2023
Bravenec, Tomás
Exploiting Wireless Communications for Localization: Beyond Fingerprinting PhD Thesis
Universitat Jaume I. INIT, 2023.
Abstract | Links | BibTeX | Tags: A-wear, data analysis methods, geoprivacy, Indoor positioning, machine learning
@phdthesis{Bravenec2023d,
title = {Exploiting Wireless Communications for Localization: Beyond Fingerprinting},
author = {Tomás Bravenec},
url = {http://hdl.handle.net/10803/689593},
doi = {http://dx.doi.org/10.6035/14124.2023.868082},
year = {2023},
date = {2023-12-18},
school = {Universitat Jaume I. INIT},
abstract = {The field of Location-based Services (LBS) has experienced significant growth over the past decade, driven by increasing interest in fitness tracking, robotics, and eHealth. This dissertation focuses on evaluating privacy measures in Indoor Positioning Systems (IPS), particularly in the context of ubiquitous Wi-Fi networks. It addresses non-cooperative user tracking through the exploitation of unencrypted Wi-Fi management frames, which contain enough information for device fingerprinting despite MAC address randomization. The research also explores an algorithm to estimate room occupancy based on passive Wi-Fi frame sniffing and Received Signal Strength Indicator (RSSI) measurements. Such room occupancy detection has implications for energy regulations in smart buildings. Furthermore, the thesis investigates methods to reduce computational requirements of machine learning and positioning algorithms through optimizing neural networks and employing interpolation techniques for IPS based on RSSI fingerprinting. The work contributes datasets, analysis scripts, and firmware to improve reproducibility and supports advancements in the LBS field.},
keywords = {A-wear, data analysis methods, geoprivacy, Indoor positioning, machine learning},
pubstate = {published},
tppubtype = {phdthesis}
}
The field of Location-based Services (LBS) has experienced significant growth over the past decade, driven by increasing interest in fitness tracking, robotics, and eHealth. This dissertation focuses on evaluating privacy measures in Indoor Positioning Systems (IPS), particularly in the context of ubiquitous Wi-Fi networks. It addresses non-cooperative user tracking through the exploitation of unencrypted Wi-Fi management frames, which contain enough information for device fingerprinting despite MAC address randomization. The research also explores an algorithm to estimate room occupancy based on passive Wi-Fi frame sniffing and Received Signal Strength Indicator (RSSI) measurements. Such room occupancy detection has implications for energy regulations in smart buildings. Furthermore, the thesis investigates methods to reduce computational requirements of machine learning and positioning algorithms through optimizing neural networks and employing interpolation techniques for IPS based on RSSI fingerprinting. The work contributes datasets, analysis scripts, and firmware to improve reproducibility and supports advancements in the LBS field.
2022
Bravenec, Tomás; Torres-Sospedra, Joaquín; Gould, Michael; Fryza, Tomas
What Your Wearable Devices Revealed About You and Possibilities of Non-Cooperative 802.11 Presence Detection During Your Last IPIN Visit Proceedings Article
In: 2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN), pp. 1-7, IEEE, 2022, ISBN: 978-1-7281-6218-8.
