120 research outputs found

    Context-based Pseudonym Changing Scheme for Vehicular Adhoc Networks

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    Vehicular adhoc networks allow vehicles to share their information for safety and traffic efficiency. However, sharing information may threaten the driver privacy because it includes spatiotemporal information and is broadcast publicly and periodically. In this paper, we propose a context-adaptive pseudonym changing scheme which lets a vehicle decide autonomously when to change its pseudonym and how long it should remain silent to ensure unlinkability. This scheme adapts dynamically based on the density of the surrounding traffic and the user privacy preferences. We employ a multi-target tracking algorithm to measure privacy in terms of traceability in realistic vehicle traces. We use Monte Carlo analysis to estimate the quality of service (QoS) of a forward collision warning application when vehicles apply this scheme. According to the experimental results, the proposed scheme provides a better compromise between traceability and QoS than a random silent period scheme.Comment: Extended version of a previous paper "K. Emara, W. Woerndl, and J. Schlichter, "Poster: Context-Adaptive User-Centric Privacy Scheme for VANET," in Proceedings of the 11th EAI International Conference on Security and Privacy in Communication Networks, SecureComm'15. Dallas, TX, USA: Springer, June 2015.

    A survey on pseudonym changing strategies for Vehicular Ad-Hoc Networks

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    The initial phase of the deployment of Vehicular Ad-Hoc Networks (VANETs) has begun and many research challenges still need to be addressed. Location privacy continues to be in the top of these challenges. Indeed, both of academia and industry agreed to apply the pseudonym changing approach as a solution to protect the location privacy of VANETs'users. However, due to the pseudonyms linking attack, a simple changing of pseudonym shown to be inefficient to provide the required protection. For this reason, many pseudonym changing strategies have been suggested to provide an effective pseudonym changing. Unfortunately, the development of an effective pseudonym changing strategy for VANETs is still an open issue. In this paper, we present a comprehensive survey and classification of pseudonym changing strategies. We then discuss and compare them with respect to some relevant criteria. Finally, we highlight some current researches, and open issues and give some future directions

    Advancement in infotainment system in automotive sector with vehicular cloud network and current state of art

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    The automotive industry has been incorporating various technological advancement on top-end versions of the vehicle order to improvise the degree of comfortability as well as enhancing the safer driving system. Infotainment system is one such pivotal system which not only makes the vehicle smart but also offers abundance of information as well as entertainment to the driver and passenger. The capability to offer extensive relay of service through infotainment system is highly dependent on vehicular adhoc network as well as back end support of cloud environment. However, it is know that such legacy system of vehicular adhoc network is also characterized by various problems associated with channel capacity, latency, heterogeneous network processing, and many more. Therefore, this paper offers a comprehensive insight to the research work being carried out towards leveraging the infotainment system in order to obtain the true picture of strength, limitation, and open end problems associated with infotainment system

    The Impact of the Adversary's Eavesdropping Stations on the Location Privacy Level in Internet of Vehicles

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    The Internet of Vehicles (IoV) has got the interest of different research bodies as a promising technology. IoV is mainly developed to reduce the number of crashes by enabling vehicles to sense the environment and spread their locations to the neighborhood via safety-beacons to enhance the system functioning. Nevertheless, a bunch of security and privacy threats is looming; by exploiting the spatio-data included in these beacons. A lot of privacy schemes were developed to cope with the problem like CAPS, CPN, RSP, and SLOW. The schemes provide a certain level of location privacy yet the strength of the adversary, e.g., the number of eavesdropping stations has not been fully considered. In this paper, we aim at investigating the effect of the adversary’s eavesdropping stations number and position on the overall system functioning via privacy and QoS metrics. We also show the performances of these schemes in a manhattan-grid model which gives a comparison between the used schemes. The results show that both the number and the emplacement of the eavesdropping stations have a real negative impact on the achieved location privacy of the IoV users

