{"id":"https://openalex.org/W3120396155","doi":"https://doi.org/10.1145/3412841.3441970","title":"DeepiSign","display_name":"DeepiSign","publication_year":2021,"publication_date":"2021-03-22","ids":{"openalex":"https://openalex.org/W3120396155","doi":"https://doi.org/10.1145/3412841.3441970","mag":"3120396155"},"language":"en","primary_location":{"id":"doi:10.1145/3412841.3441970","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3412841.3441970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 36th Annual ACM Symposium on Applied Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2101.04319","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Alsharif Abuadbba","orcid":null},"institutions":[{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Alsharif Abuadbba","raw_affiliation_strings":["Data61, Australia"],"affiliations":[{"raw_affiliation_string":"Data61, Australia","institution_ids":["https://openalex.org/I42894916"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hyoungshick Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU","KR"],"is_corresponding":false,"raw_author_name":"Hyoungshick Kim","raw_affiliation_strings":["Data61, Australia and Sungkyunkwan University, South Korea"],"affiliations":[{"raw_affiliation_string":"Data61, Australia and Sungkyunkwan University, South Korea","institution_ids":["https://openalex.org/I848706","https://openalex.org/I42894916"]}]},{"author_position":"last","author":{"id":null,"display_name":"Surya Nepal","orcid":null},"institutions":[{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Surya Nepal","raw_affiliation_strings":["Data61, Australia"],"affiliations":[{"raw_affiliation_string":"Data61, Australia","institution_ids":["https://openalex.org/I42894916"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I42894916"],"apc_list":null,"apc_paid":null,"fwci":1.2599,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.83059821,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"952","last_page":"959"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9998000264167786,"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":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9968000054359436,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9955000281333923,"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/verifiable-secret-sharing","display_name":"Verifiable secret sharing","score":0.8335999846458435},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.7641000151634216},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6388999819755554},{"id":"https://openalex.org/keywords/hash-chain","display_name":"Hash chain","score":0.4530999958515167},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43320000171661377},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4108000099658966},{"id":"https://openalex.org/keywords/security-analysis","display_name":"Security analysis","score":0.40689998865127563},{"id":"https://openalex.org/keywords/digital-watermarking","display_name":"Digital watermarking","score":0.40139999985694885}],"concepts":[{"id":"https://openalex.org/C85847156","wikidata":"https://www.wikidata.org/wiki/Q59015987","display_name":"Verifiable secret sharing","level":3,"score":0.8335999846458435},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.7641000151634216},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7633000016212463},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6388999819755554},{"id":"https://openalex.org/C135783594","wikidata":"https://www.wikidata.org/wiki/Q5678864","display_name":"Hash chain","level":3,"score":0.4530999958515167},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43320000171661377},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4108000099658966},{"id":"https://openalex.org/C38369872","wikidata":"https://www.wikidata.org/wiki/Q7445009","display_name":"Security analysis","level":2,"score":0.40689998865127563},{"id":"https://openalex.org/C150817343","wikidata":"https://www.wikidata.org/wiki/Q875932","display_name":"Digital watermarking","level":3,"score":0.40139999985694885},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.38839998841285706},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37779998779296875},{"id":"https://openalex.org/C164112704","wikidata":"https://www.wikidata.org/wiki/Q7974348","display_name":"Watermark","level":3,"score":0.3772999942302704},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36809998750686646},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.35690000653266907},{"id":"https://openalex.org/C7608002","wikidata":"https://www.wikidata.org/wiki/Q477202","display_name":"Cryptographic