Summary We propose a novel AR CAPTCHA that first uses Augmented Reality to design CAPTCHA. Users should use their cameras on mobile devices to capture a marker in the 3D physical world or PC screens to find the appropriate angle to recognize each 3D character rendered on the marker in a 3D registration manner, which is very hard for machines or robots to do the same thing. Besides, we add many random 2D characters on the marker to make the state‐of‐the‐art scene text recognition methods fail to recognize the target 3D characters. To ensure availability, we design dual‐channel scenario setting (mobile phone and physical world) that enhances the security level of CAPTCHA and single‐channel scenario setting (mobile phone only) that the gyroscope could be used for our CAPTCHA. The experimental results reveal that the recognition accuracy of machines is nearly 0%, while a human could recognize AR CAPTCHA in only a few seconds.

With the construction and improvement of 5G infrastructure, more devices choose to access the Internet to achieve some functions. People are paying more attention to information security in the use of network devices. This makes lightweight block ciphers become a hotspot. A lightweight block cipher with superior performance can ensure the security of information while reducing the consumption of device resources. Traditional optimization tools, such as brute force or random search, are often used to solve the design of Symmetric-Key primitives. The metaheuristic algorithm was first used to solve the design of Symmetric-Key primitives of SKINNY. The genetic algorithm and the simulated annealing algorithm are used to increase the number of active S-boxes in SKINNY, thus improving the security of SKINNY. Based on this, to improve search efficiency and optimize search results, we design a novel metaheuristic algorithm, named particle swarm-like normal optimization algorithm (PSNO) to design the Symmetric-Key primitives of SKINNY. With our algorithm, one or better algorithm components can be obtained more quickly. The results in the experiments show that our search results are better than those of the genetic algorithm and the simulated annealing algorithm. The search efficiency is significantly improved. The algorithm we proposed can be generalized to the design of Symmetric-Key primitives of other lightweight block ciphers with clear evaluation indicators, where the corresponding indicators can be used as the objective functions.

R. Behnia et al proposed a NTRU-based searchable encryption scheme in 2017. Compared with the previous searchable encryption scheme, this scheme has a great improvement in security and efficiency, and can resist quantum computing. But this scheme will expose a lot of information to the server. If the server is not completely honest, an attacker can use the information to attack a user’s keywords. This paper proposes an improvement of Rouzbeh’s scheme, solves this problem and improves security.