In recent years, the rise of blockchain technology and its applications has led the software development industry to consider blockchain-powered Decentralized Applications (dApps) as serverless REST APIs. However, to engage with dApps, users require a blockchain wallet. This tool facilitates the generation and secure storage of a user's private key and verifies their identity, among other functionalities. Despite their utility, blockchain wallets present significant challenges, such as reliance on trusted third parties, vulnerability to adversaries observing and potentially linking user interactions, key recovery issues, and synchronization of cryptographic keys across multiple devices. This paper addresses these challenges by introducing a fully decentralized multi-platform wallet that leverages blockchain and InterPlanetary File System (IPFS) technologies for managing asymmetric keys and enabling key recovery. This novel approach empowers users to interact with dApps built on blockchain smart contracts while preserving their privacy and ensuring seamless key recovery in the case of device theft or damage. The proposed system is economically viable, with in-depth cost analysis, and demonstrates resilience against security and privacy attacks. A comparative analysis highlights the advantages of the new scheme over existing mainstream and state-of-the-art solutions. Finally, a preliminary prototype implementation is presented to validate the system's feasibility.

In recent years, the implementation of vehicle restricted areas (e.g., Low Emission Zones or Congestion Charge Zones) has proven effective in addressing urban traffic congestion and environmental pollution. Traditionally, these zones have been enforced using the highly centralized and infrastructure-expensive panoptic model. However, recent advancements in smart vehicle technology have enabled a shift towards decentralized, infrastructure-free approaches such as the lateral surveillance model. While offering significant advantages, this novel model also presents relevant security and privacy challenges, including potential misuse and widespread surveillance. This paper introduces a novel autonomous, decentralized, and infrastructure-free solution aligned with the lateral surveillance model. Leveraging Blockchain technology and privacy preservation measures, the system ensures user anonymity during fee pricing and payment processes, and it is capable of detecting and sanctioning dishonest drivers. To assess the applicability of the new scheme in real-world scenarios, it was implemented and tested in controlled environments as well as a low-traffic street. The evaluation included an assessment of the gas costs associated with the smart contracts and a detailed scalability analysis. The theoretical and experimental results demonstrate the feasibility of the proposed solution.

New digital technologies generate large amounts of information. This data is processed by Service Providers in order to improve and develop new services and products, but also to fund themselves. However, processing personal data may result in the extraction of sensitive information, which, in turn, may lead to jeopardizing the users’ privacy. To mitigate this significant risk, the European Parliament and Council of the European Union elaborated the General Data Protection Regulation (GDPR). This regulation forces Service Providers to obtain Data Subjects’ explicit consent prior to collecting and processing their personal data. Nevertheless, the GDPR’s legislative text does not define how Service Providers must transparently demonstrate that they already have these consents. Moreover, most individuals do not know the rights they have over their personal data, neither does this regulation provide them with efficient methods to be aware of what third parties are doing with such data. In order to address this situation, we propose a lightweight blockchain-based GDPR-compliant personal data management platform. The new solution provides public access to immutable evidences that reflect the reached agreements between Data Subjects and Service Providers. In this way, Service Providers can effectively demonstrate that they are fulfilling the regulation, and Data Subjects are able to control and manage their personal data according to their legitimate rights. We have implemented the new system, and we have performed a detailed study which includes: GDPR-compliance, provided functionality, security and privacy issues, and the cost in terms of gas and US dollars of the different operations to be run on the blockchain.

Low Emission Zones (LEZ)s are areas where access restrictions to polluting vehicles are enforced. These infrastructures have become a main mechanism in large cities to deal with urban traffic and environmental pollution. A main problem of practical LEZs is that they generally depend on a camera network that identifies users and jeopardizes their privacy. In the literature, there are some privacy-preserving works that rely on camera-free approaches; however, they still suffer from a major issue: they depend on centralized entities to manage the vehicles’ accesses/departures and their corresponding fee payment. Those centralized entities represent a critical single point of failure in the system, endangering its security and availability. In order to address this situation, this paper proposes a new scheme that decentralizes the LEZ management, dealing with vehicle accesses as blockchain transactions, and pricing and charging them using smart contracts. In order to validate the deployability of the new scheme in real scenarios, it has been implemented and tested in both a controlled environment and a low-traffic street. The evaluation of the smart contracts’ costs in terms of gas has been included in the performed tests. The results obtained are satisfactory and show the feasibility of the new proposal.

