Smart grids face emerging threats as connectivity expands attack surfaces. To strengthen smart meter data encryption through optimized integration of a cloud-based quantum random number generator (QRNG) service. QRNGs leverage intrinsic quantum properties to produce true randomness for cryptographic keys. An architecture is presented utilizing a QRNG service on the IBM quantum computing platform. Quantum entropy is remotely sampled and delivered on-demand via APIs to generate quantum random AES encryption keys for smart meter communications. Homomorphic encryption secures credential transmission. Compared to mathematical pseudorandom number generators, the quantum origin provides stronger security against brute force attacks and future quantum computing decryption. Tailoring QRNG generation and integration focuses on the performance, cost, and deployment constraints of grid-wide encryption hardening. The optimized approach aims to maximize randomness while minimizing complexity. By hardening cryptography via readily available quantum key generation, the QRNG integration delivers indispensable security enhancement.
Smart grids face emerging threats as connectivity expands attack surfaces. To strengthen smart meter data encryption through optimized integration of a cloud-based quantum random number generator (QRNG) service. QRNGs leverage intrinsic quantum properties to produce true randomness for cryptographic keys. An architecture is presented utilizing a QRNG service on the IBM quantum computing platform. Quantum entropy is remotely sampled and delivered on-demand via APIs to generate quantum random AES encryption keys for smart meter communications. Homomorphic encryption secures credential transmission. Compared to mathematical pseudorandom number generators, the quantum origin provides stronger security against brute force attacks and future quantum computing decryption. Tailoring QRNG generation and integration focuses on the performance, cost, and deployment constraints of grid-wide encryption hardening. The optimized approach aims to maximize randomness while minimizing complexity. By hardening cryptography via readily available quantum key generation, the QRNG integration delivers indispensable security enhancement.
The vast amounts of data and the growing number of attacks in the smart grids (SGs) are consequences of the huge reliance on information and communication technology, that is further posing serious risks to the confidentiality and integrity of the power data. On the other hand, recent advancements in quantum cryptography are emerging as foundation for secure communication protocols, offering robust defenses against potential cyber threats in SGs. In response to the imperative challenge of secure data transmission, a quantum cryptography based unconditionally secure data transmission model is proposed that integrates quantum key distribution (QKD) with classical encryption. Furthermore, truly random encryption keys generated through quantum random number generator (QRNG) are utilized that assists to overcome the limitations of pseudo-random number generator and leads to the highly immune data security mechanism. The efficacy of proposed model is evaluated through experimental results obtained over classical simulator along with real quantum computers accessed through the IBM Qiskit platform. The statistical analysis conducted on the resulting quantum states showcases a high degree of accurate measurements, thereby confirming the relevance of the proposed work.
The rise of the smart grid, which applies the Internet and smart metering technologies to the power system, results in massive, heterogeneous power data and a large number of attacks on the smart grid and causes great threats to the confidentiality and integrity of the power data. At the same time, with the development of quantum information, it is possible to use quantum cryptography to protect data transmission. Aiming at the problem of data security transmission in smart grid, this paper proposes a lightweight transmission scheme for power data security. In the scheme, we combine quantum cryptography with ”one-time pad” mechanism, use a quantum random number generator which compensates the defects of the traditional random number generator and quantum key distribution protocol which ensure the security of key distribution, and design a new lightweight stream cipher encryption algorithm. Through theoretical analysis and experiments, it is proved that the proposed transmission scheme can ensure the security of power data transmission.
Randomness is essential in cryptography for key generation and secure information exchange, ensuring confidentiality and protection. Quantum Random Number Generators (QRNGs) leverage quantum mechanics to produce truly random numbers, offering a major advantage over Pseudo Random Number Generators (PRNGs), which are slower and less secure due to their deterministic nature. Quantum computing boosts QRNG efficiency, making them ideal for cryptographic applications, such as secure key exchange and encrypted communication. QRNGs generate stronger encryption systems by utilizing quantum phenomena like Bloch sphere rotations. The integration of machine learning (ML) with QRNGs further enhances their effectiveness, optimizing random sequences for improved speed and security. This combination of QRNGs and ML provides a powerful approach to cryptography, ensuring more secure communication channels and better protection against potential attacks.
The security landscape will change dramatically with the advent of quantum computers and existing security schemes in various domains including smart grid communications must be updated to make them secure from quantum computer-enabled attacks. In this paper, we propose a quantum-safe mutual authentication protocol, leveraging the concepts of Quantum Key Distribution (QKD) and Quantum Random Number Generator (QRNG), for secure communication between smart meters and a server. Unlike conventional schemes based on cryptographic algorithms that rely on difficulties to solve certain mathematical problems, the proposed protocol is secure against attacks arising from quantum computers. In the proposed protocol, QKD is employed to establish secure keys in smart meter communications with provable security while QRNG provides truly random numbers that are unknown to any eavesdropper. Specifically, we employ the Measurement-Device-Independent Quantum Key Distribution (MDI QKD), a type of QKD whose security does not rely on any assumptions about measurement devices. We provide a formal security proof for the proposed scheme under the real-or-random (RoR) model. Additionally, we conduct a proof-of-concept experimental demonstration, using the secure keys from a MDI QKD system and random numbers from QRNG, to demonstrate the feasibility and practicality of the proposed scheme.
The IoT Smart grid systems require privacy-sensitive, scalable, and secure communication, but the traditional cryptographic methods are susceptible to quantum attacks, central failure, and high computational costs. In this paper, the author presents a multi-layered structure that uses various yet complementary approaches in order to solve these issues. Quantum Key Distribution (QKD) is applied to create quantum-resilient key management to provide the secure transmission against future quantum attacks. Homomorphic Encryption (HE) allows the computations to be performed on encrypted data to preserve privacy and minimize the risks of exposure at some point during the processing. Federated Learning (FL) is used to assist the decentralized intelligence, where anomaly detection models are trained together without the need of transferring sensitive raw data. The combination of the two techniques produces a hybrid architecture that is both highly secure and scalable. Experimental validation on real-world smart grid data indicates the 42% communication overhead reduction versus traditional encryption, a 35% improvement in anomaly detection with FL and strong resistance to quantum attack and side-channel attack simulation. The findings support the fact the suggested solution provides end-to-end confidentiality, integrity, and performance efficiency, which will form a basis of quantum-resilience and privacy-preserving communication in future smart grid IoT network.
Robust security is vital in cloud computing due to the proliferation of sensitive data. This paper presents an innovative quantum-based security framework to address emerging threats. Measurement-Device-Independent Quantum Key Distribution (MDI-QKD) enhances data transmission security by establishing unhackable channels through quantum entanglement, ensuring data integrity. Quantum Homomorphic Encryption (QHE) enables secure computations on encrypted data, ensuring confidentiality during storage. The Quantum Secure Storage and Management Communication (QSSMC) protocol ensures end-to-end privacy and prevents unauthorized access throughout the cloud data lifecycle. Additionally, Quantum Random Number Generation (QRNG) leverages quantum uncertainty to generate truly random numbers, mitigating the risks of pseudo-randomness and strengthening cryptographic applications. By integrating MDI-QKD, QHE, QSSMC, and QRNG, this framework provides robust security, confidentiality, and data integrity. Implemented in Python with a scalability rate of 95%, it offers a comprehensive solution for modern cloud computing challenges.