Abstract | Links | BibTeX | Tags: geoprivacy, wearables
@inproceedings{Bravenec2022a,
title = {What Your Wearable Devices Revealed About You and Possibilities of Non-Cooperative 802.11 Presence Detection During Your Last IPIN Visit},
author = {Tomás Bravenec and Joaquín Torres-Sospedra and Michael Gould and Tomas Fryza},
doi = {https://doi.org/10.1109/IPIN54987.2022.9918134},
isbn = {978-1-7281-6218-8},
year = {2022},
date = {2022-09-06},
booktitle = {2022 IEEE 12th International Conference on Indoor Positioning and Indoor Navigation (IPIN)},
pages = {1-7},
publisher = {IEEE},
abstract = {The focus on privacy-related measures regarding wireless networks grew in last couple of years. This is especially important with technologies like Wi-Fi or Bluetooth, which are all around us and our smartphones use them not just for connection to the internet or other devices, but for localization purposes as well. In this paper, we analyze and evaluate probe request frames of 802.11 wireless protocol captured during the 11 th international conference on Indoor Positioning and Indoor Navigation (IPIN) 2021. We explore the temporal occupancy of the conference space during four days of the conference as well as non-cooperatively track the presence of devices in the proximity of the session rooms using 802.11 management frames, with and without using MAC address randomization. We carried out this analysis without trying to identify/reveal the identity of the users or in any way reverse the MAC address randomization. As a result of the analysis, we detected that there are still many devices not adopting MAC randomization, because either it is not implemented, or users disabled it. In addition, many devices can be easily tracked despite employing MAC randomization.},
keywords = {geoprivacy, wearables},
pubstate = {published},
tppubtype = {inproceedings}
}
The focus on privacy-related measures regarding wireless networks grew in last couple of years. This is especially important with technologies like Wi-Fi or Bluetooth, which are all around us and our smartphones use them not just for connection to the internet or other devices, but for localization purposes as well. In this paper, we analyze and evaluate probe request frames of 802.11 wireless protocol captured during the 11 th international conference on Indoor Positioning and Indoor Navigation (IPIN) 2021. We explore the temporal occupancy of the conference space during four days of the conference as well as non-cooperatively track the presence of devices in the proximity of the session rooms using 802.11 management frames, with and without using MAC address randomization. We carried out this analysis without trying to identify/reveal the identity of the users or in any way reverse the MAC address randomization. As a result of the analysis, we detected that there are still many devices not adopting MAC randomization, because either it is not implemented, or users disabled it. In addition, many devices can be easily tracked despite employing MAC randomization.
Dzurenda, Petr; Casanova-Marqués, Raúl; Malina, Lukas; Hajny, Jan
Real-world Deployment of Privacy-Enhancing Authentication System using Attribute-based Credentials Proceedings Article
In: Proceedings of the 17th International Conference on Availability, Reliability and Security, pp. 1-9, ACM, 2022, ISBN: 9781450396707.
Abstract | Links | BibTeX | Tags: A-wear, geoprivacy, wearables
@inproceedings{Dzurenda2022a,
title = {Real-world Deployment of Privacy-Enhancing Authentication System using Attribute-based Credentials},
author = {Petr Dzurenda and Raúl Casanova-Marqués and Lukas Malina and Jan Hajny},
doi = {https://doi.org/10.1145/3538969.3543803},
isbn = {9781450396707},
year = {2022},
date = {2022-08-01},
booktitle = {Proceedings of the 17th International Conference on Availability, Reliability and Security},
pages = {1-9},
publisher = {ACM},
abstract = {With the daily increase in digitalization and integration of the physical and digital worlds, we need to better protect users’ privacy and identity. Attribute-based Credentials (ABCs) seem to be a promising technology for this task. In this paper, we provide comprehensive analyses of the readiness, maturity, and applicability of ABCs to real-world applications. Furthermore, we introduce our Privacy-Enhancing Authentication System (PEAS), which is based on ABCs and meets all privacy requirements such as anonymity and unlinkability of the user’s activities. Besides privacy features, PEAS also provides revocation mechanisms to identify and revoke malicious users. The system is suitable for deployment in real-world scenarios and runs on a wide range of user devices (e.g., smart cards, smartphones, and wearables).},
keywords = {A-wear, geoprivacy, wearables},
pubstate = {published},
tppubtype = {inproceedings}
}
With the daily increase in digitalization and integration of the physical and digital worlds, we need to better protect users’ privacy and identity. Attribute-based Credentials (ABCs) seem to be a promising technology for this task. In this paper, we provide comprehensive analyses of the readiness, maturity, and applicability of ABCs to real-world applications. Furthermore, we introduce our Privacy-Enhancing Authentication System (PEAS), which is based on ABCs and meets all privacy requirements such as anonymity and unlinkability of the user’s activities. Besides privacy features, PEAS also provides revocation mechanisms to identify and revoke malicious users. The system is suitable for deployment in real-world scenarios and runs on a wide range of user devices (e.g., smart cards, smartphones, and wearables).
Casanova-Marqués, Raúl; Dzurenda, Petr; Hajny, Jan
Implementation of Revocable Keyed-Verification Anonymous Credentials on Java Card Proceedings Article
In: Proceedings of the 17th International Conference on Availability, Reliability and Security, pp. 1-8, ACM, 2022, ISBN: 9781450396707.
