PAAL: A Framework Based on Authentication, Aggregation, and Local Differential Privacy for Internet of Multimedia Things

Muhammad Usman, Mian Ahmad Jan, Deepak Puthal

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Internet of Multimedia Things (IoMT) applications generate huge volumes of multimedia data that are uploaded to cloud servers for storage and processing. During the uploading process, the IoMT applications face three major challenges, i.e., node management, privacy-preserving, and network protection. In this article, we propose a multilayer framework (PAAL) based on a multilevel edge computing architecture to manage end and edge devices, preserve the privacy of end-devices and data, and protect the underlying network from external attacks. The proposed framework has three layers. In the first layer, the underlying network is partitioned into multiple clusters to manage end-devices and level-one edge devices (LOEDs). In the second layer, the LOEDs apply an efficient aggregation technique to reduce the volumes of generated data and preserve the privacy of end-devices. The privacy of sensitive information in aggregated data is protected through a local differential privacy-based technique. In the last layer, the mobile sinks are registered with a level-two edge device via a handshaking mechanism to protect the underlying network from external threats. Experimental results show that the proposed framework performs better as compared to existing frameworks in terms of managing the nodes, preserving the privacy of end-devices and sensitive information, and protecting the underlying network.

Original languageBritish English
Article number8807201
Pages (from-to)2501-2508
Number of pages8
JournalIEEE Internet of Things Journal
Volume7
Issue number4
DOIs
StatePublished - Apr 2020

Keywords

  • Aggregation
  • Internet of Multimedia Things (IoMT)
  • multilevel edge computing (MLEC)
  • multimedia
  • privacy

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