{"id":"https://openalex.org/W4416283234","doi":"https://doi.org/10.1109/smc58881.2025.11343517","title":"Generative Adversarial Evasion and Out-of-Distribution Detection for UAV Cyber-Attacks","display_name":"Generative Adversarial Evasion and Out-of-Distribution Detection for UAV Cyber-Attacks","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W4416283234","doi":"https://doi.org/10.1109/smc58881.2025.11343517"},"language":"en","primary_location":{"id":"doi:10.1109/smc58881.2025.11343517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2506.21142","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014006642","display_name":"Deepak Kumar Panda","orcid":"https://orcid.org/0000-0001-8835-3908"},"institutions":[{"id":"https://openalex.org/I82284825","display_name":"Cranfield University","ror":"https://ror.org/05cncd958","country_code":"GB","type":"education","lineage":["https://openalex.org/I82284825"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Deepak Kumar Panda","raw_affiliation_strings":["Cranfield University,Faculty of Engineering and Applied Sciences,Cranfield,U.K,MK43 0AL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cranfield University,Faculty of Engineering and Applied Sciences,Cranfield,U.K,MK43 0AL","institution_ids":["https://openalex.org/I82284825"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062362866","display_name":"Weisi Guo","orcid":"https://orcid.org/0000-0003-3524-3953"},"institutions":[{"id":"https://openalex.org/I82284825","display_name":"Cranfield University","ror":"https://ror.org/05cncd958","country_code":"GB","type":"education","lineage":["https://openalex.org/I82284825"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Weisi Guo","raw_affiliation_strings":["Cranfield University,Faculty of Engineering and Applied Sciences,Cranfield,U.K,MK43 0AL"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cranfield University,Faculty of Engineering and Applied Sciences,Cranfield,U.K,MK43 0AL","institution_ids":["https://openalex.org/I82284825"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014006642"],"corresponding_institution_ids":["https://openalex.org/I82284825"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16978432,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6295","last_page":"6300"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.6549000144004822,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.6549000144004822,"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/T11133","display_name":"UAV Applications and Optimization","score":0.1362999975681305,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11489","display_name":"Air Traffic Management and Optimization","score":0.033399999141693115,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8468999862670898},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5188999772071838},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.43970000743865967},{"id":"https://openalex.org/keywords/evasion","display_name":"Evasion (ethics)","score":0.43630000948905945},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4122999906539917},{"id":"https://openalex.org/keywords/intrusion-detection-system","display_name":"Intrusion detection system","score":0.4072999954223633},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.37940001487731934},{"id":"https://openalex.org/keywords/flagging","display_name":"Flagging","score":0.3546000123023987}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8468999862670898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6650000214576721},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.52920001745224},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5188999772071838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5026000142097473},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4440999925136566},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.43970000743865967},{"id":"https://openalex.org/C2781251061","wikidata":"https://www.wikidata.org/wiki/Q5416089","display_name":"Evasion (ethics)","level":3,"score":0.43630000948905945},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4122999906539917},{"id":"https://openalex.org/C35525427","wikidata":"https://www.wikidata.org/wiki/Q745881","display_name":"Intrusion detection system","level":2,"score":0.4072999954223633},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38609999418258667},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.37940001487731934},{"id":"https://openalex.org/C2777548347","wikidata":"https://www.wikidata.org/wiki/Q5456937","display_name":"Flagging","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.3447999954223633},{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.33970001339912415},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C147494362","wikidata":"https://www.wikidata.org/wiki/Q2078905","display_name":"Troubleshooting","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C2776196576","wikidata":"https://www.wikidata.org/wiki/Q196113","display_name":"Camouflage","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C40305131","wikidata":"https://www.wikidata.org/wiki/Q2616305","display_name":"Obfuscation","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.2709999978542328},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.257099986076355},{"id":"https://openalex.org/C95713431","wikidata":"https://www.wikidata.org/wiki/Q631425","display_name":"Vulnerability (computing)","level":2,"score":0.2538999915122986}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/smc58881.2025.11343517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2506.21142","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.21142","pdf_url":"https://arxiv.org/pdf/2506.21142","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:doi:10.48550/arxiv.2506.21142","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2506.21142","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2506.21142","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2506.21142","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2506.21142","pdf_url":"https://arxiv.org/pdf/2506.21142","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W4213147678","https://openalex.org/W4402570343","https://openalex.org/W4401820158","https://openalex.org/W3115696055","https://openalex.org/W4382318179","https://openalex.org/W4226051630","https://openalex.org/W3116270459","https://openalex.org/W3008638899","https://openalex.org/W4390044127","https://openalex.org/W4293846201"],"related_works":[],"abstract_inverted_index":{"As":[0],"UAVs":[1],"are":[2,157],"increasingly":[3],"integrated":[4],"into":[5],"civilian":[6],"airspace,":[7],"the":[8,35,52,66,106,152,161,164,213,230,242],"need":[9],"for":[10],"resilient":[11],"intrusion":[12],"detection":[13,21,147],"system":[14],"(IDS)":[15],"frameworks":[16],"grow,":[17],"as":[18,38,102,189],"traditional":[19,207],"anomaly":[20],"methods":[22],"often":[23],"struggle":[24],"to":[25,33,54,64,85,145,159,192,237],"detect":[26,174,239],"novel":[27],"threats.":[28,250],"A":[29],"common":[30],"strategy":[31],"is":[32,184],"treat":[34],"unfamiliar":[36],"attacks":[37,69,89,223],"out-of-distribution":[39],"(OOD)":[40],"samples;":[41],"hence,":[42],"inadequate":[43],"mitigation":[44],"responses":[45],"can":[46],"leave":[47],"systems":[48],"vulnerable,":[49],"granting":[50],"adversaries":[51],"capability":[53],"cause":[55],"potential":[56],"damage.":[57],"Furthermore,":[58],"conventional":[59],"OOD":[60,71,165,198,225],"detectors":[61,210],"frequently":[62],"fail":[63],"discriminate":[65],"stealthy":[67,87,154,176,221,248],"adversarial":[68,79,88,142,155,177,194,222],"from":[70,111,196,224],"samples.":[72,199,226],"This":[73],"paper":[74],"proposes":[75],"a":[76,98,179,190],"conditional":[77,180],"generative":[78,153],"network":[80],"(cGAN)-based":[81],"framework":[82],"specifically":[83],"designed":[84],"craft":[86],"that":[90,212],"effectively":[91,173],"evade":[92,146],"IDS":[93,103,244],"mechanisms.":[94],"Initially,":[95],"we":[96],"construct":[97],"robust":[99],"multi-class":[100],"classifier":[101],"which":[104],"classifies":[105],"benign":[107,149],"UAV":[108],"telemetry":[109],"data":[110,121],"known":[112,137],"cyber-attack":[113],"types,":[114],"including":[115],"Denial":[116],"of":[117,163,232],"Service":[118],"(DoS),":[119],"false":[120],"injection":[122],"(FDI),":[123],"man-in-the-middle":[124],"(MiTM),":[125],"and":[126,206,240],"replay":[127],"attacks.":[128],"Leveraging":[129],"this":[130],"classifier,":[131],"our":[132],"proposed":[133],"cGAN":[134],"strategically":[135],"perturbs":[136],"attack":[138,170],"features,":[139],"generating":[140],"sophisticated":[141],"samples":[143,156,166,195],"engineered":[144],"through":[148],"misclassification.":[150],"Then,":[151],"refined":[158],"match":[160],"distribution":[162],"while":[167],"ensuring":[168],"high":[169],"success.":[171],"To":[172],"these":[175],"perturbations,":[178],"variational":[181],"autoencoder":[182],"(CVAE)":[183],"implemented,":[185],"using":[186],"negative":[187,215],"log-likelihood":[188,216],"metric":[191],"distinguish":[193],"genuine":[197],"Comparative":[200],"analyses":[201],"between":[202],"CVAE-based":[203],"regret":[204],"analysis":[205],"Mahalanobis":[208],"distance-based":[209],"demonstrate":[211],"CVAE\u2019s":[214],"significantly":[217],"outperforms":[218],"in":[219],"detecting":[220],"Our":[227],"findings":[228],"highlight":[229],"necessity":[231],"advanced":[233],"probabilistic":[234],"modeling":[235],"techniques":[236],"reliably":[238],"adapt":[241],"existing":[243],"against":[245],"novel,":[246],"generative-model-based":[247],"cyber":[249]},"counts_by_year":[],"updated_date":"2026-06-01T08:46:32.239190","created_date":"2025-10-10T00:00:00"}