Abstract | Links | BibTeX | Tags: A-wear, geoprivacy
@inproceedings{Casanova2022a,
title = {Implementation of Revocable Keyed-Verification Anonymous Credentials on Java Card},
author = {Raúl Casanova-Marqués and Petr Dzurenda and Jan Hajny},
doi = {https://doi.org/10.1145/3538969.3543798},
isbn = {9781450396707},
year = {2022},
date = {2022-06-01},
booktitle = {Proceedings of the 17th International Conference on Availability, Reliability and Security},
pages = {1-8},
publisher = {ACM},
abstract = {Java Card stands out as a good choice for the development of smart card applications due to the high interoperability between different manufacturers, its security, and wide support of cryptographic algorithms. Despite extensive cryptographic support, current Java Cards do not support non-standard cryptographic algorithms such as post-quantum, secure-multiparty computations, and privacy-enhancing cryptographic schemes. Moreover, Java Card is restricted by the Application Programming Interface (API) in algebraic operations, which are the foundation of modern cryptographic schemes. This paper addresses the issue of developing these modern schemes by exploiting the limited cryptographic API provided by these types of cards. We show how to (ab)use the Java Card’s API to perform modular arithmetic operations, as well as basic operations on elliptic curves. Furthermore, we implement an attribute-based privacy-enhancing scheme on an off-the-shelf Java Card. To do so, we use our cryptographic API and several optimization techniques to make the scheme as efficient as possible. To demonstrate the practicality of our solution, we present the implementation results and benchmark tests.},
keywords = {A-wear, geoprivacy},
pubstate = {published},
tppubtype = {inproceedings}
}
Java Card stands out as a good choice for the development of smart card applications due to the high interoperability between different manufacturers, its security, and wide support of cryptographic algorithms. Despite extensive cryptographic support, current Java Cards do not support non-standard cryptographic algorithms such as post-quantum, secure-multiparty computations, and privacy-enhancing cryptographic schemes. Moreover, Java Card is restricted by the Application Programming Interface (API) in algebraic operations, which are the foundation of modern cryptographic schemes. This paper addresses the issue of developing these modern schemes by exploiting the limited cryptographic API provided by these types of cards. We show how to (ab)use the Java Card’s API to perform modular arithmetic operations, as well as basic operations on elliptic curves. Furthermore, we implement an attribute-based privacy-enhancing scheme on an off-the-shelf Java Card. To do so, we use our cryptographic API and several optimization techniques to make the scheme as efficient as possible. To demonstrate the practicality of our solution, we present the implementation results and benchmark tests.
2021
Casanova-Marqués, Raúl; Pascacio-de-los-Santos, Pavel; Hajny, Jan; Torres-Sospedra, Joaquín
Anonymous Attribute-based Credentials in Collaborative Indoor Positioning Systems Proceedings Article
In: Proceedings of the 18th International Conference on Security and Cryptography (SECRYPT 2021), pp. 791-797, SciTePress, 2021, ISBN: 978-989-758-524-1.
Abstract | Links | BibTeX | Tags: geoprivacy, Indoor positioning
@inproceedings{CasanovaMarques2021a,
title = {Anonymous Attribute-based Credentials in Collaborative Indoor Positioning Systems},
author = {Raúl Casanova-Marqués and Pavel Pascacio-de-los-Santos and Jan Hajny and Joaquín Torres-Sospedra },
doi = {http://dx.doi.org/10.5220/0010582507910797},
isbn = {978-989-758-524-1},
year = {2021},
date = {2021-09-01},
booktitle = {Proceedings of the 18th International Conference on Security and Cryptography (SECRYPT 2021)},
pages = {791-797},
publisher = {SciTePress},
abstract = {Collaborative Indoor Positioning Systems (CIPSs) have recently received considerable attention, mainly because they address some existing limitations of traditional Indoor Positioning Systems (IPSs). In CIPSs, Bluetooth Low Energy (BLE) can be used to exchange positioning data and provide information (the Received Signal Strength Indicator (RSSI)) to establish the relative distance between the actors. The collaborative models exploit the position of actors and the relative position among them to allow positioning to external actors or improve the accuracy of the existing actors. However, the traditional protocols (e.g., iBeacon) are not yet ready for providing sufficient privacy protection. This paper deals with privacy-enhancing technologies and their application in CIPS. In particular, we focus on cryptographic schemes which allow the verification of users without their identification, so-called Anonymous Attribute-based Credential (ABC) schemes. As the main contribution, we presen t a cryptographic scheme that allows security and privacy-friendly sharing of location information sent through BLE advertising packets. In order to demonstrate the practicality of our scheme, we also present the results from our implementation and benchmarks on different devices.},
keywords = {geoprivacy, Indoor positioning},
pubstate = {published},
tppubtype = {inproceedings}
}
Collaborative Indoor Positioning Systems (CIPSs) have recently received considerable attention, mainly because they address some existing limitations of traditional Indoor Positioning Systems (IPSs). In CIPSs, Bluetooth Low Energy (BLE) can be used to exchange positioning data and provide information (the Received Signal Strength Indicator (RSSI)) to establish the relative distance between the actors. The collaborative models exploit the position of actors and the relative position among them to allow positioning to external actors or improve the accuracy of the existing actors. However, the traditional protocols (e.g., iBeacon) are not yet ready for providing sufficient privacy protection. This paper deals with privacy-enhancing technologies and their application in CIPS. In particular, we focus on cryptographic schemes which allow the verification of users without their identification, so-called Anonymous Attribute-based Credential (ABC) schemes. As the main contribution, we presen t a cryptographic scheme that allows security and privacy-friendly sharing of location information sent through BLE advertising packets. In order to demonstrate the practicality of our scheme, we also present the results from our implementation and benchmarks on different devices.
