DEPLEST: A blockchain-based privacy-preserving distributed database toward user behaviors in social networks

Yun Chen, Hui Xie, Kun Lv, Shengjun Wei*, Changzhen Hu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

82 Citations (Scopus)

Abstract

Social networks record a significant amount of user behavior data every day. By analyzing this behavior data, companies or attackers use it for marketing or more questionable purposes. We propose a blockchain-based model to protect the privacy of users’ data in such big data environments. Traditional blockchain methods require too many resources for this task, so we propose a model that secures sensitive user information in a distributed blockchain and passes nonsensitive information through to the primary system in order to manage the blockchain size. Our DEPLEST algorithm performs these synchronization operations to keep local database storage and computational capacity within the limits of individual users’ devices. We also propose a consensus protocol for blockchain ledger maintenance that runs well on typical client systems and prove that this protocol has excellent Byzantine fault tolerance (BFT). Our experimental results show that DEPLEST meets the architectural and performance needs and that our consensus protocol outperforms the existing proof of work (PoW) and proof of stake (PoS) methods in this application.

Original languageEnglish
Pages (from-to)100-117
Number of pages18
JournalInformation Sciences
Volume501
DOIs
Publication statusPublished - Oct 2019

Keywords

  • Big data
  • Blockchain technology
  • Privacy protection
  • Social network

Fingerprint

Dive into the research topics of 'DEPLEST: A blockchain-based privacy-preserving distributed database toward user behaviors in social networks'. Together they form a unique fingerprint.

Cite this