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Realizing IoT service’s policy privacy over publish/subscribe-based middleware

Overview of attention for article published in SpringerPlus, September 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
26 Mendeley
Title
Realizing IoT service’s policy privacy over publish/subscribe-based middleware
Published in
SpringerPlus, September 2016
DOI 10.1186/s40064-016-3250-x
Pubmed ID
Authors

Li Duan, Yang Zhang, Shiping Chen, Shiyao Wang, Bo Cheng, Junliang Chen

Abstract

The publish/subscribe paradigm makes IoT service collaborations more scalable and flexible, due to the space, time and control decoupling of event producers and consumers. Thus, the paradigm can be used to establish large-scale IoT service communication infrastructures such as Supervisory Control and Data Acquisition systems. However, preserving IoT service's policy privacy is difficult in this paradigm, because a classical publisher has little control of its own event after being published; and a subscriber has to accept all the events from the subscribed event type with no choice. Few existing publish/subscribe middleware have built-in mechanisms to address the above issues. In this paper, we present a novel access control framework, which is capable of preserving IoT service's policy privacy. In particular, we adopt the publish/subscribe paradigm as the IoT service communication infrastructure to facilitate the protection of IoT services policy privacy. The key idea in our policy-privacy solution is using a two-layer cooperating method to match bi-directional privacy control requirements: (a) data layer for protecting IoT events; and (b) application layer for preserving the privacy of service policy. Furthermore, the anonymous-set-based principle is adopted to realize the functionalities of the framework, including policy embedding and policy encoding as well as policy matching. Our security analysis shows that the policy privacy framework is Chosen-Plaintext Attack secure. We extend the open source Apache ActiveMQ broker by building into a policy-based authorization mechanism to enforce the privacy policy. The performance evaluation results indicate that our approach is scalable with reasonable overheads.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 23%
Student > Ph. D. Student 5 19%
Student > Doctoral Student 2 8%
Student > Bachelor 2 8%
Other 2 8%
Other 5 19%
Unknown 4 15%
Readers by discipline Count As %
Computer Science 12 46%
Engineering 4 15%
Decision Sciences 2 8%
Business, Management and Accounting 1 4%
Medicine and Dentistry 1 4%
Other 1 4%
Unknown 5 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 September 2016.
All research outputs
#4,192,991
of 22,890,496 outputs
Outputs from SpringerPlus
#256
of 1,850 outputs
Outputs of similar age
#69,807
of 320,233 outputs
Outputs of similar age from SpringerPlus
#35
of 172 outputs
Altmetric has tracked 22,890,496 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,850 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 320,233 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 172 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.