Search Results (5)

Advances in quantum computing pose a fundamental threat to classical public-key cryptosystems, including RSA and elliptic-curve cryptography (ECC), which form the foundation for authentication and key exchange in the Transport Layer Security (TLS) protocol. In response to these emerging threats, Korea launched the KpqC (Korea Post-Quantum Cryptography) project in 2021 to design, evaluate, and standardize domestic PQC algorithms. To the best of our knowledge, this is the first systematic evaluation of the finalized Korean PQC algorithms (HAETAE, AIMer, SMAUG-T, NTRU+) within a production-grade TLS/X.509 stack, enabling direct comparison against NIST PQC and ECC baselines. To contextualize KpqC performance, we further compare against NIST-standardized PQC algorithms and classical ECC baselines. Our evaluation examines both static overhead (certificate size) and dynamic overhead (TLS 1.3 handshake latency) across computation-bound (localhost) and network-bound (LAN) scenarios, including embedded device and hybrid TLS configurations. Our results show that KpqC certificates are approximately 4.6–48.8× larger than ECC counterparts and generally exceed NIST PQC sizes. In computation-bound tests, both NIST PQC (ML-KEM) and KpqC hybrids exhibited similar handshake latency increases of approximately 8–9× relative to ECC. In network-bound tests, the difference between the two families was negligible, with relative overhead typically around 30–41%. These findings offer practical guidance for balancing security level, key size, packet size, and latency and support phased PQC migration strategies in real-world TLS deployments. Full article

With the rapid development of electronic technology, the electromagnetic interference encountered by airborne synthetic aperture radar (SAR) is no longer satisfied with a single type of interference, and it often encounters both suppressive and deceptive interference. In this manuscript, an algorithm based on blind signal separation (BSS) and deep residual learning is proposed for airborne SAR multi-electromagnetic interference suppression. Firstly, theoretical airborne SAR imaging in a multi-electromagnetic interference environment model is established, and the signal-mixed model of multi-electromagnetic interference is proposed. Then, a BSS algorithm using maximum kurtosis deconvolution and improved principal component analysis (PCA) is presented for suppressing the composite electromagnetic interference encountered by airborne SAR. Finally, in order to find the desired signal among multiple separated sources and to cope with the residual noise, a deep residual network is designed for signal recognition and denoising. This method uses a BSS algorithm with maximum kurtosis deconvolution and improved PCA to perform mixed signal separation. After performing signal separation, the original echo signal and the jamming can be obtained. To solve the separation order uncertainty and residual noise problems of the existing BSS algorithms, the deep residual network is designed to recognize airborne SAR signals after airborne SAR imaging. This algorithm has a better signal restoration degree, higher image restoration degree, and better compound interference suppression performance before and after anti-interference. Simulation and measurement results demonstrate the effectiveness of our presented algorithm. Full article

Security vulnerabilities in the symmetric-key primitives of a cipher can undermine the overall security claims of the cipher. With the rapid advancement of quantum computing in recent years, there is an increasing effort to evaluate the security of symmetric-key cryptography against potential quantum attacks. This paper focuses on analyzing the quantum attack resistance of AIM, a symmetric-key primitive used in the AIMer digital signature scheme. We present the first quantum circuit implementation of AIM and estimate its complexity (such as qubit count, gate count, and circuit depth) with respect to Grover’s search algorithm. For Grover’s key search, the most important optimization metric is depth, especially when considering parallel search. Our implementation gathers multiple methods for a low-depth quantum circuit of AIM in order to reduce the Toffoli depth and full depth (such as the Karatsuba multiplication and optimization of inner modules; $\mathsf{Mer}$, $\mathsf{LinearLayer}$). Full article