Aggregate in my way: Privacy-preserving data aggregation without trusted authority in ICN

Abstract Information-Centric Networking (ICN) is a novel future network architecture which in contrast to IP-based networks relies on content and its name. It separates the physical location of data from the discovery and forwarding process and solely relies on the content itself. For the Internet of Thing (IoT) networks, stripping the location information may provide privacy, but this does not translate to operational privacy. Attackers can infer user behavior patterns through operational privacy, by eavesdropping on meaningful information. The content name and designed signature in ICN can associate content with the identity of the provider, even if the IP address is hidden. Although several research efforts focus on the privacy protection of ICN, they do not consider the privacy implications of data aggregation. Most existing privacy-preserving data aggregation protocols are designed for special operations, such as sum, average, variance, max or min, and they cannot support arbitrary aggregation operations in the ciphertexts domain. Besides, the need for trusted authority (TA) restricts the use of existing protocols in the real world. In this paper, we propose a practical and privacy-preserving data aggregation scheme that can compute arbitrary aggregation functions without a TA. On one hand, our scheme can ensure users’ anonymity and privacy protection, while on the other, the scheme is efficient in enabling participants to join or leave the system dynamically. Security analysis shows that the proposed scheme can achieve the desired security properties, while experimental results demonstrate its effectiveness and efficiency.