Secure Data Provenance in IoT Network using Bloom Filters

Abstract

Internet of Things (IoT) network are considered the future in monitoring and surveillance. With the advent of autonomous organization, and network and service management, conventional networks are fast integrated with IoT networks. With minimal human interaction, the security of IoT data travelling through the networks becomes more critical. Data Provenance ensures the path through which data was received for providing integrity and confidence. However, the provenance frameworks are also prone to attacks, as the attacker can manipulate the data and the meta-date used by the provenance mechanism. Therefore, a secure provenance mechanism is required for IoT networks, which is efficient and light-weight as the IoT devices have limited computational and storage resources. In this paper, we propose a secure provenance mechanism which utilizes less storage, specifically designed for IoT devices, by using Bloom-filters and outsourcing attribute based cryptographic mechanisms. The proposed scheme helps in reducing the storage requirement and computational time in IoT devices. The performance of the proposed mechanism is evaluated, and the results show that the proposed solution is best suited for resourced constrained IoT network.