{"id":"https://openalex.org/W7167080344","doi":"https://doi.org/10.48550/arxiv.2607.01041","title":"Data-driven mitigation of catastrophic forgetting in dynamic physical layer attack detection","display_name":"Data-driven mitigation of catastrophic forgetting in dynamic physical layer attack detection","publication_year":2026,"publication_date":"2026-07-01","ids":{"openalex":"https://openalex.org/W7167080344","doi":"https://doi.org/10.48550/arxiv.2607.01041"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.01041","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.01041","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.01041","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052186392","display_name":"Aleksandra Knapi\u0144ska","orcid":"https://orcid.org/0000-0003-2654-4893"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Knapi\u0144ska, Aleksandra","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5062212458","display_name":"Marija Furdek","orcid":"https://orcid.org/0000-0001-5600-3700"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Furdek, Marija","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.34139999747276306,"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":0.34139999747276306,"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":0.1388999968767166,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.10180000215768814,"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/intrusion-detection-system","display_name":"Intrusion detection system","score":0.6635000109672546},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.6273000240325928},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.5820000171661377},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.499099999666214},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.46650001406669617},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4097000062465668},{"id":"https://openalex.org/keywords/intrusion","display_name":"Intrusion","score":0.3792000114917755},{"id":"https://openalex.org/keywords/network-security","display_name":"Network security","score":0.35600000619888306}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7074000239372253},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.6635000109672546},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.6273000240325928},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.5820000171661377},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.499099999666214},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.46650001406669617},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4097000062465668},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.40700000524520874},{"id":"https://openalex.org/C158251709","wikidata":"https://www.wikidata.org/wiki/Q354025","display_name":"Intrusion","level":2,"score":0.3792000114917755},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.35600000619888306},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32420000433921814},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3127000033855438},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.29679998755455017},{"id":"https://openalex.org/C65856478","wikidata":"https://www.wikidata.org/wiki/Q3991682","display_name":"Attack model","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C13540734","wikidata":"https://www.wikidata.org/wiki/Q5318996","display_name":"Dynamic network analysis","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C197298091","wikidata":"https://www.wikidata.org/wiki/Q5318963","display_name":"Dynamic data","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C196903269","wikidata":"https://www.wikidata.org/wiki/Q6059063","display_name":"Intrusion tolerance","level":3,"score":0.27000001072883606},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26600000262260437},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.263700008392334},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C2780741293","wikidata":"https://www.wikidata.org/wiki/Q4818019","display_name":"Attack patterns","level":3,"score":0.2612999975681305},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.01041","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.01041","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.01041","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.01041","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.644176185131073,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Optical":[0],"networks":[1],"are":[2],"critical":[3],"infrastructure":[4],"that":[5,13,208,221],"underpins":[6],"global":[7],"communications,":[8],"and":[9,127,240],"detecting":[10],"security":[11,190],"breaches":[12],"jeopardize":[14],"them":[15,80],"is":[16],"essential":[17],"to":[18,54,78,82,107,109,124,142,171,179,185,204,215,235,237],"maintaining":[19,58],"worldwide":[20],"connectivity.":[21],"As":[22],"malicious":[23],"actors":[24],"continuously":[25],"evolve":[26],"their":[27],"attack":[28,112,149,164,182],"techniques,":[29],"dynamically":[30],"updated":[31],"intrusion":[32,115],"detection":[33,60,116,150],"models":[34,51,75,92],"have":[35],"become":[36],"a":[37,69,119,139,168,216],"key":[38],"component":[39],"of":[40,72,85,130,162],"modern":[41],"defense":[42],"mechanisms.":[43],"By":[44],"incorporating":[45],"newly":[46],"acquired":[47,132],"telemetry":[48],"data,":[49],"these":[50],"can":[52,93],"adapt":[53,108,236],"emerging":[55],"threats":[56,126],"while":[57],"high":[59],"performance.":[61,242],"However,":[62],"when":[63],"previously":[64,110,131],"encountered":[65],"attacks":[66,96],"reappear":[67],"after":[68,175],"prolonged":[70],"period":[71],"absence,":[73],"adaptive":[74],"may":[76],"fail":[77],"recognize":[79],"due":[81,178],"the":[83,99,105,155,192,196,219],"phenomenon":[84],"catastrophic":[86,145],"forgetting.":[87],"In":[88,134],"contrast,":[89],"statically":[90],"trained":[91],"reliably":[94],"detect":[95],"represented":[97],"in":[98,147],"original":[100],"training":[101],"data":[102,173,212,233],"but":[103],"lack":[104],"ability":[106],"unseen":[111],"patterns.":[113],"Consequently,":[114],"systems":[117],"face":[118],"fundamental":[120],"tradeoff":[121],"between":[122],"adaptability":[123],"evolving":[125],"long-term":[128],"retention":[129],"knowledge.":[133],"this":[135],"work,":[136],"we":[137],"propose":[138],"data-driven":[140],"mechanism":[141,170],"cope":[143],"with":[144],"forgetting":[146],"dynamic":[148,206],"systems.":[151],"Our":[152],"approach":[153,194,229],"balances":[154],"model":[156,198],"update":[157],"datasets":[158],"by":[159,201],"using":[160],"parts":[161],"past":[163],"data.":[165],"We":[166],"utilize":[167],"threshold-based":[169],"trigger":[172],"balancing":[174],"accuracy":[176],"drops":[177],"an":[180,186],"active":[181],"change.":[183],"Applied":[184],"experimental":[187],"optical":[188],"network":[189,225],"dataset,":[191],"proposed":[193],"reduces":[195],"average":[197],"adaptation":[199],"time":[200],"37%":[202],"compared":[203],"its":[205],"counterpart":[207],"does":[209],"not":[210],"employ":[211],"balancing.":[213],"Compared":[214],"baseline":[217],"from":[218],"literature":[220],"relies":[222],"on":[223],"neural":[224],"depth":[226],"increasing,":[227],"our":[228],"requires":[230],"6%":[231],"fewer":[232],"batches":[234],"changing":[238],"conditions":[239],"regain":[241]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-03T00:00:00"}
