{"id":"https://openalex.org/W7147548806","doi":"https://doi.org/10.1109/cnml68938.2026.11453121","title":"Phase-Based Invisible Backdoor Attack","display_name":"Phase-Based Invisible Backdoor Attack","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7147548806","doi":"https://doi.org/10.1109/cnml68938.2026.11453121"},"language":null,"primary_location":{"id":"doi:10.1109/cnml68938.2026.11453121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"},"type":"article","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/A5114990580","display_name":"Chengyi Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chengyi Qiu","raw_affiliation_strings":["Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101446593","display_name":"Kai Xu","orcid":"https://orcid.org/0000-0001-6611-3516"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Xu","raw_affiliation_strings":["Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132668381","display_name":"Wenxun Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxun Wang","raw_affiliation_strings":["Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065259316","display_name":"Keping Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keping Xiao","raw_affiliation_strings":["Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China"],"affiliations":[{"raw_affiliation_string":"Wuhan University of Technology,School of Computer Science and Artificial Intelligence,Wuhan,China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5114990580"],"corresponding_institution_ids":["https://openalex.org/I196699116"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.94969185,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"328","last_page":"331"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9708999991416931,"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":0.9708999991416931,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.01209999993443489,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0034000000450760126,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/backdoor","display_name":"Backdoor","score":0.9884999990463257},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6079999804496765},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.35530000925064087},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3368000090122223},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3107999861240387},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.3066999912261963},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29330000281333923}],"concepts":[{"id":"https://openalex.org/C2781045450","wikidata":"https://www.wikidata.org/wiki/Q254569","display_name":"Backdoor","level":2,"score":0.9884999990463257},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6079999804496765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5250999927520752},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.512499988079071},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36559998989105225},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3612000048160553},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.31119999289512634},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3107999861240387},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.301800012588501},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.29260000586509705},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.2775000035762787},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2766000032424927},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C100921725","wikidata":"https://www.wikidata.org/wiki/Q1650811","display_name":"Spatial frequency","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.25999999046325684},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.25540000200271606}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cnml68938.2026.11453121","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453121","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.4528585970401764,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1834627138","https://openalex.org/W2067713319","https://openalex.org/W2096733369","https://openalex.org/W2155893237","https://openalex.org/W2194775991","https://openalex.org/W2897475915","https://openalex.org/W2934843808","https://openalex.org/W2942091739","https://openalex.org/W2979826702","https://openalex.org/W4226550712","https://openalex.org/W4312280786","https://openalex.org/W4312443924","https://openalex.org/W4312569687","https://openalex.org/W4390874616","https://openalex.org/W4392903451","https://openalex.org/W4393154709","https://openalex.org/W4408355329"],"related_works":[],"abstract_inverted_index":{"Deep":[0],"Neural":[1],"Networks":[2],"(DNNs)":[3],"are":[4],"vulnerable":[5],"to":[6,52,66],"backdoor":[7,11,44,95],"attacks.":[8],"However,":[9],"most":[10],"attacks":[12,25,96],"produce":[13],"poisoned":[14],"images":[15],"with":[16,92,115],"detectable":[17],"spatial":[18,28,75],"or":[19,30,76],"frequency":[20,77],"artifacts,":[21],"and":[22,60,86,97],"even":[23],"invisible":[24,43],"often":[26],"lack":[27],"smoothness":[29],"color":[31,58],"consistency.":[32],"To":[33],"address":[34],"these":[35],"limitations,":[36],"we":[37],"propose":[38],"PIBA,":[39],"a":[40],"novel":[41],"phase-based":[42],"attack.":[45],"PIBA":[46,81,109],"employs":[47],"Discrete":[48],"Wavelet":[49],"Transform":[50,64],"(DWT)":[51],"extract":[53],"low-scale":[54],"components,":[55],"followed":[56],"by":[57],"transformation":[59],"slide-window-based":[61],"Fast":[62],"Fourier":[63],"(FFT)":[65],"embed":[67],"phase":[68],"triggers,":[69],"ensuring":[70],"robust":[71],"attack":[72,111],"performance":[73,112],"without":[74],"artifacts.":[78],"We":[79],"evaluate":[80],"on":[82,113],"four":[83],"image":[84],"datasets":[85],"two":[87,102],"model":[88],"architectures,":[89],"comparing":[90],"it":[91],"five":[93],"state-of-the-art":[94,120],"testing":[98],"its":[99],"robustness":[100],"against":[101],"advanced":[103],"defenses.":[104],"Experimental":[105],"results":[106],"show":[107],"that":[108],"achieves":[110],"par":[114],"leading":[116],"methods":[117],"while":[118],"delivering":[119],"stealthiness":[121],"across":[122],"all":[123],"datasets.":[124]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}