Shuai Cheng , Zehui Tang , Shengke Zeng , Xinchun Cui , Tao Li
{"title":"PFDup:加密多媒体数据的实用模糊重复数据删除","authors":"Shuai Cheng , Zehui Tang , Shengke Zeng , Xinchun Cui , Tao Li","doi":"10.1016/j.jii.2024.100613","DOIUrl":null,"url":null,"abstract":"<div><p>Redundant data wastes cloud storage space, especially the multimedia data which comprises a large number of similar files and accounts for the majority of cloud storage. To protect privacy and eliminate redundancy in the cloud, fuzzy deduplication for encrypted multimedia data is practical and feasible. Unfortunately, existing fuzzy deduplications depend on aided server to be against security threats. In this paper, we propose a Practical Fuzzy Deduplication (PFDup) algorithm for encrypted multimedia data and it is secure against brute-force guessing attacks without additional independent severs. With our secure fuzzy deduplication technology, cloud storage can be significantly optimized by using Perceptual Hash (phash) to eliminate large quantities of identical even the similar multimedia data in a secure manner. In addition, PFDup protocol supports label consistency and a non-interactive Proof of Ownership (PO) in order to prevent the server–client collusion attacks. We conduct a series of experiments on numerous real-world datasets and the simulation results show that our deduplication rate for the similar images is over 91.5%.</p></div>","PeriodicalId":55975,"journal":{"name":"Journal of Industrial Information Integration","volume":"40 ","pages":"Article 100613"},"PeriodicalIF":10.4000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PFDup: Practical Fuzzy Deduplication for Encrypted Multimedia Data\",\"authors\":\"Shuai Cheng , Zehui Tang , Shengke Zeng , Xinchun Cui , Tao Li\",\"doi\":\"10.1016/j.jii.2024.100613\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Redundant data wastes cloud storage space, especially the multimedia data which comprises a large number of similar files and accounts for the majority of cloud storage. To protect privacy and eliminate redundancy in the cloud, fuzzy deduplication for encrypted multimedia data is practical and feasible. Unfortunately, existing fuzzy deduplications depend on aided server to be against security threats. In this paper, we propose a Practical Fuzzy Deduplication (PFDup) algorithm for encrypted multimedia data and it is secure against brute-force guessing attacks without additional independent severs. With our secure fuzzy deduplication technology, cloud storage can be significantly optimized by using Perceptual Hash (phash) to eliminate large quantities of identical even the similar multimedia data in a secure manner. In addition, PFDup protocol supports label consistency and a non-interactive Proof of Ownership (PO) in order to prevent the server–client collusion attacks. We conduct a series of experiments on numerous real-world datasets and the simulation results show that our deduplication rate for the similar images is over 91.5%.</p></div>\",\"PeriodicalId\":55975,\"journal\":{\"name\":\"Journal of Industrial Information Integration\",\"volume\":\"40 \",\"pages\":\"Article 100613\"},\"PeriodicalIF\":10.4000,\"publicationDate\":\"2024-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Industrial Information Integration\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2452414X24000578\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Industrial Information Integration","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2452414X24000578","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
PFDup: Practical Fuzzy Deduplication for Encrypted Multimedia Data
Redundant data wastes cloud storage space, especially the multimedia data which comprises a large number of similar files and accounts for the majority of cloud storage. To protect privacy and eliminate redundancy in the cloud, fuzzy deduplication for encrypted multimedia data is practical and feasible. Unfortunately, existing fuzzy deduplications depend on aided server to be against security threats. In this paper, we propose a Practical Fuzzy Deduplication (PFDup) algorithm for encrypted multimedia data and it is secure against brute-force guessing attacks without additional independent severs. With our secure fuzzy deduplication technology, cloud storage can be significantly optimized by using Perceptual Hash (phash) to eliminate large quantities of identical even the similar multimedia data in a secure manner. In addition, PFDup protocol supports label consistency and a non-interactive Proof of Ownership (PO) in order to prevent the server–client collusion attacks. We conduct a series of experiments on numerous real-world datasets and the simulation results show that our deduplication rate for the similar images is over 91.5%.
期刊介绍:
The Journal of Industrial Information Integration focuses on the industry's transition towards industrial integration and informatization, covering not only hardware and software but also information integration. It serves as a platform for promoting advances in industrial information integration, addressing challenges, issues, and solutions in an interdisciplinary forum for researchers, practitioners, and policy makers.
The Journal of Industrial Information Integration welcomes papers on foundational, technical, and practical aspects of industrial information integration, emphasizing the complex and cross-disciplinary topics that arise in industrial integration. Techniques from mathematical science, computer science, computer engineering, electrical and electronic engineering, manufacturing engineering, and engineering management are crucial in this context.