{"title":"MSMS:具有可区分签名责任的多段多签名模型","authors":"Minh-Tuan Dang","doi":"10.1145/3036290.3036310","DOIUrl":null,"url":null,"abstract":"This paper proposes a concept of multi-section multi-signature model with distinguished signing responsibilities. The model has overcome the limitation of some previous multi-signatures models by allowing every signer to sign and be responsible for one or multiple sections of the signed message. A theoretical analysis against two common types of digital signature attacks has proved the model security assurance level.","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"110 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"MSMS: A Multi-section Multi-signature Model with Distinguished Signing Responsibilities\",\"authors\":\"Minh-Tuan Dang\",\"doi\":\"10.1145/3036290.3036310\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a concept of multi-section multi-signature model with distinguished signing responsibilities. The model has overcome the limitation of some previous multi-signatures models by allowing every signer to sign and be responsible for one or multiple sections of the signed message. A theoretical analysis against two common types of digital signature attacks has proved the model security assurance level.\",\"PeriodicalId\":109559,\"journal\":{\"name\":\"International Conference on Machine Learning and Soft Computing\",\"volume\":\"110 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Machine Learning and Soft Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3036290.3036310\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Machine Learning and Soft Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3036290.3036310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MSMS: A Multi-section Multi-signature Model with Distinguished Signing Responsibilities
This paper proposes a concept of multi-section multi-signature model with distinguished signing responsibilities. The model has overcome the limitation of some previous multi-signatures models by allowing every signer to sign and be responsible for one or multiple sections of the signed message. A theoretical analysis against two common types of digital signature attacks has proved the model security assurance level.