{"id":"https://openalex.org/W4385953416","doi":"https://doi.org/10.1007/s10207-023-00735-6","title":"Detection of adversarial attacks based on differences in image entropy","display_name":"Detection of adversarial attacks based on differences in image entropy","publication_year":2023,"publication_date":"2023-08-17","ids":{"openalex":"https://openalex.org/W4385953416","doi":"https://doi.org/10.1007/s10207-023-00735-6"},"language":"en","primary_location":{"id":"doi:10.1007/s10207-023-00735-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10207-023-00735-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10207-023-00735-6.pdf","source":{"id":"https://openalex.org/S164062316","display_name":"International Journal of Information Security","issn_l":"1615-5262","issn":["1615-5262","1615-5270"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Security","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10207-023-00735-6.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5069381273","display_name":"Gwonsang Ryu","orcid":"https://orcid.org/0000-0002-4713-9486"},"institutions":[{"id":"https://openalex.org/I141371507","display_name":"Soongsil University","ror":"https://ror.org/017xnm587","country_code":"KR","type":"education","lineage":["https://openalex.org/I141371507"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gwonsang Ryu","raw_affiliation_strings":["Cyber Security Research Center, Soongsil University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Cyber Security Research Center, Soongsil University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I141371507"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053797473","display_name":"Daeseon Choi","orcid":"https://orcid.org/0000-0002-1438-0265"},"institutions":[{"id":"https://openalex.org/I141371507","display_name":"Soongsil University","ror":"https://ror.org/017xnm587","country_code":"KR","type":"education","lineage":["https://openalex.org/I141371507"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Daeseon Choi","raw_affiliation_strings":["Department of Software, Soongsil University, Seoul, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Department of Software, Soongsil University, Seoul, Republic of Korea","institution_ids":["https://openalex.org/I141371507"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5053797473"],"corresponding_institution_ids":["https://openalex.org/I141371507"],"apc_list":{"value":2590,"currency":"EUR","value_usd":3190},"apc_paid":{"value":2590,"currency":"EUR","value_usd":3190},"fwci":2.6655,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.91918373,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"23","issue":"1","first_page":"299","last_page":"314"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998999834060669,"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":0.9998999834060669,"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9854000210762024,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9790999889373779,"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/adversarial-system","display_name":"Adversarial system","score":0.8654605150222778},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7857473492622375},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.598249614238739},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5383840799331665},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5374755263328552},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5188702344894409},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.453456848859787},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.404096782207489},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3795708417892456},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3745230436325073}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8654605150222778},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7857473492622375},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.598249614238739},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5383840799331665},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5374755263328552},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5188702344894409},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.453456848859787},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.404096782207489},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3795708417892456},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3745230436325073},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10207-023-00735-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10207-023-00735-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10207-023-00735-6.pdf","source":{"id":"https://openalex.org/S164062316","display_name":"International Journal of Information Security","issn_l":"1615-5262","issn":["1615-5262","1615-5270"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Security","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10207-023-00735-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10207-023-00735-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10207-023-00735-6.pdf","source":{"id":"https://openalex.org/S164062316","display_name":"International Journal of Information Security","issn_l":"1615-5262","issn":["1615-5262","1615-5270"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Security","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385953416.pdf"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W2007339694","https://openalex.org/W2108598243","https://openalex.org/W2180612164","https://openalex.org/W2194775991","https://openalex.org/W2243397390","https://openalex.org/W2302255633","https://openalex.org/W2535873859","https://openalex.org/W2565639579","https://openalex.org/W2603766943","https://openalex.org/W2604505099","https://openalex.org/W2607219512","https://openalex.org/W2611576673","https://openalex.org/W2618043096","https://openalex.org/W2774644650","https://openalex.org/W2798302089","https://openalex.org/W2947133760","https://openalex.org/W2947874337","https://openalex.org/W2962847335","https://openalex.org/W2962933288","https://openalex.org/W2963448658","https://openalex.org/W2963542245","https://openalex.org/W2963857521","https://openalex.org/W2964082701","https://openalex.org/W2964350391","https://openalex.org/W2967100019","https://openalex.org/W2984260944","https://openalex.org/W2990452356","https://openalex.org/W3006135495","https://openalex.org/W3034190247","https://openalex.org/W3034802054","https://openalex.org/W3035005405","https://openalex.org/W3035182590","https://openalex.org/W3044541995","https://openalex.org/W3088733693","https://openalex.org/W3094063482","https://openalex.org/W3102720581","https://openalex.org/W3108175762","https://openalex.org/W3160456797","https://openalex.org/W3198190218","https://openalex.org/W4225261186","https://openalex.org/W4289833633","https://openalex.org/W6603798796","https://openalex.org/W6821127250"],"related_works":["https://openalex.org/W2950183588","https://openalex.org/W3080754722","https://openalex.org/W3093978547","https://openalex.org/W3203790781","https://openalex.org/W2997056298","https://openalex.org/W2738001131","https://openalex.org/W4285785480","https://openalex.org/W3127875750","https://openalex.org/W4383221314","https://openalex.org/W2953536436"],"abstract_inverted_index":{"Abstract":[0],"Although":[1],"deep":[2],"neural":[3],"networks":[4],"(DNNs)":[5],"have":[6,32],"achieved":[7],"high":[8,62],"performance":[9],"across":[10],"various":[11,87],"applications,":[12],"they":[13],"are":[14],"often":[15],"deceived":[16],"by":[17,21,94,123],"adversarial":[18,27,57,88,92,120],"examples":[19,93,121],"generated":[20,122],"adding":[22],"small":[23],"perturbations.":[24],"To":[25],"combat":[26],"attacks,":[28],"many":[29],"detection":[30],"methods":[31,42],"been":[33],"proposed,":[34],"including":[35],"feature":[36],"squeezing":[37],"and":[38,65,75,105,136,148],"trapdoor.":[39],"However,":[40],"these":[41],"rely":[43],"on":[44],"the":[45,79,96,101,119,140],"output":[46],"of":[47,118],"DNNs":[48,85],"or":[49],"involve":[50],"training":[51],"a":[52,73],"separate":[53],"network":[54],"to":[55,61,83],"detect":[56,115],"examples,":[58],"which":[59],"leads":[60],"computational":[63],"costs":[64],"low":[66],"efficiency.":[67],"In":[68],"this":[69],"study,":[70],"we":[71],"propose":[72],"simple":[74],"effective":[76],"approach":[77],"called":[78],"entropy-based":[80],"detector":[81],"(EBD)":[82],"protect":[84],"from":[86],"attacks.":[89],"EBD":[90,113],"detects":[91],"comparing":[95],"difference":[97],"in":[98],"entropy":[99],"between":[100],"input":[102],"sample":[103],"before":[104],"after":[106],"bit":[107],"depth":[108],"reduction.":[109],"We":[110],"show":[111],"that":[112],"can":[114],"over":[116],"98%":[117],"attacks":[124,138],"using":[125],"fast-gradient":[126],"sign":[127],"method,":[128,131,134],"basic":[129],"iterative":[130,133],"momentum":[132],"DeepFool":[135],"CW":[137],"when":[139],"false":[141],"positive":[142],"rate":[143],"is":[144],"2.5%":[145],"for":[146],"CIFAR-10":[147],"ImageNet":[149],"datasets.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}