{"title":"用抗噪声编码将隐藏数据嵌入消息流的方法","authors":"S. V. Belim, S. A. Gorshkov","doi":"10.3103/S0146411624701062","DOIUrl":null,"url":null,"abstract":"<p>This article proposes a model of embedding steganographic data into a message stream using noise-immune coding. The embedded data is disguised as noise in the message transmission channel. Extraction of the embedded message is based on the procedure of detecting corrupted bits using error-correcting codes. The presented model is related to key schemes. The stability of the scheme is based on the impossibility for the analyst to obtain complete information about the embedding. The model is universal and can be implemented in any network protocol using noise-immune codes.</p>","PeriodicalId":46238,"journal":{"name":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","volume":"58 8","pages":"1392 - 1395"},"PeriodicalIF":0.6000,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Method of Embedding Hidden Data into a Message Stream with Noise-Immune Encoding\",\"authors\":\"S. V. Belim, S. A. Gorshkov\",\"doi\":\"10.3103/S0146411624701062\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This article proposes a model of embedding steganographic data into a message stream using noise-immune coding. The embedded data is disguised as noise in the message transmission channel. Extraction of the embedded message is based on the procedure of detecting corrupted bits using error-correcting codes. The presented model is related to key schemes. The stability of the scheme is based on the impossibility for the analyst to obtain complete information about the embedding. The model is universal and can be implemented in any network protocol using noise-immune codes.</p>\",\"PeriodicalId\":46238,\"journal\":{\"name\":\"AUTOMATIC CONTROL AND COMPUTER SCIENCES\",\"volume\":\"58 8\",\"pages\":\"1392 - 1395\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2025-03-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AUTOMATIC CONTROL AND COMPUTER SCIENCES\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.3103/S0146411624701062\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AUTOMATIC CONTROL AND COMPUTER SCIENCES","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.3103/S0146411624701062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Method of Embedding Hidden Data into a Message Stream with Noise-Immune Encoding
This article proposes a model of embedding steganographic data into a message stream using noise-immune coding. The embedded data is disguised as noise in the message transmission channel. Extraction of the embedded message is based on the procedure of detecting corrupted bits using error-correcting codes. The presented model is related to key schemes. The stability of the scheme is based on the impossibility for the analyst to obtain complete information about the embedding. The model is universal and can be implemented in any network protocol using noise-immune codes.
期刊介绍:
Automatic Control and Computer Sciences is a peer reviewed journal that publishes articles on• Control systems, cyber-physical system, real-time systems, robotics, smart sensors, embedded intelligence • Network information technologies, information security, statistical methods of data processing, distributed artificial intelligence, complex systems modeling, knowledge representation, processing and management • Signal and image processing, machine learning, machine perception, computer vision