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

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

Context-based Pseudonym Changing Scheme for Vehicular Adhoc Networks

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.

Random delay techniques for location privacy in VANETs

Ankara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2013.Thesis (Master's) -- Bilkent University, 2013.Includes bibliographical references leaves 49-51.Vehicular ad hoc network (VANET) is an emerging new communication technology which has attracted a lot of research attention from academic community and industry. It is promising technology to provide safer and efficient traffic conditions. This is realized by letting vehicles to exchange safety messages. This messaging increases the awareness of vehicles about their neighboring vehicles positions and warns drivers about dangerous situations. However, availability of such information facilitates the tracking of vehicles. So, this information must be protected against the potential misuse. In this thesis, we address the problem of achieving location privacy in VANETs with randomly changing identifiers (i.e. pseudonyms) in the presence of a global passive adversary. We suggest adding a random delay to message broadcast period after the vehicle update its pseudonym in mix zones. By this way, we want to mitigate the linkability between pseudonyms. This could help to make tracking more difficult and increase safety and confidence of drivers using VANET. Instead of adding delay to safety messages completely random, one step taken further and delay is added according to the silent vehicle number in mix zone. We also investigated the effects of different number of mix-zone placements in the network to the location privacy of users. Several simulations have been performed to evaluate the performance of the systems. The results of experiments show that adding delay to message broadcast period improves location privacy of drivers in VANET and also provide information about the relationship between the strength of the adversary and the level of privacy achieved by changing pseudonyms.Albakır Çatal, SatiyeM.S

HPDM: A Hybrid Pseudonym Distribution Method for Vehicular Ad-hoc Networks

AbstractProtecting the location privacy of drivers is still one of the main challenges in Vehicular Ad-hoc Networks (VANETs). The changing of pseudonym is commonly accepted as a solution to this problem. The pseudonyms represent fake vehicle identifiers. Roadside Units (RSUs) play a central role in the existing pseudonyms distribution solutions. Indeed, the VANET area should totally be covered by RSUs in order to satisfy the demand of vehicles in terms of pseudonyms. However, the total coverage is costly and hard to be achieved, especially in the first phase of VANETs deployment. In addition, RSUs could be overloaded due to the large number of pseudonyms requests that could be received from vehicles. In this paper, we propose a new hybrid pseudonyms distribution method, called HPDM that relies not only on RSUs but also on vehicles to perform the pseudonyms distribution. The analysis demonstrate that HPDM is privacy and accountability preserving. The performance evaluation of the proposed method is carried out using veins framework based on OMNet++ network simulator and SUMO mobility engine and shows its feasibility

On the Optimal Placement of Mix Zones

In mobile wireless networks, third parties can track the location of mobile nodes by monitoring the pseudonyms used for identification. A frequently proposed solution to protect the location privacy of mobile nodes suggests to change pseudonyms in regions called mix zones. In this paper, we propose a novel metric based on the mobility profiles of mobile nodes to evaluate the mixing effectiveness of possible mix zone locations. Then, as the location privacy achieved with mix zones depends on their placement in the network, we analyze the optimal placement of mix zones with combinatorial optimization techniques. The proposed algorithm maximizes the achieved location privacy in the system and takes into account the cost on mobile nodes induced by mix zones. By means of simulations, we show that the placement recommended by our algorithm significantly reduces the tracking success by the adversary

Users Collaborative Mix-Zone to Resist the Query Content and Time Interval Correlation Attacks

In location-based services of continuous query, it is easier than snapshot to confirm whether a location belongs to a particular user, because sole location can be composed into a trajectory by profile correlation. In order to cut off the correlation and disturb the sub-trajectory, an un-detective region called mix-zone was proposed. However, at the time of this writing, the existing algorithms of this type mainly focus on the profiles of ID, passing time, transition probability, mobility patterns as well as road characteristics. In addition, there is still no standard way of coping with attacks of correlating each location by mining out query content and time interval from the sub-trajectory. To cope with such types of attack, users have to generalize their query contents and time intervals similarity. Hence, this paper first provided an attack model to simulate the adversary correlating the real location with a higher probability of query content and time interval similarity. Then a user collaboration mix-zone (CoMix) that can generalize these two types of profiles is proposed, so as to achieve location privacy. In CoMix, each user shares the common profile set to lowering the probability of success opponents to get the actual position through the correlation of location. Thirdly, entropy is utilized to measure the level of privacy preservation. At last, this paper further verifies the effectiveness and efficiency of the proposed algorithm by experimental evaluations

