A Blockchain-based Quantum Binary Voting for Decentralized IoT Towards Industry 5.0

TL;DR

The paper tackles secure consensus in decentralized IoT for Industry 5.0 by introducing a quantum binary voting protocol on a quantum blockchain. It combines cheat-sensitive quantum bit commitment (CSQBC) with quantum Byzantine agreement (QBA) to enable masked ballots to be prepared, committed, and decommitted, followed by a quantum consensus among miners using entangled Aharonov states. The approach is analyzed for security against internal and external threats and demonstrated through simulations on IBMQ and SimulaQron, showing viable performance with current hardware in principle and outlining the necessary qubit resources. The work advances practical quantum-secured IoT governance, highlighting a pathway toward tamper-resistant, verifiable, and self-tallying consensus mechanisms for Industry 5.0 deployments.

Abstract

Industry 5.0 depends on intelligence, automation, and hyperconnectivity operations for effective and sustainable human-machine collaboration. Pivotal technologies like the Internet of Things (IoT) enable this by facilitating connectivity and data-driven decision-making between cyber-physical devices. As IoT devices are prone to cyberattacks, they can use blockchain to improve transparency in the network and prevent data tampering. However, in some cases, even blockchain networks are vulnerable to Sybil and 51% attacks. This has motivated the development of quantum blockchains that are more resilient to such attacks as they leverage post-quantum cryptographic protocols and secure quantum communication channels. In this work, we develop a quantum binary voting algorithm for the IoT-quantum blockchain frameworks that enables inter-connected devices to reach a consensus on the validity of transactions, even in the presence of potential faults or malicious actors. The correctness of the voting protocol is provided in detail, and the results show that it guarantees the achievement of a consensus securely against all kinds of significant external and internal attacks concerning quantum bit commitment, quantum blockchain, and quantum Byzantine agreement. We also provide an implementation of the voting algorithm with the quantum circuits simulated on the IBM Quantum platform and Simulaqron library.

Figures (5)

• Figure 1: The system model of our blockchain-based quantum binary voting in a decentralized IoT. In our context, the protocol will have six components: (i) an IoT environment, which constitutes all the interconnected devices, (ii) an election preparation service (EPS), which authenticates and verifies devices as voters and maintains a voter list, (iii) voting environment, which constitutes all those devices that are authenticated and registered as voters (${V}$) by EPS, (iv) consensus environment, which constitutes of miners (${M}$) who take the masked ballots and reach a consensus on the result (v) the quantum-secure communication gateway which connects the voting and consensus environment, and (vi) an independent auditor, which can scrutinize the voting process for any complacency. The voters communicate with each other to prepare their masked ballots and then commit them to the miners residing on the same or different quantum blockchain. Then, miners authenticate the voters and their masked ballots via QKD protocol. Finally, on successful verification, they reach a consensus on the masked ballots via the quantum Byzantine agreement (QBA) protocol.
• Figure 2: An example of preparing a vote matrix $V$ and masked ballots $\hat{v}_i$ for $N=3$ voters.
• Figure 3: (a) State preparation circuit for the Aharonov state $\ket{A}$. When decomposed into the basis gates $[U, \text{CNOT}]$ supported by IBM quantum hardware, the depth of the circuit would be $146$, and it would use $97$ single-qubit $U$ gates and $83$ two-qubit $\text{CNOT}$ gates. (b) The probability distribution of the state prepared by the circuit on a noiseless device.
• Figure 4: (a) Probability of success for committing the right bit via CSQBC protocol is plotted against $n$, i.e., the number of qubits required to generate the sequence QS, for different bitstrings. (b) Fidelity of $\ket{{A}}$ states prepared in different IBMQ backends with respect to $\ket{{A}}$ state prepared via an ideal noise-less simulation. Here, we have used noise models from different hardware backends for our simulations.
• Figure 5: The probability of (a) detectable and (b) successful broadcasts increases with an increment in the number of Aharonov states $\ket{{A}}$ that have been distributed within the miners ${M}$, even if there are complicit miner(s), for any sufficient agreement probability $\lambda\geq0.9$. Here, the parameter $\gamma$ represents that complicit behaviour exhibited in the miner within the blockchain system in any iteration, where: (i) $\gamma=0$, any of the three miners is complicit at random and (ii) $\gamma =i\neq0$, only miner M$_{i}$ is always complicit.