A survey on secure data analytics in edge computing

Research output: Contribution to journalReview ArticleScientificpeer-review

Researchers

Research units

  • Xidian University
  • University of Oklahoma

Abstract

Internet of Things (IoT) is gaining increasing popularity. Overwhelming volumes of data are generated by IoT devices. Those data after analytics provide significant information that could greatly benefit IoT applications. Different from traditional applications, IoT applications, such as environmental monitoring, smart navigation, and smart healthcare come with new requirements, such as mobility, real-time response, and location awareness. However, traditional cloud computing paradigm cannot satisfy these demands due to centralized processing and being far away from local devices. Hence, edge computing was introduced to perform data processing and storage in the edge of networks, which is closer to data sources than cloud computing, thus efficient and location-aware. Unfortunately, edge computing brings new security and privacy challenges when applied to data analytics. The literature still lacks a thorough review on the recent advances in secure data analytics in edge computing. In this paper, we first introduce the concept and features of edge computing, and then propose a number of requirements for its secure data analytics by analyzing potential security threats in edge computing. Furthermore, we give a comprehensive review on the pros and cons of the existing works on data analytics in edge computing based on our proposed requirements. Based on our literature survey, we highlight current open issues and propose future research directions.

Details

Original languageEnglish
Article number8634892
Pages (from-to)4946-4967
Number of pages22
JournalIEEE Internet of Things Journal
Volume6
Issue number3
Publication statusPublished - 1 Jun 2019
MoE publication typeA2 Review article in a scientific journal

    Research areas

  • Data analytics, Edge computing, Privacy preservation, Security

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