8,413 research outputs found
Security Analysis of Vehicular Ad Hoc Networks (VANET)
Vehicular Ad Hoc Networks (VANET) has mostly gained the attention of today's
research efforts, while current solutions to achieve secure VANET, to protect
the network from adversary and attacks still not enough, trying to reach a
satisfactory level, for the driver and manufacturer to achieve safety of life
and infotainment. The need for a robust VANET networks is strongly dependent on
their security and privacy features, which will be discussed in this paper. In
this paper a various types of security problems and challenges of VANET been
analyzed and discussed; we also discuss a set of solutions presented to solve
these challenges and problems.Comment: 6 pages; 2010 Second International Conference on Network
Applications, Protocols and Service
A Contribution to Secure the Routing Protocol "Greedy Perimeter Stateless Routing" Using a Symmetric Signature-Based AES and MD5 Hash
This work presents a contribution to secure the routing protocol GPSR (Greedy
Perimeter Stateless Routing) for vehicular ad hoc networks, we examine the
possible attacks against GPSR and security solutions proposed by different
research teams working on ad hoc network security. Then, we propose a solution
to secure GPSR packet by adding a digital signature based on symmetric
cryptography generated using the AES algorithm and the MD5 hash function more
suited to a mobile environment
Flexible Authentication in Vehicular Ad hoc Networks
A Vehicular Ad-Hoc Network (VANET) is a form of Mobile ad-hoc network, to
provide communications among nearby vehicles and between vehicles and nearby
fixed roadside equipment. The key operation in VANETs is the broadcast of
messages. Consequently, the vehicles need to make sure that the information has
been sent by an authentic node in the network. VANETs present unique challenges
such as high node mobility, real-time constraints, scalability, gradual
deployment and privacy. No existent technique addresses all these requirements.
In particular, both inter-vehicle and vehicle-to-roadside wireless
communications present different characteristics that should be taken into
account when defining node authentication services. That is exactly what is
done in this paper, where the features of inter-vehicle and vehicle-to-roadside
communications are analyzed to propose differentiated services for node
authentication, according to privacy and efficiency needs
Formal Analysis of V2X Revocation Protocols
Research on vehicular networking (V2X) security has produced a range of
security mechanisms and protocols tailored for this domain, addressing both
security and privacy. Typically, the security analysis of these proposals has
largely been informal. However, formal analysis can be used to expose flaws and
ultimately provide a higher level of assurance in the protocols.
This paper focusses on the formal analysis of a particular element of
security mechanisms for V2X found in many proposals: the revocation of
malicious or misbehaving vehicles from the V2X system by invalidating their
credentials. This revocation needs to be performed in an unlinkable way for
vehicle privacy even in the context of vehicles regularly changing their
pseudonyms. The REWIRE scheme by Forster et al. and its subschemes BASIC and
RTOKEN aim to solve this challenge by means of cryptographic solutions and
trusted hardware.
Formal analysis using the TAMARIN prover identifies two flaws with some of
the functional correctness and authentication properties in these schemes. We
then propose Obscure Token (OTOKEN), an extension of REWIRE to enable
revocation in a privacy preserving manner. Our approach addresses the
functional and authentication properties by introducing an additional key-pair,
which offers a stronger and verifiable guarantee of successful revocation of
vehicles without resolving the long-term identity. Moreover OTOKEN is the first
V2X revocation protocol to be co-designed with a formal model.Comment: 16 pages, 4 figure
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
MARINE: Man-in-the-middle attack resistant trust model IN connEcted vehicles
Vehicular Ad-hoc NETwork (VANET), a novel technology holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as Man-in-the-Middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate and trusted content within the network. In this paper, we propose a novel trust model, namely, Man-in-the-middle Attack Resistance trust model IN connEcted vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multi-dimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data is then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the bench-marked trust model. Simulation results show that for a network containing 35% MiTM attackers, MARINE outperforms the state of the art trust model by 15%, 18%, and 17% improvements in precision, recall and F-score, respectively.N/A
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