Mosaic Tracking: Lightweight Batch Video Frame Awareness Multitarget Encryption Scheme Based on a Novel Discrete Tabu Learning Neuron and YoloV5

With the popularity of surveillance devices, the security of surveillance video has attracted much attention, and three key issues need to be solved. The videos cannot be synchronized with their encryption effects, while full encryption does not meet the current trend of lightweight algorithms, and customized encryption for multiple specific targets is rarely seen. Inspired by this, a lightweight batch video frame awareness multitarget encryption scheme based on a novel discrete Tabu learning neuron (DTLN) and YoloV5 is designed in this article, the DTLN is in hyperchaotic state within a great range of parameters, which ensures the diversity of key selection and security. At the same time, the coexistence of homogeneous attractors is found, and such attractors are difficult to be successfully recognized by the parameter recognition algorithm, which increases the difficulty for the attacker to obtain the key. The mosaic tracking scheme designed by YoloV5 network can lightweightly encrypt batch frames of multiple types and targets, and users can also customize the encryption targets according to their needs. The simulation results show that the encryption scheme can realize lightweight encryption of multitype and multitarget, and performs well in all the security performance indexes, and has certain advantages compared with other video encryption schemes in terms of performance and functionality.