Car Sharing is an innovative transport concept that has emerged to contribute to efficient use of vehicles in urban areas that nowadays suffer from traffic congestion or parking unavailability. Several companies such as vehicle manufacturers have identified the business opportunities related with the Car Sharing market and realized the potential of providing this service to end-users under a private car sharing scenario. However, remaining technical challenges related with the secure management of digital permissions that grant access to vehicles must be addressed. In this paper, we propose a key management system that enables car-sharing use cases, based on a central key management server and a distributed management of the PKI infrastructure. Our system out-stands by providing accountability on the actor's and being resilient to internal attackers that attempt to impersonate system entities, provide false credentials to honest users or illegally take over a vehicle.

The traffic control system proposed in this article has as its main objectives the security, the reliability and the anonymity of the vehicle access to traffic-restricted urban zones. The aim of these zones is to reduce atmospheric pollution in urban centers. The presented approach makes use of smartphones as a communication device between the user and the virtual barrier, which acts as electronic validator and controls the access to the restricted zone. The access is fast (it does not require the complete stop of the vehicle) and is less invasive when compared to existing systems that are based on video camera recording. This is a versatile and cost-efficient system that can be adapted to other access-controlled urban settings: parking lots, sport event access zones, festivals, etc.

Access control management is an important area of research within the security field. Several models have been proposed to manage the access rights of users over restricted resources, which are mainly based on defining rules between specific entities and concrete resources. Though these approaches are enough to manage organizations involving a limited number of entities and resources, the specification of rules or constraints for large and heterogeneous scenarios may imply a considerable burden to the administrators. To palliate this problem, we propose a generic ontology-based solution to manage the access control that can greatly simplify and speed up the definition of rules in complex scenarios and that can also improve the interoperability between heterogeneous settings. Moreover, we show its potential by applying it in two highly dynamic and large scenarios, i.e., Online Social Networks (OSNs) and the Cloud.

Great cities try to prevent from high levels of pollution and traffic jams by restricting the access of vehicles to centric zones, also known as Low-Emission Zones (LEZ). Depending on the topology of the city and also on the traffic patterns and contamination levels, the LEZ can be divided in multiple zones with different prices, obtaining a Multifare Low Emission Zone. Multifare LEZs must manage not only entrances and departures but also changes of zone. Some of the most important issues of LEZs are the risk of losing privacy of the citizen who drive through the LEZ and a significant error percentage on detection of fraudulent drivers. In this article, an Electronic Road Pricing (ERP) system designed specifically for cities with multifare Low-Emission Zones is proposed. Its aim is to detect fraud and to preserve driver's privacy. Using revocable anonymity only fraudulent drivers lose their privacy.

Social networks have become an essential meeting point for millions of individuals willing to publish and consume huge quantities of heterogeneous information. Some studies have shown that the data published in these platforms may contain sensitive personal information and that external entities can gather and exploit this knowledge for their own benefit. Even though some methods to preserve the privacy of social networks users have been proposed, they generally apply rigid access control measures to the protected content and, even worse, they do not enable the users to understand which contents are sensitive. Last but not least, most of them require the collaboration of social network operators or they fail to provide a practical solution capable of working with well-known and already deployed social platforms. In this paper, we propose a new scheme that addresses all these issues. The new system is envisaged as an independent piece of software that does not depend on the social network in use and that can be transparently applied to most existing ones. According to a set of privacy requirements intuitively defined by the users of a social network, the proposed scheme is able to: (i) automatically detect sensitive data in users’ publications; (ii) construct sanitized versions of such data; and (iii) provide privacy-preserving transparent access to sensitive contents by disclosing more or less information to readers according to their credentials toward the owner of the publications. We also study the applicability of the proposed system in general and illustrate its behavior in two case studies.

