{"title":"关联数据的基于时间戳的完整性证明","authors":"Andrew Sutton, Reza Samavi","doi":"10.1145/3208352.3208353","DOIUrl":null,"url":null,"abstract":"In this paper, we first investigate the state-of-the-art methods of generating cryptographic hashes that can be used as an integrity proof for RDF datasets. We then propose an efficient method of computing integrity proofs for Linked Data that constructs a sorted Merkle tree for growing RDF datasets based on timestamps (as a key) that are semantically extractable from the RDF dataset. We evaluate our method by comparing it to existing methods and investigating its resistance to common security threats.","PeriodicalId":210506,"journal":{"name":"Proceedings of the International Workshop on Semantic Big Data","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Timestamp-based Integrity Proofs for Linked Data\",\"authors\":\"Andrew Sutton, Reza Samavi\",\"doi\":\"10.1145/3208352.3208353\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we first investigate the state-of-the-art methods of generating cryptographic hashes that can be used as an integrity proof for RDF datasets. We then propose an efficient method of computing integrity proofs for Linked Data that constructs a sorted Merkle tree for growing RDF datasets based on timestamps (as a key) that are semantically extractable from the RDF dataset. We evaluate our method by comparing it to existing methods and investigating its resistance to common security threats.\",\"PeriodicalId\":210506,\"journal\":{\"name\":\"Proceedings of the International Workshop on Semantic Big Data\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Workshop on Semantic Big Data\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3208352.3208353\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Workshop on Semantic Big Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3208352.3208353","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we first investigate the state-of-the-art methods of generating cryptographic hashes that can be used as an integrity proof for RDF datasets. We then propose an efficient method of computing integrity proofs for Linked Data that constructs a sorted Merkle tree for growing RDF datasets based on timestamps (as a key) that are semantically extractable from the RDF dataset. We evaluate our method by comparing it to existing methods and investigating its resistance to common security threats.
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