Secure Data Provenance in Internet of Things based Networks by Outsourcing Attribute based Signatures and using Bloom Filters

Abstract

With the dawn of autonomous organization and network and service management, the integration of existing networks with Internet of Things (IoT) based networks is becoming a reality. With minimal human interaction, the security of IoT data moving through the network becomes prone to attacks. IoT networks require a secure provenance mechanism, which is efficient and lightweight because of the scarce computing and storage resources at the IoT nodes. In this paper, we have proposed a secure mechanism to sign and authenticate provenance messages using Ciphertext-Policy Attribute Based Encryption (CP-ABE) based signatures. The proposed technique uses Bloom filters to reduce storage requirements and an outsourced ABE mechanism to use lessen the computational requirements at the IoT devices. The proposed technique helps in reducing the storage requirements and computation 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.

BlockTrack-L: A Lightweight Blockchain-based Provenance Message Tracking in IoT

“…The blockchain provides an immutable record of each communication performed inside the cloud based IoT network; however, as the hash is stored on a permissioned blockchain, the IoT nodes is required to be authenticated to maintain the data integrity. This section provides the details of the outsourced signature-based mechanism used to provide authentication and data integrity, which is suitable for IoT devices as it offloads the computational load [2].…”

“…4 shows the conceptual model of implementing the CP-ABE in IoT based Cloud environment. The details of the algorithm can be seen in our previous work [2], where the authors have implemented the load sharing of cryptographical computation by outsourcing the signing and signature verification to the Edge nodes.…”

“…Data provenance has been examined in many areas for various purposes, such as, copyright of an artistic work, intellectual property, scientific contribution tracking, regulatory and legal considerations etc. Similarly, data tracking is of great significance and a central part in digital forensics [2]. HealthCare has an essential aspect to trace patient records for any kind of conflict resolution [3].…”

“…Apart from that, provenance of data/messages has also been studied in databases [6], cloud computing, wireless sensor networks etc. [2]. In fact, message provenance of IoT devices communication on the blockchain network is still an open area of research.…”

“…This is normally achieved through encryption techniques, which again have a high computational load. In our previous work [2], we have devised a light-weight encryption mechanism which can calculate attribute-based signature by outsourcing encryption load to the Edge node instead of the IoT node, thus significantly reducing the computational load and providing better security services.…”