    Towards a Framework for Preserving Privacy in VANET

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    Vehicular Ad-hoc Network (VANET) is envisioned as an integral part of the Intelligent Transportation Systems as it promises various services and benefits such as road safety, traffic efficiency, navigation and infotainment services. However, the security and privacy risks associated with the wireless communication are often overlooked. Messages exchanged in VANET wireless communication carry inferable Personally Identifiable Information(PII). This introduces several privacy threats that could limit the adoption of VANET. The quantification of these privacy threats is an active research area in VANET security and privacy domains. The Pseudonymisation technique is currently the most preferred solution for critical privacy threats in VANET to provide conditional anonymous authentication. In the existing literature, several Pseudonym Changing Schemes(PCS) have been proposed as effective de-identification approaches to prevent the inference of PII. However, for various reasons, none of the proposed schemes received public acceptance. Moreover, one of the open research challenges is to compare different PCSs under varying circumstances with a set of standardized experimenting parameters and consistent metrics. In this research, we propose a framework to assess the effectiveness of PCSs in VANET with a systematic approach. This comprehensive equitable framework consists of a variety of building blocks which are segmented into correlated sub-domains named Mobility Models, Adversary Models, and Privacy Metrics. Our research introduces a standard methodology to evaluate and compare VANET PCSs using a generic simulation setup to obtain optimal, realistic and most importantly, consistent results. This road map for the simulation setup aims to help the research \& development community to develop, assess and compare the PCS with standard set of parameters for proper analysis and reporting of new PCSs. The assessment of PCS should not only be equitable but also realistic and feasible. Therefore, the sub-domains of the framework need coherent as well as practically applicable characteristics. The Mobility Model is the layout of the traffic on the road which has varying features such as traffic density and traffic scenarios based on the geographical maps. A diverse range of Adversary Models is important for pragmatic evaluation of the PCSs which not only considers the presence of global passive adversary but also observes the effect of intelligent and strategic \u27local attacker\u27 placements. The biggest challenge in privacy measurement is the fact that it is a context-based evaluation. In the literature, the PCSs are evaluated using either user-oriented or adversary-oriented metrics. Under all circumstances, the PCSs should be assessed from both user and adversary perspectives. Using this framework, we determined that a local passive adversary can be strong based on the attacking capabilities. Therefore, we propose two intelligent adversary placements which help in privacy assessment with realistic adversary modelling. When the existing PCSs are assessed with our systematic approach, consistent models and metrics, we identified the privacy vulnerabilities and the limitations of existing PCSs. There was a need for comprehensive PCS which consider the context of the vehicles and the changing traffic patterns in the neighbourhood. Consequently, we developed a Context-Aware \& Traffic Based PCS that focuses on increasing the overall rate of confusion for the adversary and to reduce deterministic information regarding the pseudonym change. It is achieved by increasing the number of dynamic attributes in the proposed PCS for inference of the changing pattern of the pseudonyms. The PCS increases the anonymity of the vehicle by having the synchronized pseudonym changes. The details given under the sub-domains of the framework solidifies our findings to strengthen the privacy assessment of our proposed PCS

    Traceability and safety tradeoffs in modern vehicles

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    Dissertação de mestrado integrado em Engenharia InformáticaIn this dissertation, the efficiency of privacy protecting mechanisms in short-range vehicular communications, namely Pseudonym Change Strategies, is investigated. To evaluate these strategies, a set of simulation tools is used, that allow for the assessment of several metrics, such as the privacy level obtained and the real pseudonym consumption, resulting from the use of a representative set of pseudonym change strategies. Most importantly, hybrid strategies were considered, which combine schemes that were previously analysed separately. The results show that combining mix-zones with another scheme provides better privacy in most cases. Lastly, we showcase and analyse the problems found in the process of trying to make the simulated scenarios more realistic, which easily comes into conflict with tool limitations and/or subtle and hard to anticipate interactions between different components.Nesta dissertação investiga-se a eficácia de mecanismos de protecção da privacidade em comunicações veiculares de curto alcance, nomeadamente recorrendo a Estratégias de Alteração de Pseudónimos. Para a avaliação dessas estratégias, recorre-se a um conjunto de ferramentas de simulação que permitem aferir diferentes métricas, como o nível de privacidade obtido e o consumo efectivo de pseudónimos, decorrentes da utilização de um conjunto representativo de estratégias de alteração de pseudónimos. Mais importante ainda, foram consideradas estratégias híbridas, que combinam esquemas antes analisados separadamente. Os resultados mostram que combinar zonas mistas com outro esquema proporciona melhor privacidade na maioria dos casos. Por último, apresentam-se e analisam-se problemas encontrados no processo de procurar tornar mais realistas os cenários das simulações realizadas, e que facilmente esbarra com limitações das ferramentas e/ou interações subtis e dificilmente antecipáveis de diferentes componentes

    Secure and Authenticated Message Dissemination in Vehicular ad hoc Networks and an Incentive-Based Architecture for Vehicular Cloud

