Relevant bibliographies by topics / Location- Privacy control

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  1. Journal articles

Academic literature on the topic 'Location- Privacy control'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Location- Privacy control"

1

Yunxiang, Zhang, and Wang Bin. "Stability Control of Position Flow Fuzzy Estimation in Swarm Intelligence Aware Privacy Protection." Wireless Communications and Mobile Computing 2023 (January 30, 2023): 1–8. http://dx.doi.org/10.1155/2023/4792248.

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The group intelligence perception privacy protection model is a method to achieve the balance between user privacy and service requests through the cooperation between users using location services and has a good perception effect. In order to better protect the location privacy of network users and improve the stability control effect of fuzzy estimation of location flow, this paper designs a stability control method of fuzzy estimation of location flow in group intelligent perception privacy protection. This method uses the group intelligence aware privacy protection model to obtain the user
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2

Peng, Tao, Qin Liu, and Guojun Wang. "Enhanced Location Privacy Preserving Scheme in Location-Based Services." IEEE Systems Journal 11, no. 1 (2017): 219–30. http://dx.doi.org/10.1109/jsyst.2014.2354235.

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3

Zhu, Liang, Xiaowei Liu, Zhiyong Jing, Liping Yu, Zengyu Cai, and Jianwei Zhang. "Knowledge-Driven Location Privacy Preserving Scheme for Location-Based Social Networks." Electronics 12, no. 1 (2022): 70. http://dx.doi.org/10.3390/electronics12010070.

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Location privacy-preserving methods for location-based services in mobile communication networks have received great attention. Traditional location privacy-preserving methods mostly focus on the researches of location data analysis in geographical space. However, there is a lack of studies on location privacy preservation by considering the personalized features of users. In this paper, we present a Knowledge-Driven Location Privacy Preserving (KD-LPP) scheme, in order to mine user preferences and provide customized location privacy protection for users. Firstly, the UBPG algorithm is propose
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4

Yang, Guangcan, Shoushan Luo, Yang Xin, et al. "A Search Efficient Privacy-Preserving Location-Sharing Scheme in Mobile Online Social Networks." Applied Sciences 10, no. 23 (2020): 8402. http://dx.doi.org/10.3390/app10238402.

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With the advent of intelligent handheld devices, location sharing becomes one of the most popular services in mobile online social networks (mOSNs). In location-sharing services, users can enjoy a better social experience by updating their real-time location information. However, the leakage of private information may hinder the further development of location-sharing services. Although many solutions have been proposed to protect users’ privacy, the privacy-utility trade-offs must be considered. Therefore, we propose a new scheme called search efficient privacy-preserving location-sharing (SE
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5

Perusco, Laura, and Katina Michael. "Control, trust, privacy, and security: evaluating location-based services." IEEE Technology and Society Magazine 26, no. 1 (2007): 4–16. http://dx.doi.org/10.1109/mtas.2007.335564.

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6

Luceri, Luca, Davide Andreoletti, Massimo Tornatore, Torsten Braun, and Silvia Giordano. "Measurement and control of geo-location privacy on Twitter." Online Social Networks and Media 17 (May 2020): 100078. http://dx.doi.org/10.1016/j.osnem.2020.100078.

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7

Chu, Xiang, Jun Liu, Daqing Gong, and Rui Wang. "Preserving Location Privacy in Spatial Crowdsourcing Under Quality Control." IEEE Access 7 (2019): 155851–59. http://dx.doi.org/10.1109/access.2019.2949409.

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8

Qi He, Dapeng Wu, and P. Khosla. "The quest for personal control over mobile location privacy." IEEE Communications Magazine 42, no. 5 (2004): 130–36. http://dx.doi.org/10.1109/mcom.2004.1299356.

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9

Góes, Rômulo Meira, Blake C. Rawlings, Nicholas Recker, Gregory Willett, and Stéphane Lafortune. "Demonstration of Indoor Location Privacy Enforcement using Obfuscation." IFAC-PapersOnLine 51, no. 7 (2018): 145–51. http://dx.doi.org/10.1016/j.ifacol.2018.06.293.

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10

Xu, Chuan, Li Luo, Yingyi Ding, Guofeng Zhao, and Shui Yu. "Personalized Location Privacy Protection for Location-Based Services in Vehicular Networks." IEEE Wireless Communications Letters 9, no. 10 (2020): 1633–37. http://dx.doi.org/10.1109/lwc.2020.2999524.

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