Comparative study of computer simulation software's

Nowadays, walking is considered as an efficient biometric feature for user authentication. Although there are some studies that address the task of securing gait patterns in gait-based authentication systems, but they do not take into account the low discrimination and high diversity of gait data, which significantly affects the security and practicality of the proposed systems. In this article, we focus on addressing the above shortcomings in the inertial sensor-based gait system. In particular, we use linear discrimination analysis to increase the discrimination of gait patterns, and use the amount of gray code to extract a high, differential, and stable binary pattern. Experimental results on 38 different users showed that our proposed method significantly improves the performance and security of the gait encryption system. Specifically, we obtained a false acceptance rate of 6 × 10−5 (for example, 1 failurein 16983 experiments) and a false rejection rate of 9 2 with 148-bit security.