Lightweight Quantum Encryption for Secure Transmission of Power Data in Smart Grid
Open accessAbstract
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.
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Deployment of ANNs in communication networks is not new; ANNs have been deployed to perform and assist in various operations of communication systems.
“Deployment of ANNs in communication networks is not a new idea, instead, ANNs have been deployed to perform and assist in various operations of communication systems; e.g., ANN is proposed for symbol decoding for MIMO-OFDM systems in [74].”
From Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future (2019) · cites this paper as [74]
The Introduction and the section on quantum cryptography for smart grids discuss secure power-data communication, not ANN deployment. A search of our copy for ANN-based MIMO-OFDM symbol decoding found no passage addressing the cited example; the available passages therefore cannot verify the attribution. (LLM, conf=0.76)
Experimental — accuracy not yet measuredThe available information of transmitted training/pilot symbols and corresponding received symbols at the physical layer can be paired together to supervise learning of ANNs for symbol decoding.
“The available information of transmitted (training/pilot symbols) and the corresponding received symbols at the physical layer of a communication system can be paired together to supervise the learning of ANNs for symbol decoding [74].”
From Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future (2019) · cites this paper as [74]
The Communication Phase section describes a stream cipher, while the Preparation Phase describes quantum key generation and distribution. Searches for training or pilot symbols, received-symbol pairs, ANNs, and symbol decoding found no passage addressing supervised learning for decoding. (LLM, conf=0.74)
Experimental — accuracy not yet measuredA bank of ANNs is proposed for symbol decoding in MIMO-OFDM systems.
“A bank of ANNs is proposed for symbol decoding in MIMO-OFDM systems in [74].”
From Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future (2019) · cites this paper as [74]
The Introduction describes a lightweight quantum-cryptography scheme for transmitting smart-grid power data, and the cryptographic-algorithm section describes a stream cipher. Searches for a bank of ANNs, symbol decoding, and MIMO-OFDM found no passage addressing the attributed proposal in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measured
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Cited by
Sorted by citations
Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future
Nawaz, S. J., Sharma, S. K., Wyne, S., Patwary, M. N., & Asaduzzaman, M. (2019) · IEEE Access · doi:10.1109/access.2019.2909490 · Cited by 658 · see citing works
Quantum Secure Lightweight Cryptography with Quantum Permutation Pad
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- Authors
- Li, Y., Zhang, P., & Huang, R.
- Affiliations
- North China Electric Power University (CN)
- State Grid Corporation of China (China) (CN)
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 36285-36293
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2911804888
- Cited by
- 72
- References
- 24
- Citations by year
- 2026: 8 · 2025: 11 · 2024: 18 · 2023: 5 · 2022: 11 · 2021: 9 · 2020: 7 · 2019: 3
- FWCI
- 3.46
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Fundamental Research Funds for the Central Universities (2018ZD06)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
- Physical Sciences › Engineering › Control and Systems Engineering › Smart Grid Security and Resilience
- Physical Sciences › Computer Science › Artificial Intelligence › Cryptography and Data Security
- Keywords
- quantum cryptography, smart grid, quantum key distribution, one-time pad, quantum random number generators, lightweight stream cipher, secure data transmission, smart metering, confidentiality and integrity
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