A passive and privacy-friendly area based localization for wireless indoor networks

Ahmad, Nazrul M.; Amin, Anang Hudaya Muhamad; Kannan, Subarmaniam; Ali, Afiq Muzakkir Mat; Abdollah, Mohd Faizal; Yusof, Robiah

doi:10.1109/tenconspring.2016.7519407

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…There has been a number of fingerprint-based approaches in the literature. For instance, Ahmad et al follow an approach in the sense that all localization data is to be stored on the individual device rather than a centralized remote server [10]. Their model uses a Wi-Fi fingerprint database to localize a user and their system can dynamically update itself as the phone is consistently collecting data.…”

Section: Related Workmentioning

confidence: 99%

“…It has been proven to be as accurate as traditional centralized fingerprint databases as it also passive collects beacon-stuffing information from APs as well. Beacon stuffing releases information to the phone such as Region ID, Location Number, AP ID, and AP fingerprint that is recorded at its location [10]. This system provides essentially perfect security to the user, assuming the phone is not compromised.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Server-Side Fingerprint-Based Indoor Localization Using Encrypted Sorting

Quijano

Akkaya

2019

2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems Workshops (MASSW)

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GPS signals, the main origin of navigation, are not functional in indoor environments. Therefore, Wi-Fi access points have started to be increasingly used for localization and tracking inside the buildings by relying on fingerprint-based approach. However, with these types of approaches, several concerns regarding the privacy of the users have arisen. Malicious individuals can determine a clients daily habits and activities by simply analyzing their wireless signals. While there are already efforts to incorporate privacy to the existing fingerprint-based approaches, they are limited to the characteristics of the homomorphic cryptographic schemes they employed. In this paper, we propose to enhance the performance of these approaches by exploiting another homomorphic algorithm, namely DGK, with its unique encrypted sorting capability and thus pushing most of the computations to the server side. We developed an Android app and tested our system within a Columbia University dormitory. Compared to existing systems, the results indicated that more power savings can be achieved at the client side and DGK can be a viable option with more powerful server computation capabilities.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Server-Side Fingerprint-Based Indoor Localization Using Encrypted Sorting

Quijano

Akkaya

2019

2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems Workshops (MASSW)

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Preserving Privacy in Wi-Fi Localization with Plausible Dummy Locations

Zhang,

Zhao,

Zhang

2024

Signals and Communication Technology

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Privacy in Indoor Positioning Systems: A Systematic Review

Holcer

Torres-Sospedra

Gould

et al. 2020

2020 International Conference on Localization and GNSS (ICL-GNSS)

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This article presents a systematic review of privacy in indoor positioning systems. The selected 41 articles on location privacy preserving mechanisms employ non-inherently private methods such as encryption, k-anonymity, and differential privacy. The 15 identified mechanisms are categorized and summarized by where they are processed: on device, during transmission, or at a server. Trade-offs such as calculation speed, granularity, or complexity in setup are identified for each mechanism. In 40% of the papers, some trade-offs are minimized by combining several methods into a hybrid solution. The combinations of mechanisms and their levels of offered privacy are suggested based on a series of user mobility cases.

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A passive and privacy-friendly area based localization for wireless indoor networks

Cited by 4 publications

References 16 publications

Server-Side Fingerprint-Based Indoor Localization Using Encrypted Sorting

Server-Side Fingerprint-Based Indoor Localization Using Encrypted Sorting

Preserving Privacy in Wi-Fi Localization with Plausible Dummy Locations

Privacy in Indoor Positioning Systems: A Systematic Review

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