Security and Privacy Preservation in Vehicular Social Networks

Improving road safety and traffic efficiency has been a long-term endeavor for the government, automobile industry and academia. Recently, the U.S. Federal Communication Commission (FCC) has allocated a 75 MHz spectrum at 5.9 GHz for vehicular communications, opening a new door to combat the road fatalities by letting vehicles communicate to each other on the roads. Those communicating vehicles form a huge Ad Hoc Network, namely Vehicular Ad Hoc Network (VANET). In VANETs, a variety of applications ranging from the safety related (e.g. emergence report, collision warning) to the non-safety related (e.g., delay tolerant network, infortainment sharing) are enabled by vehicle-to-vehicle (V-2-V) and vehicle-to-roadside (V-2-I) communications. However, the flourish of VANETs still hinges on fully understanding and managing the challenging issues over which the public show concern, particularly, security and privacy preservation issues. If the traffic related messages are not authenticated and integrity-protected in VANETs, a single bogus and/or malicious message can potentially incur a terrible traffic accident. In addition, considering VANET is usually implemented in civilian scenarios where locations of vehicles are closely related to drivers, VANET cannot be widely accepted by the public if VANET discloses the privacy information of the drivers, i.e., identity privacy and location privacy. Therefore, security and privacy preservation must be well addressed prior to its wide acceptance. Over the past years, much research has been done on considering VANET's unique characteristics and addressed some security and privacy issues in VANETs; however, little of it has taken the social characteristics of VANET into consideration. In VANETs, vehicles are usually driven in a city environment, and thus we can envision that the mobility of vehicles directly reflects drivers' social preferences and daily tasks, for example, the places where they usually go for shopping or work. Due to these human factors in VANETs, not only the safety related applications but also the non-safety related applications will have some social characteristics. In this thesis, we emphasize VANET's social characteristics and introduce the concept of vehicular social network (VSN), where both the safety and non-safety related applications in VANETs are influenced by human factors including human mobility, human self-interest status, and human preferences. In particular, we carry on research on vehicular delay tolerant networks and infotainment sharing --- two important non-safety related applications of VSN, and address the challenging security and privacy issues related to them. The main contributions are, i) taking the human mobility into consideration, we first propose a novel social based privacy-preserving packet forwarding protocol, called SPRING, for vehicular delay tolerant network, which is characterized by deploying roadside units (RSUs) at high social intersections to assist in packet forwarding. With the help of high-social RSUs, the probability of packet drop is dramatically reduced and as a result high reliability of packet forwarding in vehicular delay tolerant network can be achieved. In addition, the SPRING protocol also achieves conditional privacy preservation and resist most attacks facing vehicular delay tolerant network, such as packet analysis attack, packet tracing attack, and black (grey) hole attacks. Furthermore, based on the ``Sacrificing the Plum Tree for the Peach Tree" --- one of the Thirty-Six Strategies of Ancient China, we also propose a socialspot-based packet forwarding (SPF) protocol for protecting receiver-location privacy, and present an effective pseudonyms changing at social spots strategy, called PCS, to facilitate vehicles to achieve high-level location privacy in vehicular social network; ii) to protect the human factor --- interest preference privacy in vehicular social networks, we propose an efficient privacy-preserving protocol, called FLIP, for vehicles to find like-mined ones on the road, which allows two vehicles sharing the common interest to identify each other and establish a shared session key, and at the same time, protects their interest privacy (IP) from other vehicles who do not share the same interest on the road. To generalize the FLIP protocol, we also propose a lightweight privacy-preserving scalar product computation (PPSPC) protocol, which, compared with the previously reported PPSPC protocols, is more efficient in terms of computation and communication overheads; and iii) to deal with the human factor -- self-interest issue in vehicular delay tolerant network, we propose a practical incentive protocol, called Pi, to stimulate self-interest vehicles to cooperate in forwarding bundle packets. Through the adoption of the proper incentive policies, the proposed Pi protocol can not only improve the whole vehicle delay tolerant network's performance in terms of high delivery ratio and low average delay, but also achieve the fairness among vehicles. The research results of the thesis should be useful to the implementation of secure and privacy-preserving vehicular social networks

Towards a Framework for Preserving Privacy in VANET

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

Optimizing Mixing in Pervasive Networks: A Graph-Theoretic Perspective

One major concern in pervasive wireless applications is location privacy, where malicious eavesdroppers, based on static device identifiers, can continuously track users. As a commonly adopted countermeasure to prevent such identifier-based tracking, devices regularly and simultaneously change their identifiers in special areas called mix-zones. Although mix-zones provide spatio-temporal de-correlations between old and new identifiers, pseudonym changes, depending on the position of the mix-zone, can incur a substantial cost on the network due to lost communications and additional resources such as energy. In this paper, we address this trade-off by studying the problem of determining an optimal set of mix-zones such that the degree of mixing in the network is maximized, whereas the overall network-wide mixing cost is minimized. We follow a graph-theoretic approach and model the optimal mixing problem as a novel generalization of the vertex cover problem, called the Mix Cover (MC) problem. We propose three bounded-ratio approximation algorithms for the MC problem and validate them by an empirical evaluation of their performance on real data. The combinatorics-based approach followed here enables us to study the feasibility of determining optimal mix-zones regularly and under dynamic network conditions