research-article

Crowd-enabled Processing of Trustworthy, Privacy-Enhanced and Personalised Location Based Services with Quality Guarantee

Authors:

Tanzima Hashem,

Mehnaz Tabassum MahinAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 2, Issue 4

Article No.: 167, Pages 1 - 25

https://doi.org/10.1145/3287045

Published: 27 December 2018 Publication History

Abstract

We propose a novel approach for enabling trustworthy, privacy-enhanced and personalised location based services (LBSs) that find nearby points of interests (POIs) such as restaurants, ATM booths, and hospitals in a crowdsourced manner. In our crowdsourced approach, a user forms a group from the crowd and processes the LBS using the POI knowledge of the group members without involving an external service provider. We use personalised rating in addition to the distance of a POI for finding the answers of the location based queries. The personalised rating of a POI is computed using individual POI ratings given by the group members and the query requestor's trust and similarity scores for the group members. The major challenges for the crowdsourced data are incompleteness and inaccuracy, which may result in lower quality answer for the LBS. In this paper, we first present techniques to select knowledgeable group members for processing LBSs and thereby increase the accuracy and the confidence level of the query answers. We then develop efficient algorithms to process LBSs in real time and enhance privacy by reducing the number of the group members' POIs shared with the query requestor. Finally, we run extensive experiments using real datasets to show the efficiency and effectiveness of our approach.

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Cited By

Zhang SLuo ZYang LTeng FLi T(2024)A survey of route recommendations: Methods, applications, and opportunitiesInformation Fusion10.1016/j.inffus.2024.102413(102413)Online publication date: Apr-2024
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Islam FHashem TShahriyar R(2023)A Crowd-Enabled Approach for Privacy-Enhanced and Personalized Safe Route Planning for Fixed or Flexible DestinationsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.323470335:11(10922-10936)Online publication date: 1-Nov-2023
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Renukadevi MAnita EGeetha D(2023)Enhanced Horse Optimization Algorithm Based Intelligent Query Optimization in Crowdsourcing SystemsAdvanced Network Technologies and Intelligent Computing10.1007/978-3-031-28180-8_16(234-249)Online publication date: 22-Mar-2023
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Index Terms

Crowd-enabled Processing of Trustworthy, Privacy-Enhanced and Personalised Location Based Services with Quality Guarantee
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing theory, concepts and paradigms
      1. Ubiquitous computing
2. Information systems
  1. Information systems applications
    1. Spatial-temporal systems
      1. Location based services

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 2, Issue 4

December 2018

1169 pages

EISSN:2474-9567

DOI:10.1145/3301777

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Copyright © 2018 ACM.

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Publication History

Published: 27 December 2018

Accepted: 01 October 2018

Revised: 01 April 2018

Received: 01 February 2018

Published in IMWUT Volume 2, Issue 4

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Cited By

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https://doi.org/10.1016/j.inffus.2024.102413
Islam FHashem TShahriyar R(2023)A Crowd-Enabled Approach for Privacy-Enhanced and Personalized Safe Route Planning for Fixed or Flexible DestinationsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.323470335:11(10922-10936)Online publication date: 1-Nov-2023
https://doi.org/10.1109/TKDE.2023.3234703
Renukadevi MAnita EGeetha D(2023)Enhanced Horse Optimization Algorithm Based Intelligent Query Optimization in Crowdsourcing SystemsAdvanced Network Technologies and Intelligent Computing10.1007/978-3-031-28180-8_16(234-249)Online publication date: 22-Mar-2023
https://doi.org/10.1007/978-3-031-28180-8_16
Belal YBellet AMokhtar SNitu V(2022)PEPPERProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35503026:3(1-27)Online publication date: 7-Sep-2022
https://dl.acm.org/doi/10.1145/3550302
Bagave PWestberg MDobbe RJanssen MDing A(2022)Accountable AI for Healthcare IoT Systems2022 IEEE 4th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA)10.1109/TPS-ISA56441.2022.00013(20-28)Online publication date: Dec-2022
https://doi.org/10.1109/TPS-ISA56441.2022.00013
Islam FHashem TShahriyar R(2021)A Privacy-Enhanced and Personalized Safe Route Planner with Crowdsourced Data and Computation2021 IEEE 37th International Conference on Data Engineering (ICDE)10.1109/ICDE51399.2021.00027(229-240)Online publication date: Apr-2021
https://doi.org/10.1109/ICDE51399.2021.00027
Bhaskar NKumar P(2020)Optimal processing of nearest-neighbor user queries in crowdsourcing based on the whale optimization algorithmSoft Computing10.1007/s00500-020-04722-0Online publication date: 11-Feb-2020
https://doi.org/10.1007/s00500-020-04722-0
Mahin MHashem T(2019)Activity-aware Ridesharing Group Trip Planning Queries for Flexible POIsACM Transactions on Spatial Algorithms and Systems10.1145/33418185:3(1-41)Online publication date: 4-Sep-2019
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