Security Verification of Artificial Neural Networks Used to Error Correction in Quantum Cryptography
| Title | Security Verification of Artificial Neural Networks Used to Error Correction in Quantum Cryptography |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Niemiec, Marcin, Mehic, Miralem, Voznak, Miroslav |
| Conference Name | 2018 26th Telecommunications Forum (℡FOR) |
| Date Published | Nov. 2018 |
| Publisher | IEEE |
| ISBN Number | 978-1-5386-7171-9 |
| Keywords | Artificial neural networks, Collaboration, error correction, error correction codes, error rates, machine learning, Metrics, neural nets, Neural Network Security, Neurons, partially synchronized neural networks, passive attacks, policy-based governance, pubcrawl, quantum cryptography, resilience, Resiliency, security verification, synchronisation, Synchronization, telecommunication security |
| Abstract | Error correction in quantum cryptography based on artificial neural networks is a new and promising solution. In this paper the security verification of this method is discussed and results of many simulations with different parameters are presented. The test scenarios assumed partially synchronized neural networks, typical for error rates in quantum cryptography. The results were also compared with scenarios based on the neural networks with random chosen weights to show the difficulty of passive attacks. |
| URL | https://ieeexplore.ieee.org/document/8612006 |
| DOI | 10.1109/TELFOR.2018.8612006 |
| Citation Key | niemiec_security_2018 |
- partially synchronized neural networks
- telecommunication security
- Synchronization
- synchronisation
- security verification
- Resiliency
- resilience
- quantum cryptography
- pubcrawl
- policy-based governance
- passive attacks
- Artificial Neural Networks
- Neurons
- Neural Network Security
- neural nets
- Metrics
- machine learning
- error rates
- error correction codes
- error correction
- collaboration