  As wireless network technology becomes more and more popular, mutual
interference between various signals has become more and more severe and
common. Therefore, there is often a situation in which the transmission of its
own signal is interfered with by occupying the channel. Especially in a
confrontational environment, Jamming has caused great harm to the security of
information transmission. So I propose ML-based secure ultra-low power
communication, which is an approach to use machine learning to predict future
wireless traffic by capturing patterns of past wireless traffic to ensure
ultra-low-power transmission of signals via backscatters. In order to be more
suitable for the adversarial environment, we use backscatter to achieve
ultra-low power signal transmission, and use frequency-hopping technology to
achieve successful confrontation with Jamming information. In the end, we
achieved a prediction success rate of 96.19%.
