Because of the substantial progress in quantum computing technology, the safety of traditional cryptologic schemes is facing serious challenges. In this study, we explore the quantum safety of the lightweight cipher MIBS and propose quantum key-recovery attacks on the MIBS cipher by utilizing Grover’s algorithm and Bernstein–Vazirani algorithm. We first construct linear-structure functions based on the 5-round MIBS cipher according to the characteristics of the linear transformations, and then we obtain a quantum distinguisher of the 5-round MIBS cipher by applying Bernstein–Vazirani algorithm to the constructed functions. Finally, utilizing this distinguisher and Grover’s algorithm, we realize a 7-round key-recovery attack on the MIBS cipher, and then we expand the attack to more rounds of MIBS based on a similar idea. The quantum attack on the 7-round MIBS requires 156 qubits and has a time complexity of $2^{10.5}$. An 8-round attack requires 179 qubits and has a time complexity of $2^{22}$. Compared with existing quantum attacks, our attacks have better time complexity when attacking the same number of rounds.

The two-dimensional inverse synthetic aperture radar (2-D ISAR) image is a 2-D projection of the three-dimensional (3-D) shape of the target, and it is difficult to meet the demand of recognition and classification, especially of targets with complex motion. Recently, interferometric ISAR (InISAR) has been receiving increasing attention since it can reconstruct the 3-D shape of the target with high resolution. This paper proposes a novel 3-D InISAR imaging algorithm based on linear canonical transform (LCT) for targets with complex motion. In this method, the initial echo signal model is generated after analyzing the complex motion of the target. After motion compensation and image coregistration, the azimuth echo is modeled as linear frequency modulation (LFM) signal. Given the time-frequency characteristics of LFM signal, then a new 2-D ISAR imaging algorithm based on LCT is developed to obtain well-focused and multi-channel 2-D ISAR images as well as preserve the phase information of images. Finally, employing the interferometric technique, a novel 3-D InISAR imaging method is proposed and the high-resolution 3-D shape of the target can be reconstructed. In addition, the time-frequency concentration, moderate computation cost and effect of baseline are discussed, and different simulation experiments and results verify the superior performance of the proposed method.