论文标题

大数据共享中的安全和隐私:最先进和研究方向

Security and Privacy in Big Data Sharing: State-of-the-Art and Research Directions

论文作者

Ferradi, Houda, Cao, Jiannong, Jiang, Shan, Cao, Yinfeng, Saxena, Divya

论文摘要

大数据共享(BDS)是指数据所有者共享数据的行为,以便用户可以根据协议找到,访问和使用数据。近年来,由于BDS的广泛应用,例如大数据交易和跨域数据分析,BDS一直是一个新兴的主题。但是,随着多方参与BDS平台,出现了侵犯安全性和隐私问题的问题。有许多解决方案可以增强安全性和在不同的大数据操作(例如,数据操作,数据搜索,数据共享和数据外包)的隐私方面。据我们所知,没有现有的调查特别关注这些安全和隐私解决方案的广泛而系统的发展。在这项研究中,我们对引入的最新解决方案进行了全面调查,以解决BDS中的安全性和隐私问题。为了更好地理解,我们首先介绍了BD的通用模型,并确定安全性和隐私要求。我们根据确定的要求讨论并对BDS的最新安全和隐私解决方案进行分类。最后,根据获得的见解,我们介绍并讨论了新的有前途的研究方向。

Big Data Sharing (BDS) refers to the act of the data owners to share data so that users can find, access and use data according to the agreement. In recent years, BDS has been an emerging topic due to its wide applications, such as big data trading and cross-domain data analytics. However, as the multiple parties are involved in a BDS platform, the issue of security and privacy violation arises. There have been a number of solutions for enhancing security and preserving privacy at different big data operations (e.g., data operation, data searching, data sharing and data outsourcing). To the best of our knowledge, there is no existing survey that has particularly focused on the broad and systematic developments of these security and privacy solutions. In this study, we conduct a comprehensive survey of the state-of-the-art solutions introduced to tackle security and privacy issues in BDS. For a better understanding, we first introduce a general model for BDS and identify the security and privacy requirements. We discuss and classify the state-of-the-art security and privacy solutions for BDS according to the identified requirements. Finally, based on the insights gained, we present and discuss new promising research directions.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源