ASIA: Accelerated secure in-network aggregation in vehicular sensing networks

Abstract

Abstract-Vehicular Ad-Hoc Networks (VANETs) can potentially become a sensing platform. In-network aggregation, a fundamental primitive for querying sensory data, has been shown to reduce overall communication overhead at large. To secure data aggregation in VANETs, existing schemes mainly rely on digital signatures. However, generating and verifying such signatures can cause high computational overhead. More importantly, timeconsuming verifications lead to the vulnerability to signature flooding attacks in which a receiver cannot timely verify all messages before their respective deadlines. In this paper, we propose ASIA as an Accelerated Secure In-network Aggregation strategy that can accelerate message verifications and significantly reduce computational overhead while retaining satisfactory security. We replace the most common tree graph with a directed acyclic graph as the aggregation structure. Resulting redundancy in information flow offers the opportunity for misbehavior detection. Meanwhile, by leveraging time asymmetry, upstream nodes in the structure can verify downstream messages through the modified light-weight TESLA scheme. We analyze the security properties of ASIA and provide evaluation results. We show that ASIA can largely accelerate message verifications and drastically reduce computational and communication overhead compared to existing schemes using the resource-consuming Elliptic Curve Digital Signature Algorithm.