{"id":"https://openalex.org/W4416962048","doi":"https://doi.org/10.1109/icumt67815.2025.11268583","title":"Multi-Domain Information-Theoretic Features and Kolmogorov Complexity for Lightweight Image Splicing Detection","display_name":"Multi-Domain Information-Theoretic Features and Kolmogorov Complexity for Lightweight Image Splicing Detection","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W4416962048","doi":"https://doi.org/10.1109/icumt67815.2025.11268583"},"language":null,"primary_location":{"id":"doi:10.1109/icumt67815.2025.11268583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icumt67815.2025.11268583","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 17th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)","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/A5101321576","display_name":"Naman Tyagi","orcid":null},"institutions":[{"id":"https://openalex.org/I191972202","display_name":"Amity University","ror":"https://ror.org/02n9z0v62","country_code":"IN","type":"education","lineage":["https://openalex.org/I191972202"]},{"id":"https://openalex.org/I4210126505","display_name":"Amity University","ror":"https://ror.org/02exxtn84","country_code":"AE","type":"education","lineage":["https://openalex.org/I191972202","https://openalex.org/I4210126505"]}],"countries":["AE","IN"],"is_corresponding":true,"raw_author_name":"Naman Tyagi","raw_affiliation_strings":["Amity University,Amity School of Engineering & Technology,Dept. of CSE,Noida,Uttar Pradesh,India"],"affiliations":[{"raw_affiliation_string":"Amity University,Amity School of Engineering & Technology,Dept. of CSE,Noida,Uttar Pradesh,India","institution_ids":["https://openalex.org/I191972202","https://openalex.org/I4210126505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005485404","display_name":"Rakesh Chandra Joshi","orcid":"https://orcid.org/0000-0003-1264-9010"},"institutions":[{"id":"https://openalex.org/I191972202","display_name":"Amity University","ror":"https://ror.org/02n9z0v62","country_code":"IN","type":"education","lineage":["https://openalex.org/I191972202"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rakesh Chandra Joshi","raw_affiliation_strings":["Amity University,Amity Centre for Artificial Intelligence,Noida,Uttar Pradesh,India"],"affiliations":[{"raw_affiliation_string":"Amity University,Amity Centre for Artificial Intelligence,Noida,Uttar Pradesh,India","institution_ids":["https://openalex.org/I191972202"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Srishti Das","orcid":null},"institutions":[{"id":"https://openalex.org/I191972202","display_name":"Amity University","ror":"https://ror.org/02n9z0v62","country_code":"IN","type":"education","lineage":["https://openalex.org/I191972202"]},{"id":"https://openalex.org/I4210126505","display_name":"Amity University","ror":"https://ror.org/02exxtn84","country_code":"AE","type":"education","lineage":["https://openalex.org/I191972202","https://openalex.org/I4210126505"]}],"countries":["AE","IN"],"is_corresponding":false,"raw_author_name":"Srishti Das","raw_affiliation_strings":["Amity University,Amity School of Engineering & Technology,Dept. of CSE,Noida,Uttar Pradesh,India"],"affiliations":[{"raw_affiliation_string":"Amity University,Amity School of Engineering & Technology,Dept. of CSE,Noida,Uttar Pradesh,India","institution_ids":["https://openalex.org/I191972202","https://openalex.org/I4210126505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086150397","display_name":"\u00ad Kunal","orcid":null},"institutions":[{"id":"https://openalex.org/I191972202","display_name":"Amity University","ror":"https://ror.org/02n9z0v62","country_code":"IN","type":"education","lineage":["https://openalex.org/I191972202"]},{"id":"https://openalex.org/I4210126505","display_name":"Amity University","ror":"https://ror.org/02exxtn84","country_code":"AE","type":"education","lineage":["https://openalex.org/I191972202","https://openalex.org/I4210126505"]}],"countries":["AE","IN"],"is_corresponding":false,"raw_author_name":"Kunal","raw_affiliation_strings":["Amity University,Amity School of Engineering & Technology,Dept. of CSE,Noida,Uttar Pradesh,India"],"affiliations":[{"raw_affiliation_string":"Amity University,Amity School of Engineering & Technology,Dept. of CSE,Noida,Uttar Pradesh,India","institution_ids":["https://openalex.org/I191972202","https://openalex.org/I4210126505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120540844","display_name":"Schiller Vojtech","orcid":null},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Schiller Vojtech","raw_affiliation_strings":["FEEC, Brno University of Technology,Dept. of Telecommunications,Brno,Czech Republic"],"affiliations":[{"raw_affiliation_string":"FEEC, Brno University of Technology,Dept. of Telecommunications,Brno,Czech Republic","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jezek Stepan","orcid":null},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Jezek Stepan","raw_affiliation_strings":["FEEC, Brno University of Technology,Dept. of Telecommunications,Brno,Czech Republic"],"affiliations":[{"raw_affiliation_string":"FEEC, Brno University of Technology,Dept. of Telecommunications,Brno,Czech Republic","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038343229","display_name":"Malay Kishore Dutta","orcid":"https://orcid.org/0000-0003-2462-737X"},"institutions":[{"id":"https://openalex.org/I191972202","display_name":"Amity University","ror":"https://ror.org/02n9z0v62","country_code":"IN","type":"education","lineage":["https://openalex.org/I191972202"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Malay Kishore Dutta","raw_affiliation_strings":["Amity University,Amity Centre for Artificial Intelligence,Noida,Uttar Pradesh,India"],"affiliations":[{"raw_affiliation_string":"Amity University,Amity Centre for Artificial Intelligence,Noida,Uttar Pradesh,India","institution_ids":["https://openalex.org/I191972202"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101321576"],"corresponding_institution_ids":["https://openalex.org/I191972202","https://openalex.org/I4210126505"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37660222,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"227","last_page":"233"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9930999875068665,"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"}},"topics":[{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9930999875068665,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.0013000000035390258,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.0008999999845400453,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.878600001335144},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7358999848365784},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.555400013923645},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5339999794960022},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5239999890327454},{"id":"https://openalex.org/keywords/rna-splicing","display_name":"RNA