{"id":"https://openalex.org/W7138276790","doi":"https://doi.org/10.48550/arxiv.2603.13525","title":"Correlation Bounds and Markov Analysis for Ring-Oscillator TRNGs: A Joint Validation Framework","display_name":"Correlation Bounds and Markov Analysis for Ring-Oscillator TRNGs: A Joint Validation Framework","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7138276790","doi":"https://doi.org/10.48550/arxiv.2603.13525"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.13525","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13525","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.13525","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129657273","display_name":"Miguel Alcocer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alcocer, Miguel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129673538","display_name":"Ana Isabel G\u00f3mez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G\u00f3mez, Ana Isabel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129740894","display_name":"Domingo Gomez-Perez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gomez-Perez, Domingo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11017","display_name":"Chaos-based Image/Signal Encryption","score":0.8531000018119812,"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/T11017","display_name":"Chaos-based Image/Signal Encryption","score":0.8531000018119812,"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/T10951","display_name":"Cryptographic Implementations and Security","score":0.052299998700618744,"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/T11693","display_name":"Cryptography and Residue Arithmetic","score":0.027899999171495438,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/markov-chain","display_name":"Markov chain","score":0.6815000176429749},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5889000296592712},{"id":"https://openalex.org/keywords/random-number-generation","display_name":"Random number generation","score":0.5479000210762024},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5149000287055969},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.508400022983551},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4851999878883362},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.4586000144481659},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.4162999987602234},{"id":"https://openalex.org/keywords/joint-entropy","display_name":"Joint entropy","score":0.4146000146865845},{"id":"https://openalex.org/keywords/distance-correlation","display_name":"Distance correlation","score":0.41019999980926514}],"concepts":[{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6815000176429749},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5889000296592712},{"id":"https://openalex.org/C201866948","wikidata":"https://www.wikidata.org/wiki/Q228206","display_name":"Random number generation","level":2,"score":0.5479000210762024},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5149000287055969},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.508400022983551},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.49720001220703125},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4851999878883362},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.4586000144481659},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43689998984336853},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4185999929904938},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.4162999987602234},{"id":"https://openalex.org/C106752470","wikidata":"https://www.wikidata.org/wiki/Q1364826","display_name":"Joint entropy","level":3,"score":0.4146000146865845},{"id":"https://openalex.org/C121694360","wikidata":"https://www.wikidata.org/wiki/Q5282862","display_name":"Distance correlation","level":3,"score":0.41019999980926514},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.40779998898506165},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.3905999958515167},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.3885999917984009},{"id":"https://openalex.org/C54907487","wikidata":"https://www.wikidata.org/wiki/Q7915688","display_name":"Variable-order Markov model","level":4,"score":0.38659998774528503},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3723999857902527},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.3716999888420105},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.3671000003814697},{"id":"https://openalex.org/C8272713","wikidata":"https://www.wikidata.org/wiki/Q176737","display_name":"Stochastic process","level":2,"score":0.35019999742507935},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.34700000286102295},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.321399986743927},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3118000030517578},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2915000021457672},{"id":"https://openalex.org/C196956702","wikidata":"https://www.wikidata.org/wiki/Q6795829","display_name":"Maximum-entropy Markov model","level":5,"score":0.28600001335144043},{"id":"https://openalex.org/C52622258","wikidata":"https://www.wikidata.org/wiki/Q131222","display_name":"Information theory","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C2986587452","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical analysis","level":2,"score":0.27810001373291016},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.26840001344680786},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.2572000026702881},{"id":"https://openalex.org/C104111718","wikidata":"https://www.wikidata.org/wiki/Q2153973","display_name":"Ring oscillator","level":3,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.13525","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13525","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.13525","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13525","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"True":[0],"Random":[1],"Number":[2],"Generators":[3],"(TRNGs)":[4],"based":[5],"on":[6,28],"ring":[7],"oscillators":[8],"require":[9],"rigorous":[10],"statistical":[11],"validation":[12,52],"to":[13,57],"ensure":[14],"cryptographic":[15],"quality.":[16],"While":[17],"the":[18,49,65,69,117,136],"Mauduit-S\u00e1rk\u00f6zy":[19],"$k$-th":[20],"order":[21],"correlation":[22,60,110],"measure":[23],"$C_k$":[24],"provides":[25],"theoretical":[26],"bounds":[27],"pseudorandomness,":[29],"and":[30,73,94,114],"Maurer's":[31,55],"Universal":[32],"Statistical":[33],"Test":[34],"offers":[35],"empirical":[36],"entropy":[37],"assessment,":[38],"no":[39],"prior":[40],"work":[41],"has":[42],"correlated":[43],"these":[44,133],"metrics.":[45],"This":[46],"paper":[47],"presents":[48],"first":[50],"joint":[51],"framework":[53],"linking":[54],"Z-score":[56,113],"off-peak":[58],"2nd-order":[59],"$C_2$.":[61,115],"We":[62],"also":[63],"derive":[64],"mathematical":[66],"relationship":[67],"between":[68,111],"previous":[70],"two":[71],"measures":[72],"high-order":[74],"Markov":[75],"chain":[76],"transition":[77],"probabilities":[78],"in":[79],"counter-based":[80],"TRNGs":[81],"over":[82],"oscillator":[83],"sampling":[84],"architectures.":[85],"Our":[86],"results":[87,105,118],"are":[88],"validated":[89],"computationally":[90],"using":[91],"OpenTRNG":[92],"implementations,":[93],"demonstrate":[95],"that":[96],"practical":[97],"implementations":[98],"achieve":[99,128],"Schmidt's":[100],"improved":[101],"bound.":[102],"The":[103],"initial":[104],"suggest":[106,119],"a":[107,120,130],"strong":[108],"positive":[109],"Maurer":[112],"Therefore,":[116],"unified":[121],"metric":[122],"for":[123],"TRNG":[124],"quality-assessment":[125],"can":[126],"be":[127],"as":[129],"combination":[131],"of":[132,138],"metrics,":[134],"simplifying":[135],"study":[137],"new":[139],"designs.":[140]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-18T00:00:00"}