Adjusted Location Privacy Scheme in VANET Safety Applications

The primary aim of Vehicular Ad hoc NETworks (VANET) is to enhance traffic safety by enabling frequent broadcasting of location information between vehicles. In VANET safety applications, a vehicle requires to broadcast messages, which usually contain its location information, every (1-10 Hz) with other vehicles in its communication area (300m) to facilitate cooperative awareness. This would arise privacy issues because vehicles are vulnerable to tracking attacks via their locations. To prevent long-term linking, many privacy schemes have adopted a silent period in which a vehicle stops sharing its locations for a period. However, silent periods could have a negative impact on safety applications as an accident could have happened if a vehicle stop sharing its locations with other neighbours. Thus, in this paper, we first discuss three privacy schemes (RSP, SLOW and CAPS), which adopted silent periods but in different concepts. Then, we improve the privacy and safety level of CAPS. A privacy simulator PREXT is used to evaluate and compare the performance of schemes

Data-centric Misbehavior Detection in VANETs

Detecting misbehavior (such as transmissions of false information) in vehicular ad hoc networks (VANETs) is very important problem with wide range of implications including safety related and congestion avoidance applications. We discuss several limitations of existing misbehavior detection schemes (MDS) designed for VANETs. Most MDS are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners, e.g. for gaining access to a particular lane. Because of this (\emph{rational behavior}), it is more important to detect false information than to identify misbehaving nodes. We introduce the concept of data-centric misbehavior detection and propose algorithms which detect false alert messages and misbehaving nodes by observing their actions after sending out the alert messages. With the data-centric MDS, each node can independently decide whether an information received is correct or false. The decision is based on the consistency of recent messages and new alert with reported and estimated vehicle positions. No voting or majority decisions is needed, making our MDS resilient to Sybil attacks. Instead of revoking all the secret credentials of misbehaving nodes, as done in most schemes, we impose fines on misbehaving nodes (administered by the certification authority), discouraging them to act selfishly. This reduces the computation and communication costs involved in revoking all the secret credentials of misbehaving nodes.Comment: 12 page

Coherent, automatic address resolution for vehicular ad hoc networks

Published in: Int. J. of Ad Hoc and Ubiquitous Computing, 2017 Vol.25, No.3, pp.163 - 179. DOI: 10.1504/IJAHUC.2017.10001935The interest in vehicular communications has increased notably. In this paper, the use of the address resolution (AR) procedures is studied for vehicular ad hoc networks (VANETs). We analyse the poor performance of AR transactions in such networks and we present a new proposal called coherent, automatic address resolution (CAAR). Our approach inhibits the use of AR transactions and instead increases the usefulness of routing signalling to automatically match the IP and MAC addresses. Through extensive simulations in realistic VANET scenarios using the Estinet simulator, we compare our proposal CAAR to classical AR and to another of our proposals that enhances AR for mobile wireless networks, called AR+. In addition, we present a performance evaluation of the behaviour of CAAR, AR and AR+ with unicast traffic of a reporting service for VANETs. Results show that CAAR outperforms the other two solutions in terms of packet losses and furthermore, it does not introduce additional overhead.Postprint (published version

Routing and Applications of Vehicular Named Data Networking

Vehicular Ad hoc NETwork (VANET) allows vehicles to exchange important informationamong themselves and has become a critical component for enabling smart transportation.In VANET, vehicles are more interested in content itself than from which vehicle the contentis originated. Named Data Networking (NDN) is an Internet architecture that concentrateson what the content is rather than where the content is located. We adopt NDN as theunderlying communication paradigm for VANET because it can better address a plethora ofproblems in VANET, such as frequent disconnections and fast mobility of vehicles. However,vehicular named data networking faces the problem of how to efficiently route interestpackets and data packets. To address the problem, we propose a new geographic routing strategy of applying NDNin vehicular networks with Delay Tolerant Networking (DTN) support, called GeoDTN-NDN. We designed a hybrid routing mechanism for solving the flooding issue of forwardinginterest packets and the disruption problem of delivering data packets. To avoid disruptionscaused by routing packets over less-traveled roads, we develop a new progressive segmentrouting approach that takes into consideration how vehicles are distributed among differentroads, with the goal of favoring well-traveled roads. A novel criterion for determiningprogress of routing is designed to guarantee that the destination will be reached no matterwhether a temporary loop may be formed in the path. We also investigate applications of vehicular named data networking. We categorizethese applications into four types and design an NDN naming scheme for them. We proposea fog-computing based architecture to support the smart parking application, which enablesa driver to find a parking lot with available parking space and make reservation for futureparking need. Finally we describe several future research directions for vehicular nameddata networking

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

Modeling Adversarial Insider Vehicles in Mix Zones

Security is a necessity when dealing with new forms of technology that may not have been analyzed from a security perspective. One of the latest growing technological advances are Vehicular Ad-Hoc Networks (VANETs). VANETs allow vehicles to communicate information to each other wirelessly which allows for an increase in safety and efficiency for vehicles. However, with this new type of computerized system comes the need to maintain security on top of it. In order to try to protect location privacy of the vehicles in the system, vehicles change pseudonyms or identifiers at areas known as mix zones. This thesis implements a model that characterizes the attack surface of an adversarial insider vehicle inside of a VANET. This adversarial vehicle model describes the interactions and effects that an attacker vehicle can have on mix zones in order to lower the overall location privacy of the system and remain undetected to defenders in the network. In order to reach the final simulation of the model, several underlying models had to be developed around the interactions of defender and attacker vehicles. The evaluation of this model shows that there are significant impacts that internal attacker vehicles can have on location privacy within mix zones. From the created simulations, the results show that having one to five optimal attackers shows a decrease of 0.6%-2.6% on the location privacy of the network and a 12% decrease in potential location privacy in a mix zone where an attacker defects in a 50-node network. The industry needs to consider implementing defenses based on this particular attack surface discussed

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

MLAS: Multiple level authentication scheme for VANETs

The vehicular ad hoc network (VANET) is an emerging type of network which enables vehicles on roads to inter-communicate for driving safety. The basic idea is to allow arbitrary vehicles to broadcast ad hoc messages (e.g. traffic accidents) to other vehicles. However, this raises the concern of security and privacy. Messages should be signed and verified before they are trusted while the real identity of vehicles should not be revealed, but traceable by authorized party. Existing solutions either rely too heavily on a tamper-proof hardware device, or do not have an effective message verification scheme. In this paper, we propose a multiple level authentication scheme which still makes use of tamper-proof devices but the strong assumption that a long-term system master secret is preloaded into all tamper-proof devices is removed. Instead the master secret can be updated if needed to increase the security level. On the other hand, messages sent by vehicles are classified into two types - regular messages and urgent messages. Regular messages can be verified by neighboring vehicles by means of Hash-based Message Authentication Code (HMAC) while urgent messages can only be verified with the aid of RSUs nearby by means of a conditional privacy-preserving authentication scheme. Copyright 2011 ACM.postprintThe 6th ACM Symposium on Information, Computer and Communications Security (ASIACCS 2011), Hong Kong, China, 22-24 March 2011. In Proceedings of 6th ACM ASIACCS, 2011, p. 471-47