Provision of next-generation personalized cyber-physical services

2022

ICA

Self Cite

Most recent solutions for users’ authentication in Industry 4.0 scenarios are based on unique biological characteristics that are captured from users and recognized using artificial intelligence and machine learning technologies. These biometric applications tend to be computationally heavy, so to monitor users in an unobtrusive manner, sensing and processing modules are physically separated and connected through point-to-point wireless communication technologies. However, in this approach, sensors are very resource constrained, and common cryptographic techniques to protect private users’ information while traveling in the radio channel cannot be implemented because their computational cost. Thus, new security solutions for those biometric authentication systems in their short-range wireless communications are needed. Therefore, in this paper, we propose a new cryptographic approach addressing this scenario. The proposed solution employs lightweight operations to create a secure symmetric encryption solution. This cipher includes a pseudo-random number generator based, also, on simple computationally low-cost operations in order to create the secret key. In order to preserve and provide good security properties, the key generation and the encryption processes are fed with a chaotic number sequence obtained through the numerical integration of a new four-order hyperchaotic dynamic. An experimental analysis and a performance evaluation are provided in the experimental section, showing the good behavior of the described solution.

Section: Introductionmentioning

confidence: 99%

Lightweight encryption for short-range wireless biometric authentication systems in Industry 4.0

2022

ICA

Self Cite

“…Future pervasive sensing platforms, supported by new technological paradigms such as Internet of Things (IoT) 1 and cyberphysical systems (CPS), 2 will enable a new generation of eHealth and well-being services. These innovative services will improve their performance (including their personalization, 3 cost, and processing delay) with respect to currently existing solutions. In order to do that, a large catalog of biological signals, environmental measures, and people’s behavioral information (among other data sources) must be captured and processed by well-being services.…”

Section: Introductionmentioning

confidence: 99%

Enabling trustworthy personal data protection in eHealth and well-being services through privacy-by-design

Robles

International Journal of Distributed Sensor Networks

Alcarria

et al. 2020

Self Cite

Users are each day more aware of their privacy and data protection. Although this problem is transversal to every digital service, it is especially relevant when critical and personal information is managed, as in eHealth and well-being services. During the last years, many different innovative services in this area have been proposed. However, data management challenges are still in need of a solution. In general, data are directly sent to services but no trustworthy instruments to recover these data or remove them from services are available. In this scheme, services become the users’ data owners although users keep the rights to access, modify, and be forgotten. Nevertheless, the adequate implementation of these rights is not guaranteed, as services use the received data with commercial purposes. In order to address and solve this situation, we propose a new trustworthy personal data protection mechanism for well-being services, based on privacy-by-design technologies. This new mechanism is based on Blockchain networks and indirection functions and tokens. Blockchain networks execute transparent smart contracts, where users’ rights are codified, and store the users’ personal data which are never sent or given to external services. Besides, permissions and privacy restrictions designed by users to be applied to their data and services consuming them are also implemented in these smart contracts. Finally, an experimental validation is also described to evaluate the Quality of Experience (in terms of user satisfaction) and Quality of Service (in terms of processing delay) compared to traditional service provision solutions.

“…As can be seen, content is managed by users, who can manually trigger an information actualization; or create automatic mechanisms through prosumer environments [25] to modify the system behaviour and information characteristics according to a collection of rules or situations. These information control orders are the final cause of inefficiencies in fixed configurations but they are external to any information system or solution, so they are not considered in this work.…”

Section: Efficient Communications With Resource Constrained Informmentioning

confidence: 99%

Enabling Efficient Communications with Resource Constrained Information Endpoints in Smart Homes

Sánchez-de-Rivera

Alcarria

et al. 2019

Sensors

Smart Homes are one of the most promising real applications of Internet of Things and Cyber-Physical Systems. Devices and software components are deployed to create enhanced living environments where physical information is captured by sensors, sent to servers and finally transmitted to information endpoints to be consumed after its processing. These systems usually employ resource constrained components in dense architectures supported by massive machine type communications. Components, to adapt to different scenarios, present several configuration options. In machine type communications, these configuration options should be selected dynamically and automatically. Many works have addressed this situation in relation to sensor-server communications but endpoints are still mostly manually configured. Therefore, in this paper it is proposed an automatic and dynamic configuration algorithm, based on the idea of “efficiency,” for information endpoints in the context of Smart Homes. Different costs associated to endpoint-server communications in Smart Homes are identified and mathematically modelled. Using this model and real measurements, the most efficient configuration is selected for each endpoint at each moment, not only guarantying the interoperability of devices but also ensuring an adequate resource usage, for example, modifying the endpoints’ lifecycle or the information compression mechanism. In order to validate the proposed solution, an experimental validation including both real implementation and simulation scenarios is provided.