I. Tsmots, V. Rabyk, Y. Lukaschuk, V. Teslyuk, Z. Liubun
{"title":"保护密码数据的神经网络技术","authors":"I. Tsmots, V. Rabyk, Y. Lukaschuk, V. Teslyuk, Z. Liubun","doi":"10.1109/ELIT53502.2021.9501094","DOIUrl":null,"url":null,"abstract":"A neural network technology of cryptographic data protection has been developed, and an algorithm for learning the neural networks based on principal components method has been created. This algorithm is developed using the C programming language on a Raspberry Pi microcomputer. Tables of macroparticle products are calculated and an algorithm for the data encryption/decryption based on neural networks is developed. Neuro-like encryption/decryption networks of a given architecture are designed and focused on FPGA implementation. Simulation of the decryption network with different bit input data is performed. We consider an example of how to learn the neural network and encrypt the data with this network.","PeriodicalId":164798,"journal":{"name":"2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT)","volume":"30 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Neural Network Technology for Protecting Cryptographic Data\",\"authors\":\"I. Tsmots, V. Rabyk, Y. Lukaschuk, V. Teslyuk, Z. Liubun\",\"doi\":\"10.1109/ELIT53502.2021.9501094\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A neural network technology of cryptographic data protection has been developed, and an algorithm for learning the neural networks based on principal components method has been created. This algorithm is developed using the C programming language on a Raspberry Pi microcomputer. Tables of macroparticle products are calculated and an algorithm for the data encryption/decryption based on neural networks is developed. Neuro-like encryption/decryption networks of a given architecture are designed and focused on FPGA implementation. Simulation of the decryption network with different bit input data is performed. We consider an example of how to learn the neural network and encrypt the data with this network.\",\"PeriodicalId\":164798,\"journal\":{\"name\":\"2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT)\",\"volume\":\"30 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ELIT53502.2021.9501094\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELIT53502.2021.9501094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neural Network Technology for Protecting Cryptographic Data
A neural network technology of cryptographic data protection has been developed, and an algorithm for learning the neural networks based on principal components method has been created. This algorithm is developed using the C programming language on a Raspberry Pi microcomputer. Tables of macroparticle products are calculated and an algorithm for the data encryption/decryption based on neural networks is developed. Neuro-like encryption/decryption networks of a given architecture are designed and focused on FPGA implementation. Simulation of the decryption network with different bit input data is performed. We consider an example of how to learn the neural network and encrypt the data with this network.