The high levels of pollution and traffic congestion present in almost all major cities around the world have brought solutions such as the deployment of electronic toll systems in some of these cities. The main purpose of those electronic toll systems is to restrict the access of vehicles to certain city areas, named low emission zones. Since its adoption, this solution has proven to be quite promising. However, current proposals are still far from being ideal. More specifically, current schemes still introduce a significant error percentage in the detection of fraudulent drivers. Moreover, they usually require toll systems to be equipped with cameras that take pictures of all the vehicles that pass through the control points. This behavior may represent a serious privacy threat for the drivers. In this article, a new electronic toll system is proposed. The aim of the new proposal is to detect fraud while preserving drivers privacy. More concretely, it provides a non-probabilistic fraud control, and the control points only take pictures of the vehicles that misbehave. Last but not least, the proposed system applies an enhanced dynamic pricing that can help the authorities to better distribute traffic over the road network. Copyright © 2016 John Wiley & Sons, Ltd.

Web search engines (WSEs) use search queries to profile users and to provide personalized services like query disambiguation or refinement. These services are valuable because users get an enhanced search experience. However, the compiled user profiles may contain sensitive information that might represent a privacy threat. This issue should be addressed in a way that it also preserves the utility of the profile with regard to search services. State‐of‐the‐art approaches tackle these issues by generating and submitting fake queries that are related to the interests of the user. This technique allows the WSE to only know general (and useful) data while the detailed (and potentially private) data are obfuscated. To build fake queries, these proposals rely on past queries to obtain user interests. However, we argue that this is not always the best strategy and, in this article, we study the use of social networks to gather more accurate user profiles that enable better personalized service while offering a similar, or even better, level of practical privacy. These hypotheses are empirically supported by evaluations using real profiles gathered from Twitter and a set of AOL search queries.

Web search engines (WSEs) build user profiles and use them to offer an enhanced web search experience. Nevertheless, these elements might contain sensitive data that may represent a privacy threat for the users. There are some works in the literature that address this situation while preserving the profile usefulness. These schemes submit synthetic queries that are fake but related to the real general interests of the user. Specifically, they rely on past user queries to obtain the legitimate interests of each user. We argue that this is not always the best strategy and, in this paper, we study the use of social networks to gather this information and provide a better personalized service while offering an equivalent privacy level.

The advent of new information sharing technologies has led society to a scenario where thousands of textual documents are publicly published every day. The existence of confidential information in many of these documents motivates the use of measures to hide sensitive data before being published, which is precisely the goal of document sanitization. Even though methods to assist the sanitization process have been proposed, most of them are focused on the detection of specific types of sensitive entities for concrete domains, lacking generality and and requiring user supervision. Moreover, to hide sensitive terms, most approaches opt to remove them, a measure that hampers the utility of the sanitized document. This paper presents a general-purpose sanitization method that, based on information theory and exploiting knowledge bases, detects and hides sensitive textual information while preserving its meaning. Our proposal works in an automatic and unsupervised way and it can be applied to heterogeneous documents, which make it specially suitable for environments with massive and heterogeneous information-sharing needs. Evaluation results show that our method outperforms strategies based on trained classifiers regarding the detection recall, whereas it better retains the document's utility compared to term-suppression methods.

Web search engines profile their users by storing and analyzing their past searches. Profiles reflect the interests of the users and enable web search engines to offer a better service. In this way, search results are personalized to fulfill the expectations of each individual user. Nevertheless, this service is not provided without cost. User profiles contain information that can be considered private and personal. This represents a serious privacy threat which must be addressed. Several privacy-preserving techniques which try to prevent this situation can be found in the literature. In this paper, we focus on those that work directly in the computer of the users without requiring any external entity. More specifically, we propose a new single-party scheme that addresses the trade-off between privacy and quality of service but it does not require any change at the server side. The performance of this new method has been evaluated using real search queries extracted from the AOL's files. The results achieved show that our proposal works as expected and it can be considered a proper option for those users who are concerned about their privacy.

Vehicular ad hoc networks (VANETs) allow vehicle-to-vehicle communication and, in particular, vehicle-generated announcements. Vehicles can use such announcements to warn nearby vehicles about road conditions (traffic jams, accidents). Thus, they can greatly increase the safety of driving. However, their trustworthiness must be guaranteed. A new system for vehicle-generated announcements is presented that is secure against external and internal attackers attempting to send fake messages. Internal attacks are thwarted by using an endorsement mechanism based on multisignatures. Besides, this scheme ensures that vehicles volunteering to generate and/or endorse trustworthy announcements do not have to sacrifice their privacy.