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":2,"locations":[{"id":"pmh:oai:dal.scholaris.ca:10222/78536","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/10222/78536","pdf_url":null,"source":{"id":"https://openalex.org/S7407064432","display_name":"DalSpace (Dalhousie University)","issn_l":"2041-2096","issn":["2041-2096"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["dongbi-a","poland-140","russia-white-list-1"],"host_organization":"https://openalex.org/I129902397","host_organization_name":"Dalhousie University","host_organization_lineage":["https://openalex.org/I129902397"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},{"id":"mag:3016764799","doi":null,"is_oa":false,"landing_page_url":"https://dalspace.library.dal.ca/handle/10222/78536","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1674877186","https://openalex.org/W1966741850","https://openalex.org/W1976166354","https://openalex.org/W1977263765","https://openalex.org/W2042495914","https://openalex.org/W2060386404","https://openalex.org/W2087766914","https://openalex.org/W2096118443","https://openalex.org/W2109563611","https://openalex.org/W2111890927","https://openalex.org/W2118050553","https://openalex.org/W2129864758","https://openalex.org/W2136087862","https://openalex.org/W2151554678","https://openalex.org/W2155545199","https://openalex.org/W2155883880","https://openalex.org/W2158698691","https://openalex.org/W2162969618","https://openalex.org/W2171744244","https://openalex.org/W2296269467","https://openalex.org/W2365795845","https://openalex.org/W2532890539","https://openalex.org/W2566297732","https://openalex.org/W2762776925","https://openalex.org/W2775103799","https://openalex.org/W2790319517","https://openalex.org/W2790583291","https://openalex.org/W2904332864","https://openalex.org/W2904539465","https://openalex.org/W2918854598","https://openalex.org/W2921453769","https://openalex.org/W2933912020","https://openalex.org/W2944006848","https://openalex.org/W2944992190","https://openalex.org/W2947339731","https://openalex.org/W2950832684","https://openalex.org/W2951058227","https://openalex.org/W2979354191","https://openalex.org/W2980115220","https://openalex.org/W2982682021","https://openalex.org/W3004752684"],"related_works":["https://openalex.org/W4386981677","https://openalex.org/W7027866952","https://openalex.org/W4408429129","https://openalex.org/W4412626896","https://openalex.org/W3117819143","https://openalex.org/W4288033219","https://openalex.org/W4206676437","https://openalex.org/W2960339583","https://openalex.org/W4293046456","https://openalex.org/W4281657813"],"abstract_inverted_index":{"Distributed":[0],"Denial":[1],"of":[2,8,44,52,66,197,217,223,253],"Service":[3,115],"(DDoS)":[4],"is":[5,32,47,100,163,225,257],"a":[6,64,168,212,232],"set":[7,230],"frequent":[9],"cyber":[10],"attacks":[11,18,224],"used":[12,159,174,190],"against":[13],"public":[14],"servers.":[15],"Because":[16],"DDoS":[17,53,94,192],"can":[19],"be":[20,173,189],"launched":[21],"remotely":[22],"and":[23,38,71,83,105,149,201],"reflected":[24],"by":[25,63],"legit-":[26],"imated":[27],"users":[28],"on":[29,220],"networks,":[30,69],"it":[31],"hard":[33],"for":[34],"victims":[35],"to":[36,48,87,175,188],"detect":[37],"prevent":[39],"them.":[40],"The":[41,194,215,227,240],"ob-":[42],"jective":[43],"this":[45,161],"thesis":[46,162,228],"explore":[49],"the":[50,91,97,103,153,157,177,208,244,251,254],"detection":[51],"attacks,":[54],"especially":[55],"those":[56],"that":[57],"have":[58],"arisen":[59],"in":[60,160,191,206],"recent":[61,93],"years,":[62],"combination":[65],"dense":[67],"neural":[68],"autoencoders":[70],"Pearson":[72,202],"Correlation":[73,203],"Coefficient.":[74],"Three":[75,182],"different":[76,183,221],"classification":[77,248],"models":[78,185,195,242,256],"are":[79,186],"de-":[80],"signed,":[81],"trained":[82],"tested.":[84],"In":[85],"order":[86],"gain":[88],"information":[89],"about":[90],"most":[92],"attack":[95],"types,":[96],"CICDDoS2019":[98],"dataset":[99,109],"selected":[101],"as":[102,211],"training":[104],"testing":[106],"set.":[107],"This":[108],"contains":[110],"Microsoft":[111],"SQL":[112],"Server(MSSQL),":[113],"Simple":[114,138],"Discovery":[116],"Pro-":[117],"tocol(SSDP),":[118],"Network":[119,139],"Time":[120],"Protocol(NTP),":[121],"Trivial":[122],"File":[123],"Transfer":[124],"Protocol(TFTP),":[125],"Domain":[126],"Name":[127],"System(DNS),":[128],"Lightweight":[129],"Directory":[130],"Access":[131],"Protocol(LDAP),":[132],"Net-":[133],"work":[134],"Basic":[135],"Input/Output":[136],"System(NetBIOS),":[137],"Management":[140],"Proto-":[141],"col(SNMP),":[142],"SYN":[143],"flood,":[144],"User":[145],"Datagram":[146],"Protocol(UDP)":[147],"flood":[148],"UDP-Lag.":[150],"To":[151],"imitate":[152],"real":[154],"network":[155],"environment,":[156],"data":[158],"raw":[164,178],"PCAP":[165],"files.":[166],"CIC-FlowMeter,":[167],"packet":[169],"analysis":[170],"tool,":[171],"will":[172],"convert":[176],"packets":[179],"into":[180],"features.":[181],"deep-learning":[184],"proposed":[187,241,255],"detection.":[193],"consist":[196],"DNN,":[198],"Auto":[199],"Encoder":[200],"Coef-":[204],"ficient,":[205],"which":[207],"autoencoder":[209],"works":[210],"feature":[213],"compressor.":[214],"performance":[216],"each":[218],"model":[219],"types":[222],"compared.":[226],"also":[229],"up":[231],"bench-":[233],"mark":[234],"using":[235],"traditional":[236,245],"machine":[237,246],"learning":[238,247],"models.":[239,249],"outperform":[243],"Furthermore,":[250],"F1-score":[252],"higher":[258],"than":[259],"other":[260],"approaches.":[261]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3}],"updated_date":"2026-11-03T10:50:19.383937","created_date":"2020-04-24T00:00:00"}
