With the fast development of the Internet of Things (IoT) technologies, more IoT devices are currently connected with the Internet, resulting in more exchange of information. However, data privacy and security threats have become emerging challenges of the IoT. In this paper, we are concerned about the security of image transmission in green IoT. Image encryption algorithms for green IoT are faced with two challenges: 1) To save the cost, devices in green Internet of Things (IoT) always have very low computing power, so they cannot support high-precision computing and 2) The algorithm deployed on the device should be efficient to guarantee the device to run for a long time. To solve the problem of precision limited, we propose a parallel chaotic system named PSBP. ¹ The PSBP is composed of Piecewise Linear Chaotic Map (PWLCM), Skew Tent Map (STM) and Bernoulli map in parallel model with the limited precision of 16-bit, which can generate good-performance key matrix for encryption. Then, we introduce a cost-efficient image encryption algorithm based on PSBP (named IEPSBP) which addresses the second challenge. Instead of bits or bytes, we use one row or one column as the basic unit to realize permutation and diffusion. The security analysis and performance experiments indicate that IEPSBP is secure and cost-efficient for green IoT.

In these years, image encryption systems based on chaotic maps have received considerable attention from researchers. For the security of encryption algorithms, it is important to ensure that chaotic systems can produce high quality pseudo-random sequences. However, when a chaotic system that theoretically has good random performance is deployed in a limited precision platform, its random performance will deteriorate. We prove that even if the precision reaches 256-bit, the piecewise linear chaotic map still fails to achieve the desired random performance. Moreover, in the case of low precision, the cascade structure commonly used in mixed chaotic maps will aggravate the problem of random degeneration. To generate good pseudo-random numbers in low-precision platforms, we propose a positive integer random sequence generator, called 32-bit PL_PWLCM&LM, which comprises two 32-bit PL_PWLCMs and one 32-bit logistic map in parallel. In our proposed image encryption system, we adopt the permutation algorithm with four pixels as a permutation unit and the diffusion algorithm based on rows and columns. The security and performance analyses prove that the proposed scheme is a secure, robust, and fast image encryption algorithm. Source codes are shared on GitHub: https://github.com/cuclihao/Pic_Enc_V3.

In order to improve the reliability of electronic transactions, it is necessary to study more stringent and effective methods of identification and authentication. Face recognition technology has been applied in electronic trading, but it has not been widely promoted on a global scale. In view of this, based on the 3D modeling technology, this study combines the actual situation to carry out the demand analysis. Moreover, on this basis, the face feature recognition process is set. In addition, based on the needs of network finance for identity recognition and authentication and the characteristics and deficiencies of face image identification and authentication methods, this paper proposes an image-based identity recognition and authentication method for systems to be more strictly authenticated. Finally, this paper sets the comparative experiment to compare the performance of the algorithm. The results show that the proposed algorithm has certain practical effects and can provide theoretical reference for related research.