This paper presents a study of positioning system that provides advanced information services based on Wi-Fi and Bluetooth Low Energy (BLE) technologies. It uses Wi-Fi for rough positioning and BLE for fine positioning. It is designed for use in public transportation system stations and terminals where the conditions are “hostile” or unfavourable due to signal noise produced by the continuous movement of passengers and buses, data collection conducted in the constant presence thereof, multipath fading, non-line of sight (NLOS) conditions, the fact that part of the wireless communication infrastructure has already been deployed and positioned in a way that may not be optimal for positioning purposes, variable humidity conditions, etc. The ultimate goal is to provide a service that may be used to assist people with special needs. We present experimental results based on scene analysis; the main distance metric used was the Euclidean distance but the Mahalanobis distance was also used in one case. The algorithm employed to compare fingerprints was the weighted k-nearest neighbor one. For Wi-Fi, with only three visible access points, accuracy ranged from 3.94 to 4.82 m, and precision from 5.21 to 7.0 m 90% of the time. With respect to BLE, with a low beacon density (1 beacon per 45.7 m²), accuracy ranged from 1.47 to 2.15 m, and precision from 1.81 to 3.58 m 90% of the time. Taking into account the fact that this system is designed to work in real situations in a scenario with high environmental fluctuations, and comparing the results with others obtained in laboratory scenarios, our results are promising and demonstrate that the system would be able to position users with these reasonable values of accuracy and precision.

Public-key cryptography is too slow for general purpose encryption, with most applications limiting its use as much as possible. Some secure protocols, especially those that enable forward secrecy, make a much heavier use of public-key cryptography, increasing the demand for lightweight cryptosystems that can be implemented in low powered or mobile devices. This performance requirements are even more significant in critical infrastructure and emergency scenarios where peer-to-peer networks are deployed for increased availability and resiliency. We benchmark several public-key key-exchange algorithms, determining those that are better for the requirements of critical infrastructure and emergency applications and propose a security framework based on these algorithms and study its application to decentralized node or sensor networks.

Vehicular ad hoc networks (VANETs) is considered a milestone in improving the safety and efficiency in transportation. Nevertheless, when information from the vehicular communications is combined with data from the cloud, it also introduces some privacy risks by making it easier to track the physical location of vehicles. For this reason, to guarantee the proper performance of a \{VANET\} it is essential to protect the service against malicious users aiming at disrupting the proper operation of the network. Current researches usually define a traditional identity-based authentication for nodes, which are loaded with individual credentials. However, the use of these credentials in VANETs without any security mechanism enables vehicle tracking and therefore, violate users’ privacy, a risk that may be overcome by means of appropriate anonymity schemes. This comes at the cost, however, of on the one hand preventing VANET centralized authorities from identifying malicious users and revoking them from the network, or on the other hand to avoid complete anonymity of nodes in front of the CA thus to allow their revocation. In this paper, a novel revocation scheme that is able to track and revoke specific malicious users only after a number of complaints have been received while otherwise guaranteeing node’s k-anonymity is described. The proper performance of these mechanisms has been widely evaluated with NS-2 simulator and an analytical model validated with scripts. The results show that presented work is a promising approach in order to increase privacy protection while allowing revocation with little extra costs.Postprint (author's final draft

This paper describes the design and analysis of a new scheme for the authenticated exchange of confidential information in insecure environments within the Internet of Things, which allows a receiver of a message to authenticate the sender and compute a secret key shared with it. The proposal is based on the concept of a non-interactive zero-knowledge proof, so that in a single communication, relevant data may be inferred to verify the legitimacy of the sender. Besides, the new scheme uses the idea under the Diffie–Hellman protocol for the establishment of a shared secret key. The proposal has been fully developed for platforms built on the Android Open Source Project, so it can be used in any device or sensor with this operating system. This work provides a performance study of the implementation and a comparison between its promising results and others obtained with similar schemes.

Smart-locks have become increasingly popular for access to homes and businesses in many countries, because of their ease of use and adaptability. These locks offer a simple and secure alternative to traditional key-based entry, making them an attractive choice for both residential and commercial properties. Nevertheless, it is essential to acknowledge the potential security threats that come with any new technology. The security of smart-locks is particularly critical, as a breach could result in unauthorized entry. Since the smart-locks can connect, there are different ways to check if vulnerabilities can be found easily or on the contrary, if the security level is high. Two of the main ways of checking the security level of this kind of IoT device are the information that can be obtained from the Android application and the security level of the Bluetooth connection. Many vulnerabilities can be found in the Android smart lock management application. This application is very useful to perform all the configurations with such a lock, but if it is not properly implemented and secured, it can provide clues for malicious users to perform unauthorized access to the system. Another security factor is the Bluetooth connection. This ensures that only authorized users have access to the property. In this work, we have analyzed the security level of different parts of smart-locks. In particular, we have analyzed the security of the applications for the most important smart-locks on the market. This study reveals relevant information such as whether the application is obfuscated or not, the encryption algorithm for the Bluetooth connection, or relevant URLs that applications use to connect to the cloud. The security of the Bluetooth connection between the smartphone application and two selected smart-locks was also analyzed. It was demonstrated that if no encryption is used for the Bluetooth connection, the smart-lock is not secure, but if AES encryption is used, the security level is high.

This paper introduces a cutting-edge approach that combines facial recognition and drowsiness detection technologies with Internet of Things capabilities, including 5G/6G connectivity, aimed at bolstering vehicle security and driver safety. The delineated two-phase project is tailored to strengthen security measures and address accidents stemming from driver distraction and fatigue. The initial phase is centered on facial recognition for driver authentication before vehicle initiation. Following successful authentication, the subsequent phase harnesses continuous eye monitoring features, leveraging edge computing for real-time processing to identify signs of drowsiness during the journey. Emphasis is placed on video-based identification and analysis to ensure robust drowsiness detection. Finally, the study highlights the potential of these innovations to revolutionize automotive security and accident prevention within the context of intelligent transport systems.