Mesh: A Supply Chain Solution with Locally Private Blockchain Transactions

Abstract

A major line of research on blockchains is geared towards enhancing the privacy of transactions through anonymity using generic non-interactive proofs. However, there is a good cluster of application scenarios where complete anonymity is not desirable and accountability is in fact required. In this work, we utilize non-interactive proofs of knowledge of elliptic curve discrete logarithms to present membership and verifiable encryption proof, which offers plausible anonymity when combined with the regular signing process of the blockchain transactions. The proof system requires no trusted setup, both its communication and computation complexities are linear in the number of set members, and its security relies on the discrete logarithm assumption. As a use-case for this scenario, we present Mesh which is a blockchain-based framework for supply chain management using RFIDs. Finally, the confidentiality of the transacted information is realized using a lightweight key chaining mechanism implemented on RFIDs. We formally define and prove the main security features of the protocol, and report on experiments for evaluating the performance of the modified transactions for this system.

Black-Box IoT: Authentication and Distributed Storage of IoT Data from Constrained Sensors

“…More recently, AlTawy and Gong [5] presented a blockchainbased framework in the supply chain setting using RFIDs. This model considered blockchain smart contracts interacting with an overlay application on the RFID readers and a centralized server that handles membership credentials.…”

“…5 (iii) Stores ℓ = 1 to st S ij where ℓ denotes the current "index" in the hash chain. (iv) Creates a physical identity proof 𝜋 (v) Sends (𝜋, pk S ij ) to LAdm i (b) LAdm i checks Vrfy(𝜋) ∧ (pk S ij ∉ SL) ∧AggrUpd(sk LAdm i , pk S ij ) == 1 ∀Ag ij ∈ G i .…”

“…LAdm i should run the protocol with every aggregator in the group, however we present this with one aggregator for simplicity 5. This step is typically computed by a powerful device 6.…”