We introduce a quantum key distribution protocol using mean multi-kings' problem. Using this protocol, a sender can share a bit sequence as a secret key with receivers. We consider a relation between information gain by an eavesdropper and disturbance contained in legitimate users' information. In BB84 protocol, such relation is known as the so-called information disturbance theorem. We focus on a setting that the sender and two receivers try to share bit sequences and the eavesdropper tries to extract information by interacting legitimate users' systems and an ancilla system. We derive trade-off inequalities between distinguishability of quantum states corresponding to the bit sequence for the eavesdropper and error probability of the bit sequence shared with the legitimate users. Our inequalities show that eavesdropper's extracting information regarding the secret keys inevitably induces disturbing the states and increasing the error probability.
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http://dx.doi.org/10.3390/e22111275 | DOI Listing |
Bioinformatics
January 2025
Department of Computer Science, City University of Hong Kong, Hong Kong, China.
Motivation: Proteoforms are the different forms of a proteins generated from the genome with various sequence variations, splice isoforms, and post-translational modifications. Proteoforms regulate protein structures and functions. A single protein can have multiple proteoforms due to different modification sites.
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January 2025
The Higher Educational Key Laboratory for Flexible Manufacturing Equipment Integration of Fujian Province (Xiamen Institute of Technology), Xiamen, 361021, China.
With ongoing social progress, three-dimensional (3D) video is becoming increasingly prevalent in everyday life. As a key component of 3D video technology, depth video plays a crucial role by providing information about the distance and spatial distribution of objects within a scene. This study focuses on deep video encoding and proposes an efficient encoding method that integrates the Convolutional Neural Network (CNN) with a hyperautomation mechanism.
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December 2024
School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China.
This study presents a novel algorithm for protocol reverse analysis of EtherCAT. The algorithm combines sequence alignment and the Pearson correlation coefficient. We utilize value distribution statistics and the bit flip rate algorithm to effectively partition the protocol fields.
View Article and Find Full Text PDFGenes (Basel)
December 2024
Genomic Medicine Laboratory UILDM, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.
Recent advancements in Next-Generation Sequencing (NGS) technologies have revolutionized genomic research, presenting unprecedented opportunities for personalized medicine and population genetics. However, issues such as data silos, privacy concerns, and regulatory challenges hinder large-scale data integration and collaboration. Federated Learning (FL) has emerged as a transformative solution, enabling decentralized data analysis while preserving privacy and complying with regulations such as the General Data Protection Regulation (GDPR).
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December 2024
School of Electronic and Nanoscale Engineering, University of Glasgow, Glasgow, G12 8QQ, UK.
In the era of the Internet of Things (IoT), the transmission of medical reports in the form of scan images for collaborative diagnosis is vital for any telemedicine network. In this context, ensuring secure transmission and communication is necessary to protect medical data to maintain privacy. To address such privacy concerns and secure medical images against cyberattacks, this research presents a robust hybrid encryption framework that integrates quantum, and classical cryptographic methods.
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