Faces are widely used in information recognition and other fields. Due to the openness of the Internet, ensuring that face information is not stolen by criminals is a hot issue. The traditional encryption method only encrypts the whole area of the image and ignores some features of the face. This paper proposes a double-encrypted face image encryption algorithm. The contour features of the face are extracted, followed by two rounds of encryption. The first round of encryption algorithm encrypts the identified face image, and the second round of encryption algorithm encrypts the entire image. The encryption algorithm used is scrambling and diffusion at the same time, and the keystream of the cryptosystem is generated by 2D SF-SIMM. The design structure of this cryptosystem increases security, and the attacker needs to crack two rounds of the algorithm to get the original face image.

Designing a chaotic system with a simple structure and complex dynamic behavior is one of the main tasks of chaotic cryptography. This paper designs a new 1D chaotic system called 1D two-parameters-sin-cos (1D-TPSC). Compared with high-dimensional chaotic systems, the 1D-TPSC has a simple structure and is easy to implement with software. The Lyapunov exponent analyzes the parameter space of the 1D-TPSC in a chaotic state. Furthermore, using sensitivity analysis, cobweb plot, and bifurcation diagram to verify that the sequence generated by 1D-TPSC has good performance. In addition, the 1D-TPSC has also been applied in chaotic image encryption. Arnold mapping is used to scramble the plaintext, and random XOR is used to diffuse the scrambled image. Simulation experiments show that the method can remarkably resist standard attack methods.

In this paper, a high security color image encryption algorithm is proposed by 2D Sin-Cos-Hénon (2D-SCH) system. A new two-dimensional chaotic system which is 2D-SCH. This system is hyperchaotic. The use of the 2D-SCH, a color image encryption algorithm based on random scrambling and localization diffusion, is proposed. First, the secret key is generated by SHA512 through plaintext. As the initial value of the 2D-SCH system, the secret key is used to generate chaotic sequences. Then, the random scrambling is designed based on chaotic sequences. Finally, a pair of initial points is generated by the secret key; the image diffuses around this point. The ciphertext is obtained by a double encryption. Different from the traditional encryption algorithm, this paper encrypts three channels of color image simultaneously, which greatly improves the security of the algorithm. Simulation results show that the algorithm can resist various attacks.

The bionic flapping wing aircraft realizes flight by imitating the structure and flapping mode of birds. In this paper, a three-dimensional composite motion aerodynamic analysis model of a bionic flapping wing is established. The diverting field and flapping wing grid are divided up using dynamic hybrid grid technology. The flow field of the flapping wing is analyzed by solving the Navier–Stokes (N–S) equation combined with the Boussinesq hypothesis. The lift of the flapping wing under different flutter frequencies and incoming wind speeds is studied under the asymmetric flutter condition. In order to verify the accuracy of the aerodynamic simulation results, a flapping-wing shrinking-ratio model prototype is made, and low-speed wind tunnel experiments are carried out to test the changes in the flight lift of the wing at different flutter frequencies and angles of attack. A comparative analysis of the wind tunnel experiment and the aerodynamic simulation results shows that when the flapping frequency (1–5 Hz) and incoming wind speed (1–5 m/s) increase, the lift force generated by the wing flapping increases. Due to the deviation between the experimental sample airfoil area and the simulated airfoil area, as well as the wing-driven fuselage vibration during the experiment, a sensor error is produced, resulting in a deviation of about 1 N between the experimental result curve and the simulation result curve. However, the aerodynamic characteristics obtained from the aerodynamic simulation analysis are basically consistent with the aerodynamic change law measured in the wind tunnel experiment.