{"id":"https://openalex.org/W7140878554","doi":"https://doi.org/10.1109/ieeeconf67917.2025.11443750","title":"Anomaly Detection in Resilient Networks: On the Impact of Delayed and False Decisions","display_name":"Anomaly Detection in Resilient Networks: On the Impact of Delayed and False Decisions","publication_year":2025,"publication_date":"2025-10-26","ids":{"openalex":"https://openalex.org/W7140878554","doi":"https://doi.org/10.1109/ieeeconf67917.2025.11443750"},"language":null,"primary_location":{"id":"doi:10.1109/ieeeconf67917.2025.11443750","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf67917.2025.11443750","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 59th Asilomar Conference on Signals, Systems, and Computers","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/A5035971695","display_name":"Friedemann Laue","orcid":"https://orcid.org/0000-0002-7477-8312"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Friedemann Laue","raw_affiliation_strings":["Friedrich-Alexander-Universität Erlangen-Nürnberg,Institute for Smart Electronics and Systems,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universität Erlangen-Nürnberg,Institute for Smart Electronics and Systems,Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050538234","display_name":"Maximilian L\u00fcbke","orcid":"https://orcid.org/0000-0001-6527-8925"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maximilian L\u00fcbke","raw_affiliation_strings":["Friedrich-Alexander-Universität Erlangen-Nürnberg,Institute for Smart Electronics and Systems,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universität Erlangen-Nürnberg,Institute for Smart Electronics and Systems,Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036049022","display_name":"Norman Franchi","orcid":"https://orcid.org/0000-0002-2777-4722"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Norman Franchi","raw_affiliation_strings":["Friedrich-Alexander-Universität Erlangen-Nürnberg,Institute for Smart Electronics and Systems,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universität Erlangen-Nürnberg,Institute for Smart Electronics and Systems,Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.74489025,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1501","last_page":"1507"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.18529999256134033,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.18529999256134033,"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/T12127","display_name":"Software System Performance and Reliability","score":0.18490000069141388,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.09589999914169312,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.4088999927043915},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.2906000018119812},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.2709999978542328},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.2653000056743622},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.249099999666214}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43140000104904175},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.4088999927043915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30550000071525574},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2709999978542328},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.249099999666214},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.24740000069141388},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.23960000276565552},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.23639999330043793}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieeeconf67917.2025.11443750","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieeeconf67917.2025.11443750","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 59th Asilomar Conference on Signals, Systems, and Computers","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.8247283101081848}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W45531478","https://openalex.org/W1980156780","https://openalex.org/W2561736116","https://openalex.org/W3080546164","https://openalex.org/W3209987567","https://openalex.org/W4206327130","https://openalex.org/W4382999283","https://openalex.org/W4386620197","https://openalex.org/W4387870976","https://openalex.org/W4388088642","https://openalex.org/W4389495275","https://openalex.org/W4389537432","https://openalex.org/W4389776450","https://openalex.org/W4393062337","https://openalex.org/W4403391197","https://openalex.org/W4406138709","https://openalex.org/W4408324720"],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"studies":[2],"a":[3,9,26,101,114,129,137],"resilient":[4],"communication":[5],"network":[6,22,46,58,127,174],"that":[7,55,146,167,180],"monitors":[8],"key":[10],"performance":[11,108,123],"indicator":[12],"(KPI)":[13],"to":[14,25,104],"detect":[15],"anomalies":[16],"and":[17,41,63,75,82,136,159,187],"disruptions.":[18],"Upon":[19],"detection,":[20,165],"the":[21,36,39,45,57,71,79,84,88,93,97,106,110,122,134,141,147,173,185,193,196],"automatically":[23],"reconfigures":[24],"recovery":[27,42,85,189],"state,":[28],"ensuring":[29],"reduced":[30],"but":[31],"stable":[32],"performance.":[33,175],"To":[34],"analyze":[35],"impact":[37],"of":[38,73,87,96,109,124,156,163,195],"detection":[40,80],"process":[43,81],"on":[44,92],"resilience,":[47],"we":[48,99,120],"propose":[49],"two":[50],"discrete-time":[51],"Markov":[52],"chains":[53],"(DTMCs)":[54],"model":[56,83,132],"dynamics":[59],"under":[60],"both":[61],"normal":[62],"challenging":[64],"conditions.":[65],"The":[66],"proposed":[67,148],"DTMCs":[68],"account":[69],"for":[70,116,133,184],"effects":[72],"delayed":[74],"false":[76,157,168],"decisions":[77,169],"in":[78],"capabilities":[86],"considered":[89,197],"network.":[90,198],"Based":[91],"statistical":[94],"properties":[95],"DTMCs,":[98],"derive":[100],"cost":[102,149],"function":[103,150],"evaluate":[105,121],"long-term":[107],"network,":[111],"serving":[112],"as":[113],"measure":[115],"resilience.":[117],"In":[118],"addition,":[119],"an":[125],"exemplary":[126],"using":[128],"Gaussian":[130],"signal":[131],"KPI":[135,186],"jamming":[138],"detector":[139],"from":[140,190],"literature.":[142],"Our":[143],"results":[144],"reveal":[145],"is":[151],"minimized":[152],"at":[153],"low":[154],"probabilities":[155,162],"alarm":[158],"relatively":[160],"high":[161],"miss":[164],"indicating":[166],"can":[170],"significantly":[171],"affect":[172],"Furthermore,":[176],"our":[177],"evaluation":[178],"shows":[179],"shorter":[181],"measurement":[182],"intervals":[183],"faster":[188],"disruptions":[191],"improve":[192],"resilience":[194]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-03-27T00:00:00"}