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Anonymous and Efficient Certificateless Multirecipient Signcryption Scheme for Ecological Data Sharing
Journal of Sensors ( IF 1.9 ) Pub Date : 2020-08-19 , DOI: 10.1155/2020/5132861
Pengfei Su 1 , Yong Xie 1 , Ping Liu 1
Affiliation  

Air pollution, water pollution, soil erosion, land desertification, and other environmental issues are becoming more and more serious. And ecological security has become a key issue for the sustainable development of the world, so research on ecology has received more and more attention. At present, ecological data is collected and stored separately by various departments or agencies. In order to conduct better research, various institutions or individuals begin to share their own data. However, data sharing between different organizations is affected by many factors, especially data security issues. At the moment, there is no scheme that has been commonly recognized to solve the problem of ecological data sharing. To provide a secure data sharing way for ecological research, a certificateless multireceiver signcryption scheme is proposed. In this paper, the proposed scheme can solve the key escrow problem, and it can improve efficiency on the basis of ensuring security by adopting elliptic curve cryptography (ECC). A rigorous security analysis proves that the scheme can resist various security attacks and ensure privacy protection based on a random oracle model. Performance analysis also shows that this scheme has the advantage of computational overhead compared to the same type of scheme. Therefore, the scheme is very suitable for the safe sharing of ecological data.

中文翻译:

生态数据共享的匿名高效无证书多收件人签密方案

空气污染,水污染,水土流失,土地荒漠化和其他环境问题正变得越来越严重。生态安全已经成为世界可持续发展的关键问题,因此生态学研究受到越来越多的关注。目前,生态数据已由各个部门或机构分别收集​​和存储。为了进行更好的研究,各种机构或个人开始共享自己的数据。但是,不同组织之间的数据共享受到许多因素的影响,尤其是数据安全性问题。目前,还没有公认的解决生态数据共享问题的方案。为了给生态研究提供一种安全的数据共享方式,提出了一种无证书的多接收者签密方案。本文提出的方案可以解决密钥托管问题,并且在采用椭圆曲线密码学(ECC)确保安全性的基础上可以提高效率。经过严格的安全分析,证明该方案能够抵抗各种安全攻击,并基于随机预言模型来确保隐私保护。性能分析还表明,与相同类型的方案相比,该方案具有计算开销的优势。因此,该方案非常适合安全共享生态数据。经过严格的安全分析,证明该方案能够抵抗各种安全攻击,并基于随机预言模型来确保隐私保护。性能分析还表明,与相同类型的方案相比,该方案具有计算开销的优势。因此,该方案非常适合生态数据的安全共享。严格的安全性分析证明,该方案能够抵抗各种安全攻击,并基于随机预言模型来确保隐私保护。性能分析还表明,与相同类型的方案相比,该方案具有计算开销的优势。因此,该方案非常适合安全共享生态数据。
更新日期:2020-08-19
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