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The Internet of Drones (IoD) overcomes the physical limitations of traditional ground networks with its dynamic topology and 3D spatial flexibility, playing a crucial role in various fields. However, eavesdropping and spoofing attacks in open channel environments threaten data confidentiality and integrity, posing significant challenges to IoD communication. Existing foundational schemes in IoD primarily rely on symmetric cryptography and digital certificates. Symmetric cryptography suffers from key management challenges and static characteristics, making it unsuitable for IoD's dynamic scenarios. Meanwhile, elliptic curve-based public key cryptography is constrained by high computational complexity and certificate management costs, rendering it impractical for resource-limited IoD nodes. This paper leverages the low computational overhead of Chebyshev polynomials to address the limited computational capability of nodes, proposing a certificateless public key cryptography scheme. Through the semigroup property, it constructs a lightweight authentication and key agreement protocol with identity privacy protection, resolving the security and performance trade-off in dynamic IoD environments. Security analysis and performance tests demonstrate that the proposed scheme resists various attacks while reducing computational overhead by 65% compared to other schemes. This work not only offers a lightweight certificateless cryptographic solution for IoD systems but also advances the engineering application of Chebyshev polynomials in asymmetric cryptography.
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http://dx.doi.org/10.3390/s25144286 | DOI Listing |
Molecules
August 2025
Department of Chemical Engineering, National Taiwan University, Taipei 10617, Taiwan.
Diffusiophoresis of a liquid metal droplet (LMD) in a cylindrical pore is investigated theoretically in this study. A patched pseudo-spectral method based on Chebyshev polynomials combined with a geometric mapping technique is adopted to solve the resulting governing electrokinetic equations in irregular geometries. Several interesting phenomena are found which provide useful guidelines in practical applications involving liquid metal droplets (LMDs) such as drug delivery.
View Article and Find Full Text PDFBIT Numer Math
August 2025
Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, England.
The efficient approximation of highly oscillatory integrals plays an important role in a wide range of applications. Whilst traditional quadrature becomes prohibitively expensive in the high-frequency regime, Levin methods provide a way to approximate these integrals in many settings at uniform cost. In this work, we present an accelerated version of Levin methods that can be applied to a wide range of physically important oscillatory integrals, by exploiting the banded action of certain differential operators on a Chebyshev polynomial basis.
View Article and Find Full Text PDFSci Rep
August 2025
Department of Mathematics, Dr. Babasaheb Ambedkar Marathwada University, Chh. Sambhajinagar, Maharashtra, 431004, India.
This study presents an innovative numerical framework for addressing initial value problems (IVPs) in linear fractional Volterra-Fredholm integro-differential equations (FVFIDEs). The approach utilizes a spectral collocation method grounded in shifted Chebyshev polynomials of the second kind to construct an approximate solution. By integrating this approximation into the governing equation and applying collocation constraints at predefined nodes, the IVP is converted into a system of linear algebraic equations.
View Article and Find Full Text PDFInt J Numer Method Biomed Eng
August 2025
Department of Mathematics, S. V. National Institute of Technology Surat, Surat, India.
Magnetic nanoparticles for hyperthermic cancer treatment have gained significant attention in recent years. Magnetic hyperthermia ablates malignant cells by dissipating heat from magnetic nanoparticles (MNPs) when subjected to an alternate magnetic field. Living tissues are highly non-homogeneous, and non-Fourier thermal behavior in biological tissue has been experimentally observed.
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August 2025
China Mobile Research Institute, Beijing, 100053, China.
Matrix operations are crucial to various computational tasks in various fields, and quantum computing offers a promising avenue to accelerate these operations. We present a quantum matrix multiplication (QMM) algorithm that employs amplitude encoding and combines quantum walks with Chebyshev polynomial approximation to achieve quadratic acceleration for matrix chain multiplication where the same matrix is applied K times while maintaining logarithmic complexity in matrix dimension and precision. The algorithm can be applied to any complex matrix.
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