2024
Casanova-Marqués, Raúl
Privacy-enhancing technologies and privacy-enhancing cryptography for wearables PhD Thesis
Brno University of Technology, 2024.
Abstract | Links | BibTeX | Tags: A-wear, cryptography, Indoor positioning, Internet of things, privacy protection, wearables
@phdthesis{Casanova2024a,
title = {Privacy-enhancing technologies and privacy-enhancing cryptography for wearables},
author = {Raúl Casanova-Marqués},
url = {http://hdl.handle.net/10803/690875},
doi = {http://dx.doi.org/10.6035/14124.2024.839804},
year = {2024},
date = {2024-04-29},
urldate = {2024-04-29},
school = {Brno University of Technology},
abstract = {In response to escalating privacy concerns and the need for secure digital communication, cryptographic mechanisms have been developed to ensure impervious information exchange. However, traditional cryptographic approaches are inadequate in dynamic and resource-constrained environments, such as wearable devices. This thesis investigates attribute-based credential schemes, offering fine-grained access control based on user-specific attributes. Specifically, it assesses the effectiveness and scalability of attribute-based anonymous credential schemes within dynamic wearable device architectures. The study focuses on enhancing these schemes by incorporating user revocation while preserving privacy. Additionally, the research develops methods for attribute-based authentication protocols on smart cards with limited elliptic curve cryptography support and addresses usability challenges. Furthermore, the thesis explores the integration of anonymous authentication in collaborative indoor positioning systems to ensure privacy and security. It also delves into implementing attribute-based authentication in resource-constrained environments, including Internet of Things devices, and evaluating their feasibility in dynamic wearable device architectures.},
keywords = {A-wear, cryptography, Indoor positioning, Internet of things, privacy protection, wearables},
pubstate = {published},
tppubtype = {phdthesis}
}
In response to escalating privacy concerns and the need for secure digital communication, cryptographic mechanisms have been developed to ensure impervious information exchange. However, traditional cryptographic approaches are inadequate in dynamic and resource-constrained environments, such as wearable devices. This thesis investigates attribute-based credential schemes, offering fine-grained access control based on user-specific attributes. Specifically, it assesses the effectiveness and scalability of attribute-based anonymous credential schemes within dynamic wearable device architectures. The study focuses on enhancing these schemes by incorporating user revocation while preserving privacy. Additionally, the research develops methods for attribute-based authentication protocols on smart cards with limited elliptic curve cryptography support and addresses usability challenges. Furthermore, the thesis explores the integration of anonymous authentication in collaborative indoor positioning systems to ensure privacy and security. It also delves into implementing attribute-based authentication in resource-constrained environments, including Internet of Things devices, and evaluating their feasibility in dynamic wearable device architectures.