{"title":"Laser-engraved holograms as entropy source for random number generators","authors":"Christos Tselios , Anastasios Tsakas , Simone Mazzucato , Christina Politi (Tanya) , Panagiotis Rizomiliotis , Dimitris Alexandropoulos","doi":"10.1016/j.mne.2024.100290","DOIUrl":null,"url":null,"abstract":"<div><div>Our study introduces a novel approach to true random number generation (TRNG) using speckle patterns generated by laser-engraved holograms on carbon fiber-reinforced polymer (CFRP) composite substrates. Unlike previous methods, our approach simplifies the process by generating the necessary image dataset from a single microscope image of the engraved hologram. We achieve a high extraction ratio of 76 %, demonstrating the effectiveness of our TRNG. Moreover, our method successfully passes rigorous statistical tests proposed by the National Institute of Standards and Technology (NIST), indicating its suitability for cryptographic and secure system applications. This work offers promising implications for enhancing security in various domains, from secure communication networks to IoT devices.</div></div>","PeriodicalId":37111,"journal":{"name":"Micro and Nano Engineering","volume":"25 ","pages":"Article 100290"},"PeriodicalIF":2.8000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Micro and Nano Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590007224000534","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Our study introduces a novel approach to true random number generation (TRNG) using speckle patterns generated by laser-engraved holograms on carbon fiber-reinforced polymer (CFRP) composite substrates. Unlike previous methods, our approach simplifies the process by generating the necessary image dataset from a single microscope image of the engraved hologram. We achieve a high extraction ratio of 76 %, demonstrating the effectiveness of our TRNG. Moreover, our method successfully passes rigorous statistical tests proposed by the National Institute of Standards and Technology (NIST), indicating its suitability for cryptographic and secure system applications. This work offers promising implications for enhancing security in various domains, from secure communication networks to IoT devices.