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    Vehicular ad hoc Networks (VANETs) allow vehicles to form a self-organized network. VANETs are likely to be widely deployed in the future, given the interest shown by industry in self-driving cars and satisfying their customers various interests. Problems related to Mobile ad hoc Networks (MANETs) such as routing, security, etc.have been extensively studied. Even though VANETs are special type of MANETs, solutions proposed for MANETs cannot be directly applied to VANETs because all problems related to MANETs have been studied for small networks. Moreover, in MANETs, nodes can move randomly. On the other hand, movement of nodes in VANETs are constrained to roads and the number of nodes in VANETs is large and covers typically large area. The following are the contributions of the thesis. Secure, authenticated, privacy preserving message dissemination in VANETs: When vehicles in VANET observe phenomena such as accidents, icy road condition, etc., they need to disseminate this information to vehicles in appropriate areas so the drivers of those vehicles can take appropriate action. When such messages are disseminated, the authenticity of the vehicles disseminating such messages should be verified while at the same time the anonymity of the vehicles should be preserved. Moreover, to punish the vehicles spreading malicious messages, authorities should be able to trace such messages to their senders when necessary. For this, we present an efficient protocol for the dissemination of authenticated messages. Incentive-based architecture for vehicular cloud: Due to the advantages such as exibility and availability, interest in cloud computing has gained lot of attention in recent years. Allowing vehicles in VANETs to store the collected information in the cloud would facilitate other vehicles to retrieve this information when they need. In this thesis, we present a secure incentive-based architecture for vehicular cloud. Our architecture allows vehicles to collect and store information in the cloud; it also provides a mechanism for rewarding vehicles that contributing to the cloud. Privacy preserving message dissemination in VANETs: Sometimes, it is sufficient to ensure the anonymity of the vehicles disseminating messages in VANETs. We present a privacy preserving message dissemination protocol for VANETs

    Virtual Pseudonym-Changing and Dynamic Grouping Policy for Privacy Preservation in VANETs

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    Location privacy is a critical problem in the vehicular communication networks. Vehicles broadcast their road status information to other entities in the network through beacon messages to inform other entities in the network. The beacon message content consists of the vehicle ID, speed, direction, position, and other information. An adversary could use vehicle identity and positioning information to determine vehicle driver behavior and identity at different visited location spots. A pseudonym can be used instead of the vehicle ID to help in the vehicle location privacy. These pseudonyms should be changed in appropriate way to produce uncertainty for any adversary attempting to identify a vehicle at different locations. In the existing research literature, pseudonyms are changed during silent mode between neighbors. However, the use of a short silent period and the visibility of pseudonyms of direct neighbors provides a mechanism for an adversary to determine the identity of a target vehicle at specific locations. Moreover, privacy is provided to the driver, only within the RSU range; outside it, there is no privacy protection. In this research, we address the problem of location privacy in a highway scenario, where vehicles are traveling at high speeds with diverse traffic density. We propose a Dynamic Grouping and Virtual Pseudonym-Changing (DGVP) scheme for vehicle location privacy. Dynamic groups are formed based on similar status vehicles and cooperatively change pseudonyms. In the case of low traffic density, we use a virtual pseudonym update process. We formally present the model and specify the scheme through High-Level Petri Nets (HLPN). The simulation results indicate that the proposed method improves the anonymity set size and entropy, provides lower traceability, reduces impact on vehicular network applications, and has lower computation cost compared to existing research work

    Towards a Reliable Machine Learning Based Global Misbehavior Detection in C-ITS: Model Evaluation Approach

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    International audienceGlobal misbehavior detection in Cooperative Intelligent Transport Systems (C-ITS) is carried out by a central entity named Misbe-havior Authority (MA). The detection is based on local misbehavior detection information sent by Vehicle's On-Board Units (OBUs) and by RoadSide Units (RSUs) called Misbehavior Reports (MBRs) to the MA. By analyzing these Misbehavior Reports (MBRs), the MA is able to compute various misbehavior detection information. In this work, we propose and evaluate different Machine Learning (ML) based solutions for the internal detection process of the MA. We show through extensive simulation and several detection metrics the ability of solutions to precisely identify different misbehavior types

    Internet of Vehicles: Motivation, Layered Architecture, Network Model, Challenges, and Future Aspects

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    © 2013 IEEE. Internet of Things is smartly changing various existing research areas into new themes, including smart health, smart home, smart industry, and smart transport. Relying on the basis of 'smart transport,' Internet of Vehicles (IoV) is evolving as a new theme of research and development from vehicular ad hoc networks (VANETs). This paper presents a comprehensive framework of IoV with emphasis on layered architecture, protocol stack, network model, challenges, and future aspects. Specifically, following the background on the evolution of VANETs and motivation on IoV an overview of IoV is presented as the heterogeneous vehicular networks. The IoV includes five types of vehicular communications, namely, vehicle-to-vehicle, vehicle-to-roadside, vehicle-to-infrastructure of cellular networks, vehicle-to-personal devices, and vehicle-to-sensors. A five layered architecture of IoV is proposed considering functionalities and representations of each layer. A protocol stack for the layered architecture is structured considering management, operational, and security planes. A network model of IoV is proposed based on the three network elements, including cloud, connection, and client. The benefits of the design and development of IoV are highlighted by performing a qualitative comparison between IoV and VANETs. Finally, the challenges ahead for realizing IoV are discussed and future aspects of IoV are envisioned
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