  Secure message dissemination is an important issue in vehicular networks,
especially considering the vulnerability of vehicle to vehicle message
dissemination to malicious attacks. Traditional security mechanisms, largely
based on message encryption and key management, can only guarantee secure
message exchanges between known source and destination pairs. In vehicular
networks however, every vehicle may learn its surrounding environment and
contributes as a source, while in the meantime act as a destination or a relay
of information from other vehicles, message exchanges often occur between
"stranger" vehicles. For secure message dissemination in vehicular networks
against insider attackers, who may tamper the content of the disseminated
messages, ensuring the consistency and integrity of the transmitted messages
becomes a major concern that traditional message encryption and key management
based approaches fall short to provide. In this paper, by incorporating the
underlying network topology information, we propose an optimal decision
algorithm that is able to maximize the chance of making a correct decision on
the message content, assuming the prior knowledge of the percentage of
malicious vehicles in the network. Furthermore, a novel heuristic decision
algorithm is proposed that can make decisions without the aforementioned
knowledge of the percentage of malicious vehicles. Simulations are conducted to
compare the security performance achieved by our proposed decision algorithms
with that achieved by existing ones that do not consider or only partially
consider the topological information, to verify the effectiveness of the
algorithms. Our results show that by incorporating the network topology
information, the security performance can be much improved. This work shed
light on the optimum algorithm design for secure message dissemination.