2020
Holcer, Sylvia; Torres-Sospedra, Joaquín; Gould, Michael; Remolar, Inmaculada
Privacy in Indoor Positioning Systems:a systematic review Proceedings Article
In: 2020 International Conference on Localization and GNSS (ICL-GNSS), Tampere, Finland, 2020, pp. 1-6, IEEE 2020, ISBN: 978-1-7281-6455-7.
Abstract | Links | BibTeX | Tags: A-wear, geoprivacy
@inproceedings{Holcer2020,
title = {Privacy in Indoor Positioning Systems:a systematic review},
author = {Sylvia Holcer and Joaquín Torres-Sospedra and Michael Gould and Inmaculada Remolar},
doi = {http://www.doi.org/10.1109/ICL-GNSS49876.2020.9115496 },
isbn = {978-1-7281-6455-7},
year = {2020},
date = {2020-06-25},
booktitle = {2020 International Conference on Localization and GNSS (ICL-GNSS), Tampere, Finland, 2020},
pages = {1-6},
organization = {IEEE},
abstract = {This article proposes 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 set-up 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 estimated user mobility cases},
keywords = {A-wear, geoprivacy},
pubstate = {published},
tppubtype = {inproceedings}
}
This article proposes 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 set-up 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 estimated user mobility cases
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 set-up 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 estimated user mobility cases
Shubina, Victoriia; Holcer, Sylvia; Gould, Michael; Lohan, Elena Simona
Survey of Decentralized Solutions with Mobile Devices for User Location Tracking, Proximity Detection, and Contact Tracing in the COVID-19 Era Journal Article
In: Data, vol. 5, no. 4, pp. 87, 2020.
Links | BibTeX | Tags: A-wear, geolocation, geoprivacy, mobi, Monitoring
@article{Shubina2020,
title = {Survey of Decentralized Solutions with Mobile Devices for User Location Tracking, Proximity Detection, and Contact Tracing in the COVID-19 Era},
author = {Victoriia Shubina and Sylvia Holcer and Michael Gould and Elena Simona Lohan },
doi = {https://doi.org/10.3390/data5040087 },
year = {2020},
date = {2020-01-31},
journal = {Data},
volume = {5},
number = {4},
pages = {87},
keywords = {A-wear, geolocation, geoprivacy, mobi, Monitoring},
pubstate = {published},
tppubtype = {article}
}
2018
Ataei, M.
Location Data Privacy: Principles to Practice PhD Thesis
Westfälische Wilhelms-Universität Münster. Department of Geosciences, 2018.
BibTeX | Tags: GEO-C, geoprivacy
@phdthesis{Ataei2018,
title = {Location Data Privacy: Principles to Practice},
author = {Ataei, M. },
editor = {Christian Kray and Vítor Santos and Francisco Ramos-Romero (supervisors) },
year = {2018},
date = {2018-11-16},
address = {Münster, Germany},
school = {Westfälische Wilhelms-Universität Münster. Department of Geosciences},
keywords = {GEO-C, geoprivacy},
pubstate = {published},
tppubtype = {phdthesis}
}
2016
Nittel, Silvia; Bodum, Lars; Clarke, Keith C; Gould, Michael; Raposo, Paulo; Sharma, Jayant; Vasardani, Maria
Emerging Technological Trends likely to Affect GIScience in the Next 20 Years Book Chapter
In: Onsrund, H.; Kunh, W. GSDI Association Press (Ed.): Chapter 3, pp. 45, 2016.
