Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

Cloud Computing in VANETs (CC-V) has been investigated into two major themes of research including Vehicular Cloud Computing (VCC) and Vehicle using Cloud (VuC). VCC is the realization of autonomous cloud among vehicles to share their abundant resources. VuC is the efficient usage of conventional cloud by on-road vehicles via a reliable Internet connection. Recently, number of advancements have been made to address the issues and challenges in VCC and VuC. This paper qualitatively reviews CC-V with the emphasis on layered architecture, network component, taxonomy, and future challenges. Specifically, a four-layered architecture for CC-V is proposed including perception, co-ordination, artificial intelligence and smart application layers. Three network component of CC-V namely, vehicle, connection and computation are explored with their cooperative roles. A taxonomy for CC-V is presented considering major themes of research in the area including design of architecture, data dissemination, security, and applications. Related literature on each theme are critically investigated with comparative assessment of recent advances. Finally, some open research challenges are identified as future issues. The challenges are the outcome of the critical and qualitative assessment of literature on CC-V

Practical Schemes For Privacy & Security Enhanced RFID

Proper privacy protection in RFID systems is important. However, many of the schemes known are impractical, either because they use hash functions instead of the more hardware efficient symmetric encryption schemes as a efficient cryptographic primitive, or because they incur a rather costly key search time penalty at the reader. Moreover, they do not allow for dynamic, fine-grained access control to the tag that cater for more complex usage scenarios. In this paper we investigate such scenarios, and propose a model and corresponding privacy friendly protocols for efficient and fine-grained management of access permissions to tags. In particular we propose an efficient mutual authentication protocol between a tag and a reader that achieves a reasonable level of privacy, using only symmetric key cryptography on the tag, while not requiring a costly key-search algorithm at the reader side. Moreover, our protocol is able to recover from stolen readers.Comment: 18 page

Internet of things security: A top-down survey

International audienceInternet of Things (IoT) is one of the promising technologies that has attracted a lot of attention in both industrial and academic fields these years. It aims to integrate seamlessly both physical and digital worlds in one single ecosystem that makes up a new intelligent era of Internet. This technology offers a huge business value for organizations and provides opportunities for many existing applications such as energy, healthcare and other sectors. However, as new emergent technology, IoT suffers from several security issues which are most challenging than those from other fields regarding its complex environment and resources-constrained IoT devices. A lot of researches have been initiated in order to provide efficient security solutions in IoT, particularly to address resources constraints and scalability issues. Furthermore, some technologies related to networking and cryptocurrency fields such as Software Defined Networking (SDN) and Blockchain are revolutionizing the world of the Internet of Things thanks to their efficiency and scalability. In this paper, we provide a comprehensive top down survey of the most recent proposed security and privacy solutions in IoT. We discuss particularly the benefits that new approaches such as blockchain and Software Defined Networking can bring to the security and the privacy in IoT in terms of flexibility and scalability. Finally, we give a general classification of existing solutions and comparison based on important parameters

A Trust-Based Adaptive Access Control Model for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have recently attracted much interest in the research community because of their wide range of applications. One emerging application for WSNs involves their use in healthcare where they are generally termed Wireless Medical Sensor Networks (WMSNs). In a hospital, fitting patients with tiny, wearable, wireless vital sign sensors would allow doctors, nurses and others to continuously monitor the state of those in their care. In the healthcare industry, patients are expected to be treated in reasonable time and any loss in data availability can result in further decline in the patient’s condition or can even lead to death. Therefore, the availability of data is more important than security concerns. The overwhelming priority is to take care of the patient, but the privacy and confidentiality of that patient’s medical records cannot be neglected. In current healthcare applications, there are many problems concerning security policy violations such as unauthorised denial of use, unauthorised information modification and unauthorised information release of medical data in the real world environment. Current WSN access control models used the traditional Role-Based Access Control (RBAC) or cryptographic methods for data access control but the systems still need to predefine attributes, roles and policies before deployment. It is, however, difficult to determine in advance all the possible needs for access in real world applications because there may be unanticipated situations at any time. This research proceeds to study possible approaches to address the above issues and to develop a new access control model to fill the gaps in work done by the WSN research community. Firstly, the adaptive access control model is proposed and developed based on the concept of discretionary overriding to address the data availability issue. In the healthcare industry, there are many problems concerning unauthorised information release. So, we extended the adaptive access control model with a prevention and detection mechanism to detect security policy violations, and added the concept of obligation to take a course of action when a restricted access is granted or denied. However, this approach does not consider privacy of patients’ information because data availability is prioritised. To address the conflict between data availability and data privacy, this research proposed the Trust-based Adaptive Access Control (TBA2C) model that integrates the concept of trust into the previous model. A simple user behaviour trust model is developed to calculate the behaviour trust value which measures the trustworthiness of the users and that is used as one of the defined thresholds to override access policy for data availability purpose, but the framework of the TBA2C model can be adapted with other trust models in the research community. The trust model can also protect data privacy because only a user who satisfies the relevant trust threshold can get restricted access in emergency and unanticipated situations. Moreover, the introduction of trust values in the enforcement of authorisation decisions can detect abnormal data access even from authorised users. Ponder2 is used to develop the TBA2C model gradually, starting from a simple access control model to the full TBA2C. In Ponder2, a Self-Managed Cell (SMC) simulates a sensor node with the TBA2C engine inside it. Additionally, to enable a full comparison with the proposed TBA2C model, the Break-The-Glass Role Based Access Control (BTGRBAC) model is redesigned and developed in the same platform (Ponder2). The proposed TBA2C model is the first to realise a flexible access control engine and to address the conflict between data availability and data privacy by combining the concepts of discretionary overriding, the user behaviour trust model, and the prevention and detection mechanism

