Wireless sensor network (WSN) is the ultimate promising field for monitoring the complex applications such that healthcare, agriculture, industry, military, weather forecasting, and Internet of Things (IoT). WSNs are composed of tiny low power sensors known for their autonomous, flexible and inexpensive nature which are designed to sense and measure physical environmental phenomena. Utilization of wireless sensor networks in difficult terrains may lead to various kinds of security threats. Identifying malicious activities in such environment is an intricate task. In recent enlargements, Wide adoption of Machine Learning (ML) algorithms by WSNs ensure accurate decision making in complex scenarios. Applying Machine Learning techniques can immensely help in boosting the efficiency and security of wireless sensor networks by limiting humanoid intervention. This study focuses on addressing the security issues providing in wi-fi sensor networks. In addition, we have executed the survey of machine learning-based techniques used to remedy these issues in the recent scenario.