splicing","score":0.5224000215530396},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.45739999413490295},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.43230000138282776},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41780000925064087}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.878600001335144},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7358999848365784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6624000072479248},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6477000117301941},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.555400013923645},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5339999794960022},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5239999890327454},{"id":"https://openalex.org/C54458228","wikidata":"https://www.wikidata.org/wiki/Q237218","display_name":"RNA splicing","level":4,"score":0.5224000215530396},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45899999141693115},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45739999413490295},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.43230000138282776},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41780000925064087},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4083999991416931},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.39100000262260437},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C52622258","wikidata":"https://www.wikidata.org/wiki/Q131222","display_name":"Information theory","level":2,"score":0.34850001335144043},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3370000123977661},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3343000113964081},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3264000117778778},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C42781572","wikidata":"https://www.wikidata.org/wiki/Q1250322","display_name":"Digital image","level":4,"score":0.30820000171661377},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.3034000098705292},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.29019999504089355},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.26170000433921814},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C180462255","wikidata":"https://www.wikidata.org/wiki/Q3559736","display_name":"Standard test image","level":4,"score":0.2567000091075897},{"id":"https://openalex.org/C7797323","wikidata":"https://www.wikidata.org/wiki/Q3798612","display_name":"Pointwise mutual information","level":3,"score":0.25440001487731934}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icumt67815.2025.11268583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icumt67815.2025.11268583","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 17th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320315323","display_name":"Technology Agency of the Czech Republic","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W3198431960","https://openalex.org/W3208515508","https://openalex.org/W4361854853","https://openalex.org/W4380610573","https://openalex.org/W4391487078","https://openalex.org/W4392884893","https://openalex.org/W4392892442","https://openalex.org/W4400042192","https://openalex.org/W4400728372","https://openalex.org/W4400926032","https://openalex.org/W4405384373","https://openalex.org/W4409358596","https://openalex.org/W4411639777"],"related_works":[],"abstract_inverted_index":{"Image":[0,113],"splicing":[1,30,205],"is":[2,108],"a":[3,25,156,192],"prevalent":[4],"form":[5],"of":[6,13,104,126,130,148,159],"digital":[7],"forgery":[8],"that":[9,45,64],"challenges":[10],"the":[11,53,111,182],"reliability":[12],"visual":[14],"content":[15],"across":[16],"forensic,":[17],"legal,":[18],"and":[19,27,49,61,68,79,86,95,145,195],"media":[20],"platforms.":[21],"In":[22],"this":[23],"study,":[24],"novel":[26],"lightweight":[28],"image":[29],"detection":[31],"framework":[32,72,190],"has":[33],"been":[34],"proposed":[35,54,71,189],"grounded":[36],"in":[37],"multi-domain":[38],"information-theoretic":[39],"principles.":[40],"Unlike":[41],"deep":[42,172,201],"learning-based":[43],"methods":[44],"require":[46],"large":[47],"datasets":[48],"high-end":[50],"GPU":[51],"resources,":[52],"approach":[55],"leverages":[56],"handcrafted":[57],"entropy,":[58,94],"mutual":[59,97],"information,":[60],"complexity-based":[62],"features":[63,75],"are":[65,99],"computationally":[66],"efficient":[67],"interpretable.":[69],"The":[70,106,186],"extracts":[73],"20":[74],"from":[76],"spatial,":[77],"cross-channel,":[78],"multi-scale":[80,96],"domains\u2014highlighting":[81],"entropy":[82],"variations,":[83],"statistical":[84],"dependencies,":[85],"information":[87,98],"complexity.":[88],"Notably,":[89],"Kolmogorov":[90],"complexity":[91],"approximation,":[92],"edge":[93],"incorporated":[100],"as":[101,191],"discriminative":[102],"indicators":[103],"tampering.":[105],"model":[107],"evaluated":[109],"on":[110],"Columbia":[112],"Splicing":[114],"Detection":[115],"Dataset":[116],"using":[117],"ten":[118],"classical":[119,164],"machine":[120,165],"learning":[121,166,202],"algorithms.":[122],"A":[123],"maximum":[124],"AUC-ROC":[125],"0.934,":[127],"cross-validation":[128],"performance":[129,170],"$\\mathbf{8":[131,149],"4":[132],".":[133,140,151],"2":[134,153],"9":[135,142],"\\%}":[136,143],"\\boldsymbol{(}":[137],"\\boldsymbol{\\pm}":[138],"\\mathbf{4":[139],"1":[141],"\\boldsymbol{)}$":[144],"test":[146],"accuracy":[147],"5":[150],"3":[152],"\\%}$":[154],"with":[155,163],"strong":[157],"F1-score":[158],"0.8571":[160],"were":[161],"achieved":[162],"classifiers,":[167],"demonstrating":[168],"competitive":[169],"without":[171],"models.":[173],"Feature":[174],"importance":[175],"analysis":[176],"further":[177],"improves":[178],"interpretability":[179],"by":[180],"ranking":[181],"most":[183],"significant":[184],"contributors.":[185],"results":[187],"validate":[188],"reliable,":[193],"resource-efficient,":[194],"explainable":[196],"alternative":[197],"to":[198],"complex":[199],"end-to-end":[200],"pipelines":[203],"for":[204],"detection.":[206]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-12-03T00:00:00"}