Privacy-Preserving Ride Sharing Scheme for Autonomous Vehicles

The transport sector is set to undergo an overall change with the advent of autonomous vehicles embedded with artificial intelligence and machine learning. Autonomous vehicles will not only make the road safer but also will improve the efficiency of the modern transport system. Ride sharing is a major gamechanger in the transport industry. Autonomous Vehiclescan make ride sharingpopular, convenientand necessary because it eliminates the need of a driver and will help in recuperating the initial cost of the vehicle. In current scenario, the organization of ride sharing requires the users to disclose sensitive private information not only about the pick-up and drop-off locations but also other details such as name and contact details. In this paper, we propose a scheme to facilitate ride sharing and address the privacy issues that plague down the current industry. The scheme encrypts data using similarity measurement technique to preserve the privacy of the user. The ride sharing route is divided into cells, which is further represented by one bit in a binary vector. Binary vectors are used to represent the trip data of each user.The encryption of the vector data is submitted to a server. The server can measure the similarity of the users’ trip data and find other users who can share rides along the same route without knowing the data. The proposed scheme can facilitate ride sharing without disclosing private information. The scheme is implemented using Visual C on a real map. The measurements from the results have confirmed that the scheme is effective when ride sharing becomes popular and the server needs to organize a large number of rides in short time

A comprehensive survey of V2X cybersecurity mechanisms and future research paths

Recent advancements in vehicle-to-everything (V2X) communication have notably improved existing transport systems by enabling increased connectivity and driving autonomy levels. The remarkable benefits of V2X connectivity come inadvertently with challenges which involve security vulnerabilities and breaches. Addressing security concerns is essential for seamless and safe operation of mission-critical V2X use cases. This paper surveys current literature on V2X security and provides a systematic and comprehensive review of the most relevant security enhancements to date. An in-depth classification of V2X attacks is first performed according to key security and privacy requirements. Our methodology resumes with a taxonomy of security mechanisms based on their proactive/reactive defensive approach, which helps identify strengths and limitations of state-of-the-art countermeasures for V2X attacks. In addition, this paper delves into the potential of emerging security approaches leveraging artificial intelligence tools to meet security objectives. Promising data-driven solutions tailored to tackle security, privacy and trust issues are thoroughly discussed along with new threat vectors introduced inevitably by these enablers. The lessons learned from the detailed review of existing works are also compiled and highlighted. We conclude this survey with a structured synthesis of open challenges and future research directions to foster contributions in this prominent field.This work is supported by the H2020-INSPIRE-5Gplus project (under Grant agreement No. 871808), the ”Ministerio de Asuntos Económicos y Transformacion Digital” and the European Union-NextGenerationEU in the frameworks of the ”Plan de Recuperación, Transformación y Resiliencia” and of the ”Mecanismo de Recuperación y Resiliencia” under references TSI-063000-2021-39/40/41, and the CHIST-ERA-17-BDSI-003 FIREMAN project funded by the Spanish National Foundation (Grant PCI2019-103780).Peer ReviewedPostprint (published version

Dynamic Deployment of Sensing Experiments in the Wild Using Smartphones

Part 1: Full Research PapersInternational audienceWhile scientific communities extensively exploit simulations to validate their theories, the relevance of their results strongly depends on the realism of the dataset they use as an input. This statement is particularly true when considering human activity traces, which tend to be highly unpredictable. In this paper, we therefore introduce APISENSE, a distributed crowdsensing platform for collecting realistic activity traces. In particular, APISENSE provides to scientists a participative platform to help them to easily deploy their sensing experiments in the wild. Beyond the scientific contributions of this platform, the technical originality of APISENSE lies in its Cloud orientation and the dynamic deployment of scripts within the mobile devices of the participants.We validate this platform by reporting on various crowdsensing experiments we deployed using Android smartphones and comparing our solution to existing crowdsensing platforms

Architectures for the Future Networks and the Next Generation Internet: A Survey

Networking research funding agencies in the USA, Europe, Japan, and other countries are encouraging research on revolutionary networking architectures that may or may not be bound by the restrictions of the current TCP/IP based Internet. We present a comprehensive survey of such research projects and activities. The topics covered include various testbeds for experimentations for new architectures, new security mechanisms, content delivery mechanisms, management and control frameworks, service architectures, and routing mechanisms. Delay/Disruption tolerant networks, which allow communications even when complete end-to-end path is not available, are also discussed