{"id":"https://openalex.org/W6926309935","doi":"https://doi.org/10.21227/6v53-jw45","title":"\"ServerSecurityProject Dataset for Peer Review\"","display_name":"\"ServerSecurityProject Dataset for Peer Review\"","publication_year":2025,"publication_date":"2025-06-25","ids":{"openalex":"https://openalex.org/W6926309935","doi":"https://doi.org/10.21227/6v53-jw45"},"language":"en","primary_location":{"id":"doi:10.21227/6v53-jw45","is_oa":true,"landing_page_url":"https://doi.org/10.21227/6v53-jw45","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.21227/6v53-jw45","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Aadya Srivastava","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Aadya Srivastava","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10252","display_name":"Microbial Natural Products and Biosynthesis","score":0.8598999977111816,"subfield":{"id":"https://openalex.org/subfields/2736","display_name":"Pharmacology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10252","display_name":"Microbial Natural Products and Biosynthesis","score":0.8598999977111816,"subfield":{"id":"https://openalex.org/subfields/2736","display_name":"Pharmacology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12858","display_name":"Plant Disease Resistance and Genetics","score":0.009100000374019146,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T13971","display_name":"Synthesis and Biological Activity","score":0.00800000037997961,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8673999905586243},{"id":"https://openalex.org/keywords/phishing","display_name":"Phishing","score":0.6046000123023987},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5884000062942505},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.524399995803833},{"id":"https://openalex.org/keywords/concept-drift","display_name":"Concept drift","score":0.49540001153945923},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42399999499320984},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4122999906539917},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4108000099658966}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8673999905586243},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6489999890327454},{"id":"https://openalex.org/C83860907","wikidata":"https://www.wikidata.org/wiki/Q135005","display_name":"Phishing","level":3,"score":0.6046000123023987},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.597000002861023},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5884000062942505},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5717999935150146},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.524399995803833},{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.49540001153945923},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42399999499320984},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4122999906539917},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4108000099658966},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.38119998574256897},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3671000003814697},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.3472999930381775},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.31060001254081726},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.3034000098705292},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.27900001406669617},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C52970973","wikidata":"https://www.wikidata.org/wiki/Q2497134","display_name":"Adaptive system","level":2,"score":0.2524999976158142},{"id":"https://openalex.org/C95922358","wikidata":"https://www.wikidata.org/wiki/Q5432725","display_name":"False positive rate","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21227/6v53-jw45","is_oa":true,"landing_page_url":"https://doi.org/10.21227/6v53-jw45","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"dataset"}],"best_oa_location":{"id":"doi:10.21227/6v53-jw45","is_oa":true,"landing_page_url":"https://doi.org/10.21227/6v53-jw45","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"\"Fuzzy":[0],"Logic":[1],"(FL)":[2],"has":[3],"largely":[4],"been":[5],"ignored":[6],"in":[7,214,218],"the":[8,102,142,181,200,208],"AI":[9],"revolution":[10],"despite":[11],"Machine":[12],"Learning":[13],"(ML)":[14],"algorithms":[15],"being":[16],"energy":[17],"and":[18,30,85,101,159,186],"training":[19,28,184],"inefficient.":[20],"As":[21],"problems":[22],"become":[23],"complex,":[24],"ML":[25,61,175],"embodies":[26],"increased":[27],"times":[29],"their":[31],"data":[32,124,202],"centers":[33],"continue":[34],"to":[35,49,62,98,113,122,127,141,163],"gain":[36],"prominence":[37],"as":[38],"polluting":[39],"centers.":[40],"This":[41,64,139,169,190],"study":[42],"developed":[43],"a":[44,69,171],"real-world":[45],"cyber":[46],"security":[47],"platform":[48,72,119],"detect":[50,128],"phishing":[51,137],"attacks,":[52],"dynamically,":[53],"using":[54,87],"auto-updating":[55],"feature":[56,212],"or":[57],"kernels":[58],"without":[59],"deploying":[60],"train.":[63],"study,":[65],"originally,":[66],"commenced":[67],"with":[68,81],"static":[70,174],"model":[71,194],"where":[73],"FL":[74,161],"would":[75,95,106],"generate":[76],"an":[77,114,145,165],"AUC":[78,115],"of":[79,104,116,144,210],"1.0":[80],"dynamically":[82],"derived":[83],"features":[84],"weights":[86],"Classification":[88],"Based":[89],"on":[90],"Association":[91],"(CBA).":[92],"However,":[93],"this":[94,193],"overfit":[96],"due":[97,135],"old":[99],"patterns":[100],"rate":[103],"detection":[105,188,216],"eventually":[107,133],"decline":[108],"by":[109],"15%":[110],"over":[111],"time":[112],"0.85\\u20130.90.":[117],"The":[118],"was":[120],"updated":[121],"deploy":[123],"drift":[125,203],"analysis":[126],"significant":[129],"degradation":[130],"(&gt;5%)":[131],"which":[132,151],"occurred":[134],"evolving":[136,219],"patterns.":[138],"led":[140],"creation":[143],"adaptive":[146,201],"(or":[147,154],"auto-updating)":[148],"fuzzy":[149],"system":[150],"used":[152],"regenerated":[153],"adapted)":[155],"features,":[156],"weights,":[157],"rules":[158],"other":[160],"aspects":[162],"ensure":[164],"AUC&nbsp;\\u2248\\u202f0.97":[166],"\\u2013":[167],"1.0.":[168],"marks":[170],"departure":[172],"from":[173],"based":[176],"learning":[177],"while":[178,199],"significantly":[179],"decreasing":[180],"feedback":[182],"loops,":[183],"time,":[185],"enhancing":[187],"frequency.":[189],"ensured":[191],"that":[192],"could":[195],"be":[196],"left":[197],"unattended":[198],"did":[204],"not":[205],"deviate,":[206],"underscoring":[207],"importance":[209],"data-driven":[211],"tuning":[213],"maintaining":[215],"efficacy":[217],"threat":[220],"landscapes.\"":[221]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}
