The convergence of quantum cryptography with applications used in everyday life is a topic drawing attention from the industrial and academic worlds. The development of quantum electronics has led to the practical achievement of quantum devices that are already available on the market and waiting for their first The research leading to the published results was supported by the project SGS reg. no.

Intensive work on quantum computing has increased interest in quantum cryptography in recent years. Although this technique is characterized by a very high level of security, there are still challenges that limit the widespread use of quantum key distribution. One of the most important problem remains secure and effective mechanisms for the key distillation process. This article presents a new idea for a key reconciliation method in quantum cryptography. This proposal assumes the use of mutual synchronization of artificial neural networks to correct errors occurring during transmission in the quantum channel. Users can build neural networks based on their own string of bits. The typical value of the quantum bit error rate does not exceed a few percent, therefore the strings are similar and also users' neural networks are very similar at the beginning of the learning process. It has been shown that the synchronization process in the new solution is much faster than in the analogous scenario used in neural cryptography. This feature significantly increases the level of security because a potential eavesdropper cannot effectively synchronize their own artificial neural networks in order to obtain information about the key. Therefore, the key reconciliation based on the new idea can be a secure and efficient solution.

In recent years, noticeable progress has been made in the development of quantum equipment, reflected through the number of successful demonstrations of Quantum Key Distribution (QKD) technology. Although they showcase the great achievements of QKD, many practical difficulties still need to be resolved. Inspired by the significant similarity between mobile ad-hoc networks and QKD technology, we propose a novel quality of service (QoS) model including new metrics for determining the states of public and quantum channels as well as a comprehensive metric of the QKD link. We also propose a novel routing protocol to achieve high-level scalability and minimize consumption of cryptographic keys. Given the limited mobility of nodes in QKD networks, our routing protocol uses the geographical distance and calculated link states to determine the optimal route. It also benefits from a caching mechanism and detection of returning loops to provide effective forwarding while minimizing key consumption and achieving the desired utilization of network links. Simulation results are presented to demonstrate the validity and accuracy of the proposed solutions.

No abstract

No abstract

Quantum Key Distribution (QKD) protocols allow the establishment of symmetric cryptographic keys up to a limited distance at limited rates. Due to optical misalignment, noise in quantum detectors, disturbance of the quantum channel or eavesdropping, an error key reconciliation technique is required to eliminate errors. This chapter analyses different key reconciliation techniques with a focus on communication and computing performance. We also briefly describe a new approach to key reconciliation techniques based on artificial neural networks.

As the cloud computing paradigm evolves, new types of cloud-based services have become available, including security services. Some of the most important and most commonly adopted security services are firewall services. These cannot be easily deployed in a cloud, however, because of a lack of mechanisms preserving firewall policy confidentiality. Even if they were provided, the customer traffic flowing through the Cloud Service Provider infrastructure would still be exposed to eavesdropping and information gaining by performing analysis. To bypass these issues, the following article introduces a novel framework, known as the Ladon Hybrid Cloud, for preserving cloud-based firewall policy confidentiality. It is shown that in this framework, a high level of privacy is provided thanks to leveraging an anonymized firewall approach and a hybrid cloud model. A number of optimization techniques, which help to further improve the Ladon Hybrid Cloud privacy level, are also introduced. Finally, analysis performed on the framework shows that it is possible to find a trade-off between the Ladon Hybrid Cloud privacy level, its congestion probability, and efficiency. This argument has been demonstrated through the results of conducted experiments.

No abstract