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This paper proposes a novel seven-dimensional fractional-order chaotic system applied to secure communication. First, a seven-dimensional fractional order system is constructed by selecting an arbitrary fractional order q. Then, the chaotic and non-chaotic dynamic behaviors of the system are analyzed by 0–1 Test, and the correctness is verified by phase diagram comparison and complexity analysis. Then, the corresponding fractional-order chaotic circuit is designed, and the phase image which is basically consistent with the experimental simulation results is obtained. Finally, the seven-dimensional fractional-order chaotic system is used to complete the signal encryption and decryption test to achieve secure communication. This indicates that the seven-dimensional fractional-order chaotic system proposed to this paper has more complex dynamic characteristics and can be used for secure communication.

Following the establishment of the draft standardization for Post-Quantum Cryptography (PQC), cryptographic systems across various sectors have undergone a paradigm shift. Although the theoretical strength of PQC has provided a robust foundation for securing communications against quantum threats, physical implementations of PQC algorithms remain vulnerable to Side-Channel Attacks (SCAs). Existing SCA studies predominantly focus on the attack process, lacking thorough side-channel leakage assessments and comparisons of inherent vulnerabilities at different attack points and with different countermeasures. In this paper, we first present a comprehensive assessment of side-channel leakage and resistance of four attack points within an ARM Cortex-M4 implementation of Kyber, including its masked version. This assessment employs a range of countermeasures such as noise addition, random delays, clock jitter, and their combinations. Besides, we also build deep-learning models for attacking, thereby verifying the results of the leakage assessments. By collaboratively utilizing three distinct leakage assessment approaches and deep learning-based attack results, we experimentally demonstrate that different algorithmic intermediate values of Kyber are suited to different countermeasures, which advances our understanding of the capacity and vulnerability of PQC implementations.