Abstract | Links | BibTeX | Tags: decentralized spatial computations, geoprivacy, geovisual analytics, place, real-time sensor streams, technological future developments, user interfaces
@inbook{nittel2015emerging,
title = {Emerging Technological Trends likely to Affect GIScience in the Next 20 Years},
author = {Silvia Nittel and Lars Bodum and Keith C Clarke and Michael Gould and Paulo Raposo and Jayant Sharma and Maria Vasardani },
editor = {Onsrund, H. and Kunh, W. GSDI Association Press},
url = {https://www.researchgate.net/profile/Silvia_Nittel/publication/281973116_Emerging_Technological_Trends_likely_to_Affect_GIScience_in_the_Next_20_Years/links/56003fa908aeafc8ac8c50c3.pdf},
year = {2016},
date = {2016-02-04},
journal = {Advancing Geographic Information Science: the Past and Next Twenty Years},
pages = {45},
chapter = {3},
abstract = { In this article, the members of the “Emerging Technological Trends likely to
Affect GIScience in the Next 20 Years” panel, which was part of the International EarlyCareer
Scholars Summer Institutes in Geographic Information Vespucci Institute in Bar
Harbor, Maine in 2015, summarize their findings about major technological
developments that potentially will required novel research in GIScience.},
keywords = {decentralized spatial computations, geoprivacy, geovisual analytics, place, real-time sensor streams, technological future developments, user interfaces},
pubstate = {published},
tppubtype = {inbook}
}
In this article, the members of the “Emerging Technological Trends likely to
Affect GIScience in the Next 20 Years” panel, which was part of the International EarlyCareer
Scholars Summer Institutes in Geographic Information Vespucci Institute in Bar
Harbor, Maine in 2015, summarize their findings about major technological
developments that potentially will required novel research in GIScience.
Affect GIScience in the Next 20 Years” panel, which was part of the International EarlyCareer
Scholars Summer Institutes in Geographic Information Vespucci Institute in Bar
Harbor, Maine in 2015, summarize their findings about major technological
developments that potentially will required novel research in GIScience.
Nittel, Silvia; Bodum, Lars; Clarke, Keith; Gould, Michael; Raposo, Paulo; Sharma, Jayant; Vasardi, Maria
Emerging Technological Trends likely to Affect GIScience in the Next 20 Years Book Chapter
In: Onsrund, H.; Kunh, Werner (Ed.): Advancing Geographic Information Science: the past and next twenty years, Chapter 3, pp. 45, GSDI association press, 2016, ISBN: 978-0985244446.
Abstract | BibTeX | Tags: geoprivacy, geovisual analytics, GIScience, Real time analysis, user interfaces
@inbook{Nittel2015,
title = {Emerging Technological Trends likely to Affect GIScience in the Next 20 Years},
author = {Silvia Nittel and Lars Bodum and Keith Clarke and Michael Gould and Paulo Raposo and Jayant Sharma and Maria Vasardi},
editor = {H. Onsrund and Werner Kunh},
isbn = {978-0985244446},
year = {2016},
date = {2016-01-01},
booktitle = {Advancing Geographic Information Science: the past and next twenty years},
pages = {45},
publisher = {GSDI association press},
chapter = {3},
abstract = {In this article, the members of the “Emerging Technological Trends likely to Affect GIScience in the Next 20 Years” panel, which was part of the International Early- Career Scholars Summer Institutes in Geographic Information Vespucci Institute in Bar Harbor, Maine in 2015, summarize their findings about major technological developments that potentially will required novel research in GIScience. Keywords:},
keywords = {geoprivacy, geovisual analytics, GIScience, Real time analysis, user interfaces},
pubstate = {published},
tppubtype = {inbook}
}
In this article, the members of the “Emerging Technological Trends likely to Affect GIScience in the Next 20 Years” panel, which was part of the International Early- Career Scholars Summer Institutes in Geographic Information Vespucci Institute in Bar Harbor, Maine in 2015, summarize their findings about major technological developments that potentially will required novel research in GIScience. Keywords: