Optimal performance of simple low-cost optical physical unclonable functions resilient to machine learning attacks
In this paper we reconsider Physical Unclonable Functions based on the traditional approach of optical scattering to randomly disordered optical media. These devices have the major advantage of utilization of simple and very low-cost technology and therefore the potential to be installed all over th...
Uloženo v:
| Vydáno v: | Scientific reports Ročník 15; číslo 1; s. 40079 - 15 |
|---|---|
| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
London
Nature Publishing Group
01.11.2025
Nature Portfolio |
| Témata: | |
| ISSN: | 2045-2322 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | In this paper we reconsider Physical Unclonable Functions based on the traditional approach of optical scattering to randomly disordered optical media. These devices have the major advantage of utilization of simple and very low-cost technology and therefore the potential to be installed all over the network providing critical cybersecurity operations such authentication, real time cryptographic key generation and generation of trues random sequences. To comply with the requirements of the aforementioned operations, critical issues must be resolved. We propose and implement algorithms for the generation of an almost unlimited number of uncorrelated optical challenges. We show experimentally that the uncorrelated challenges result in optical speckle which, after the proper numerical processing, produce true random sequences. Moreover, we determine the optimal illumination conditions to achieve the best possible performance in terms of robustness and unpredictability. Last but not least, we studied the resilience of the PUF against machine learning attacks. We conclude experimentally that under certain illuminating conditions and using the aforementioned uncorrelated challenges, the network cannot predict the responses even after being trained with a very large number of challenge responses (24,000 pairs). |
|---|---|
| AbstractList | Abstract In this paper we reconsider Physical Unclonable Functions based on the traditional approach of optical scattering to randomly disordered optical media. These devices have the major advantage of utilization of simple and very low-cost technology and therefore the potential to be installed all over the network providing critical cybersecurity operations such authentication, real time cryptographic key generation and generation of trues random sequences. To comply with the requirements of the aforementioned operations, critical issues must be resolved. We propose and implement algorithms for the generation of an almost unlimited number of uncorrelated optical challenges. We show experimentally that the uncorrelated challenges result in optical speckle which, after the proper numerical processing, produce true random sequences. Moreover, we determine the optimal illumination conditions to achieve the best possible performance in terms of robustness and unpredictability. Last but not least, we studied the resilience of the PUF against machine learning attacks. We conclude experimentally that under certain illuminating conditions and using the aforementioned uncorrelated challenges, the network cannot predict the responses even after being trained with a very large number of challenge responses (24,000 pairs). In this paper we reconsider Physical Unclonable Functions based on the traditional approach of optical scattering to randomly disordered optical media. These devices have the major advantage of utilization of simple and very low-cost technology and therefore the potential to be installed all over the network providing critical cybersecurity operations such authentication, real time cryptographic key generation and generation of trues random sequences. To comply with the requirements of the aforementioned operations, critical issues must be resolved. We propose and implement algorithms for the generation of an almost unlimited number of uncorrelated optical challenges. We show experimentally that the uncorrelated challenges result in optical speckle which, after the proper numerical processing, produce true random sequences. Moreover, we determine the optimal illumination conditions to achieve the best possible performance in terms of robustness and unpredictability. Last but not least, we studied the resilience of the PUF against machine learning attacks. We conclude experimentally that under certain illuminating conditions and using the aforementioned uncorrelated challenges, the network cannot predict the responses even after being trained with a very large number of challenge responses (24,000 pairs). |
| Author | Akriotou, Marialena Veinidis, Christos Syvridis, Dimitris Bartsokas, Theodoros |
| Author_xml | – sequence: 1 givenname: Marialena surname: Akriotou fullname: Akriotou, Marialena – sequence: 2 givenname: Theodoros surname: Bartsokas fullname: Bartsokas, Theodoros – sequence: 3 givenname: Christos surname: Veinidis fullname: Veinidis, Christos – sequence: 4 givenname: Dimitris surname: Syvridis fullname: Syvridis, Dimitris |
| BookMark | eNotkE9PAyEQxYnRxFr7BTyReF5lgd2Fo2n806RJL3reDCy0W7ewAo1pP720dS7zZvLyy7y5Q9fOO4PQQ0meSsLEc-RlJUVBaFVQJjgpjldoQgk_jZTeolmMW5KropKXcoLCakz9DgY8mmB92IHTBnuLY78bB4MH_1toHxP22aZPts0hnsXe6cE7UNlks069dxEHE_uhNy7h5PEO9KZ3mWEguN6tMaQE-jveoxsLQzSz_z5FX2-vn_OPYrl6X8xflkVXMnEslCSyA6F1Q41suFVWqUpUAkArKkkN2ioBtGO6qcuOUt5osJ2o6loQ2VjFpmhx4XYetu0YcsxwaD307Xnhw7qFkFMNprXWMinrRnBpuYFaaMU5oUxCaU1leGY9Xlhj8D97E1O79fvg8vktow0V-feUsj_GMHoB |
| ContentType | Journal Article |
| Copyright | The Author(s) 2025. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: The Author(s) 2025. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| DBID | 3V. 7X7 7XB 88A 88E 88I 8FE 8FH 8FI 8FJ 8FK ABUWG AEUYN AFKRA AZQEC BBNVY BENPR BHPHI CCPQU DWQXO FYUFA GHDGH GNUQQ HCIFZ K9. LK8 M0S M1P M2P M7P PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS Q9U DOA |
| DOI | 10.1038/s41598-025-23840-z |
| DatabaseName | ProQuest Central (Corporate) Health & Medical Collection ProQuest Central (purchase pre-March 2016) Biology Database (Alumni Edition) Medical Database (Alumni Edition) Science Database (Alumni Edition) ProQuest SciTech Collection ProQuest Natural Science Collection ProQuest Hospital Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest One Sustainability ProQuest Central UK/Ireland ProQuest Central Essentials - QC Biological Science Collection ProQuest Central Natural Science Collection ProQuest One Community College ProQuest Central Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) Biological Sciences Health & Medical Collection (Alumni) Medical Database Science Database Biological Science Database ProQuest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China ProQuest Central Basic DOAJ Directory of Open Access Journals |
| DatabaseTitle | Publicly Available Content Database ProQuest Central Student ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Central China ProQuest Biology Journals (Alumni Edition) ProQuest Central ProQuest One Applied & Life Sciences ProQuest One Sustainability ProQuest Health & Medical Research Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest Science Journals (Alumni Edition) ProQuest Biological Science Collection ProQuest Central Basic ProQuest Science Journals ProQuest One Academic Eastern Edition ProQuest Hospital Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) |
| DatabaseTitleList | Publicly Available Content Database |
| Database_xml | – sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: PIMPY name: Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Biology |
| EISSN | 2045-2322 |
| EndPage | 15 |
| ExternalDocumentID | oai_doaj_org_article_fff39967849f4ea68cb440239a1fe5e4 |
| GroupedDBID | 0R~ 3V. 4.4 53G 5VS 7X7 7XB 88A 88E 88I 8FE 8FH 8FI 8FJ 8FK AAFWJ AAJSJ AAKDD AASML ABDBF ABUWG ACGFS ACUHS ADBBV ADRAZ AENEX AEUYN AFFHD AFKRA AFPKN ALMA_UNASSIGNED_HOLDINGS AOIJS AZQEC BAWUL BBNVY BCNDV BENPR BHPHI BPHCQ BVXVI C6C CCPQU DIK DWQXO EBD EBLON EBS ESX FYUFA GNUQQ GROUPED_DOAJ GX1 HCIFZ HH5 HMCUK HYE K9. KQ8 LK8 M1P M2P M48 M7P M~E NAO OK1 PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS PROAC PSQYO Q9U RNT RNTTT RPM SNYQT UKHRP |
| ID | FETCH-LOGICAL-d138z-b909da8cc72e974fbfbb5858aacb2906acfb8a2d3c761d2247cafd85668097fb3 |
| IEDL.DBID | M7P |
| IngestDate | Mon Nov 24 19:20:39 EST 2025 Wed Nov 19 04:00:34 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-d138z-b909da8cc72e974fbfbb5858aacb2906acfb8a2d3c761d2247cafd85668097fb3 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| OpenAccessLink | https://www.proquest.com/docview/3272810322?pq-origsite=%requestingapplication% |
| PQID | 3272810322 |
| PQPubID | 2041939 |
| PageCount | 15 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_fff39967849f4ea68cb440239a1fe5e4 proquest_journals_3272810322 |
| PublicationCentury | 2000 |
| PublicationDate | 2025-11-01 |
| PublicationDateYYYYMMDD | 2025-11-01 |
| PublicationDate_xml | – month: 11 year: 2025 text: 2025-11-01 day: 01 |
| PublicationDecade | 2020 |
| PublicationPlace | London |
| PublicationPlace_xml | – name: London |
| PublicationTitle | Scientific reports |
| PublicationYear | 2025 |
| Publisher | Nature Publishing Group Nature Portfolio |
| Publisher_xml | – name: Nature Publishing Group – name: Nature Portfolio |
| SSID | ssj0000529419 |
| Score | 2.4628606 |
| Snippet | In this paper we reconsider Physical Unclonable Functions based on the traditional approach of optical scattering to randomly disordered optical media. These... Abstract In this paper we reconsider Physical Unclonable Functions based on the traditional approach of optical scattering to randomly disordered optical... |
| SourceID | doaj proquest |
| SourceType | Open Website Aggregation Database |
| StartPage | 40079 |
| SubjectTerms | Algorithms Lasers Learning algorithms Machine learning |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LS8QwEA6yKHgRn_hYJQevYds0bZKjiosHWT0o7K3k0cDC7rZsq-L-eidpxAUPXryW0pSZTL6ZMN83CF1L4TJtOSUs1xUUKFYSlTBFbOFoqgtmUx10Zh_5ZCKmU_m8MerL94T18sC94UbOOcBQOFKZdKxShTCaMc_IVKmr8ioogULWs1FM9areVLJURpZMkolRC0jl2WQ0J4BSLCHrqNL_6xAOyDLeR3sxJcQ3_a8coK1qeYh2-iGRn0do9QRRvYAXmp8ef1w73M68sC-e1x_E1G2H6yZcS-MmWh4DYs3rQI3CHr3CBsNQXc_mngOJuxovQiclfCPej2DVdZ5zf4xex_cvdw8kTkogNs3EmmiZSKuEMZxWUCA47bSGOkAoZbTXc1fGaaGozQwvUguozY1yVkAqJxLJnc5O0GBZL6tThI0WImVUi1Q5ZjI_jJhaqrnOpYXY5Wfo1lutbHoxjNLLU4cH4LQyOq38y2lnaPht8zLGTFtmlFPh9f3o-X-scYF2qfd24A0O0aBbvVWXaNu8d7N2dRW2yxfp_chd priority: 102 providerName: Directory of Open Access Journals |
| Title | Optimal performance of simple low-cost optical physical unclonable functions resilient to machine learning attacks |
| URI | https://www.proquest.com/docview/3272810322 https://doaj.org/article/fff39967849f4ea68cb440239a1fe5e4 |
| Volume | 15 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals databaseCode: DOA dateStart: 20110101 customDbUrl: isFulltext: true eissn: 2045-2322 dateEnd: 99991231 titleUrlDefault: https://www.doaj.org/ omitProxy: false ssIdentifier: ssj0000529419 providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources databaseCode: M~E dateStart: 20110101 customDbUrl: isFulltext: true eissn: 2045-2322 dateEnd: 99991231 titleUrlDefault: https://road.issn.org omitProxy: false ssIdentifier: ssj0000529419 providerName: ISSN International Centre – providerCode: PRVPQU databaseName: Biological Science Database databaseCode: M7P dateStart: 20110101 customDbUrl: isFulltext: true eissn: 2045-2322 dateEnd: 99991231 titleUrlDefault: http://search.proquest.com/biologicalscijournals omitProxy: false ssIdentifier: ssj0000529419 providerName: ProQuest – providerCode: PRVPQU databaseName: Health & Medical Collection databaseCode: 7X7 dateStart: 20110101 customDbUrl: isFulltext: true eissn: 2045-2322 dateEnd: 99991231 titleUrlDefault: https://search.proquest.com/healthcomplete omitProxy: false ssIdentifier: ssj0000529419 providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central databaseCode: BENPR dateStart: 20110101 customDbUrl: isFulltext: true eissn: 2045-2322 dateEnd: 99991231 titleUrlDefault: https://www.proquest.com/central omitProxy: false ssIdentifier: ssj0000529419 providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database databaseCode: PIMPY dateStart: 20110101 customDbUrl: isFulltext: true eissn: 2045-2322 dateEnd: 99991231 titleUrlDefault: http://search.proquest.com/publiccontent omitProxy: false ssIdentifier: ssj0000529419 providerName: ProQuest – providerCode: PRVPQU databaseName: Science Database databaseCode: M2P dateStart: 20110101 customDbUrl: isFulltext: true eissn: 2045-2322 dateEnd: 99991231 titleUrlDefault: https://search.proquest.com/sciencejournals omitProxy: false ssIdentifier: ssj0000529419 providerName: ProQuest |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1NT9wwEB0VaKVeSkuLoNCVD71aJI53bZ9QQaBWKtuoAmk5Rf6Iq5WWddikreDXd-w1cKjUSy85xFEUZcbzPGO_NwAflfSVcYJRPjYtJihOUV1wTd3Es9JMuCtN0pn9KqZTOZupOhfc-nys8iEmpkDtgo018qOKCSaj-hs77m5p7BoVd1dzC40N2IoqCVU6ulc_1ljiLhYvVebKFJU86hGvIqeMjSliFS_ofdbq_ysUJ3w53_7fL3sNr_LKknxau8IbeNYud-DFutfk3VtYfcPgcIMPdE9UARI86edRH5gswm9qQz-Q0KXqNumyAQkC3yIkhhWJIJj8lGCSPl9EKiUZArlJBzLxHbnMQvQwROr-O7g6P7s8_UxzwwXqykreU6MK5bS0VrAW8wxvvDGYTkitrYmy8Np6IzVzlRWT0iH4C6u9k7gilIUS3lS7sLkMy3YPiDVSlpwZWWrPbRV7GjPHjDBj5TAEiH04ib-96daaGk1UuU43wupHkydN473H9RPCKVeet3oireE8snF16dtxy_fh8MEiTZ56ffNkjvf_Hj6Alyw6QiIWHsLmsPrZfoDn9tcw71cj2BAzMYKtk7Np_X2UUnW8XrB6lHwMR-ovF_X1H2Lu3Bw |
| linkProvider | ProQuest |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Nb9QwEB2VLQgu5VsUCvgAR6uJ493YB1RRoOqq22UPRSqn4E-00nYdkkDV_ih-Y8dZLz0gceuBaxJZSvzyZjz2ewPwRgpfaFsyyofa4QLFSqoyrqgdeZbrEbe57n1mJ-V0Kk5P5WwDfq-1MPFY5ZoTe6K2wcQa-W7BSiai-xvbq3_Q2DUq7q6uW2isYHHkLs5xyda-G3_E-X3L2MGnkw-HNHUVoDYvxCXVMpNWCWNK5jCZ9tprjTmzUMro6H2ujNdCMVsYXOFbjHClUd4KTHtEJkuvCxz3FmxyBLsYwOZsfDz7-qeqE_fNeC6TOicrxG6LETKq2NiQYnTkGb1M3QH-Iv8-oh3c_9--xQPYSrkzeb8C-0PYcMtHcGfVTfPiMTSfkf7O8IH6WgxBgiftPDogk0U4pya0HQl1X78ndYIowdC-CL2GjMQw3_-JpHHtfBHFoqQL5Kw_copjpEISUV0XzQmewJcbeeGnMFiGpXsGxGghcs60yJXnpohdm5llutRDaZHkym3Yj9Nc1SvXkCr6ePcXQvO9SrRQee8xQ8SEgUvPnRoJozmPemOVezd0fBt21gioErm01fX0P__37ddw9_DkeFJNxtOjF3CPRRD2MsodGHTNT_cSbptf3bxtXiUcE_h203C5ArG7N0k |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB6V8hAX3qiFAj7A0drE8a6dA0JAWVG1WvYAUm_Bz2ql7TokKVX70_h1jL1eekDi1gPXJLLk-PPMeDzfNwCva-krbQWjfKwdHlBsTVXBFbUTz0o94bbUSWf2SMxm8vi4nm_Brw0XJpZVbmxiMtQ2mJgjH1VMMBnV39jI57KI-f70XfuDxg5S8aZ1005jDZFDd3GOx7f-7cE-rvUbxqafvn78THOHAWrLSl5SXRe1VdIYwRwG1l57rTF-lkoZHXXQlfFaKmYrg6d9i95OGOWtxBBIFrXwusJxb8BNEUXLU9ng_E9-J96g8bLOPJ2ikqMefWXks7ExRT_JC3qZ-wT85QaSb5ve_5__ygO4lyNq8n69BR7Clls9gtvrHpsXj6H7gkbxFD9orygSJHjSL6IuMlmGc2pCP5DQpqw-aTNwCTr8ZUjMMhKdf9qfpHP9YhkppGQI5DQVouIYOb1E1DBEyYIn8O1aJvwUtldh5XaAGC1lyZmWpfLcVLGXM7NMCz2uLZo-sQsf4pI37VpLpInq3ulB6E6abCwa7z3GjRhG8NpzpybSaM4jC1mV3o0d34W9DRqabHL65goKz_79-hXcQYw0Rwezw-dwl0U8Jm7lHmwP3Zl7AbfMz2HRdy8ToAl8v26s_Aag_j6I |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Optimal+performance+of+simple+low-cost+optical+physical+unclonable+functions+resilient+to+machine+learning+attacks&rft.jtitle=Scientific+reports&rft.au=Akriotou%2C+Marialena&rft.au=Bartsokas%2C+Theodoros&rft.au=Veinidis%2C+Christos&rft.au=Syvridis%2C+Dimitris&rft.date=2025-11-01&rft.pub=Nature+Publishing+Group&rft.eissn=2045-2322&rft.volume=15&rft.issue=1&rft.spage=40079&rft_id=info:doi/10.1038%2Fs41598-025-23840-z&rft.externalDBID=HAS_PDF_LINK |