hash function","level":3,"score":0.3402000069618225},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.32100000977516174},{"id":"https://openalex.org/C3087436","wikidata":"https://www.wikidata.org/wiki/Q1386603","display_name":"Secret sharing","level":3,"score":0.3077999949455261},{"id":"https://openalex.org/C190157925","wikidata":"https://www.wikidata.org/wiki/Q1968605","display_name":"SHA-2","level":4,"score":0.30550000071525574},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3412841.3441970","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3412841.3441970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 36th Annual ACM Symposium on Applied Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2101.04319","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2101.04319","pdf_url":"https://arxiv.org/pdf/2101.04319","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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2101.04319","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2101.04319","pdf_url":"https://arxiv.org/pdf/2101.04319","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2045254342","https://openalex.org/W2108598243","https://openalex.org/W2119112357","https://openalex.org/W2194775991","https://openalex.org/W2579318729","https://openalex.org/W2594649210","https://openalex.org/W2753783305","https://openalex.org/W2787075213","https://openalex.org/W2806082141","https://openalex.org/W2934843808","https://openalex.org/W2963163009","https://openalex.org/W4252979261"],"related_works":[],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Networks":[2],"(CNNs)":[3],"deployed":[4],"in":[5,168],"real-life":[6],"applications":[7],"such":[8,20,69],"as":[9,21],"autonomous":[10],"vehicles":[11],"have":[12],"shown":[13],"to":[14,17,30,59,80,141,165],"be":[15],"vulnerable":[16],"manipulation":[18,70,209,235],"attacks,":[19],"poisoning":[22],"attacks":[23,210],"and":[24,34,45,63,85,97,116,148,182,196,203,216,230],"fine-tuning.":[25],"Hence,":[26],"it":[27,118],"is":[28,223],"essential":[29],"ensure":[31,60],"the":[32,61,74,95,100,104,107,110,114,120,126,129,133,145,150,175,180,227],"integrity":[33,62,96],"authenticity":[35,64,98],"of":[36,65,76,99,113,128,174,184,208],"CNNs":[37],"because":[38],"compromised":[39],"models":[40,67,192],"can":[41,162],"produce":[42],"incorrect":[43],"outputs":[44],"behave":[46],"maliciously.":[47],"In":[48],"this":[49],"paper,":[50],"we":[51,102,136,186],"propose":[52],"a":[53,83,90,138],"self-contained":[54],"tamper-proofing":[55],"method,":[56],"called":[57],"DeepiSign,":[58,185],"CNN":[66,91,134,234],"against":[68,205,232],"attacks.":[71,236],"DeepiSign":[72,161,222],"applies":[73],"idea":[75],"fragile":[77],"invisible":[78],"watermarking":[79],"securely":[81],"embed":[82,149],"secret":[84,105,131,151,167],"its":[86],"hash":[87,111,122],"value":[88,112],"into":[89,144,152],"model.":[92],"To":[93,124,178],"verify":[94],"model,":[101,108,135],"retrieve":[103],"from":[106],"compute":[109],"secret,":[115],"compare":[117],"with":[119,171],"embedded":[121,130],"value.":[123],"minimize":[125],"effects":[127],"on":[132,189],"use":[137],"wavelet-based":[139],"technique":[140],"transform":[142],"weights":[143],"frequency":[146],"domain":[147],"less":[153],"significant":[154],"coefficients.":[155],"Our":[156],"theoretical":[157],"analysis":[158],"shows":[159],"that":[160,221],"hide":[163],"up":[164],"1KB":[166],"each":[169],"layer":[170],"minimal":[172],"loss":[173],"model's":[176],"accuracy.":[177],"evaluate":[179],"security":[181],"performance":[183],"performed":[187],"experiments":[188],"four":[190],"pre-trained":[191],"(ResNet18,":[193],"VGG16,":[194],"AlexNet,":[195],"MobileNet)":[197],"using":[198],"three":[199,206],"datasets":[200],"(MNIST,":[201],"CIFAR-10,":[202],"Imagenet)":[204],"types":[207],"(targeted":[211],"input":[212],"poisoning,":[213,215],"output":[214],"fine-tuning).":[217],"The":[218],"results":[219],"demonstrate":[220],"verifiable":[224],"without":[225],"degrading":[226],"classification":[228],"accuracy,":[229],"robust":[231],"representative":[233]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2021-01-18T00:00:00"}
