An Efficient Spam Detection Technique for IoT Devices using Machine Learning. (Java)

Millions of devices with sensors and actuators linked via wired or wireless channels for transmission of data make up the Internet of Things (IoT). In years to come, the amount of data that these devices release will grow substantially. In such a setting, machine learning algorithms can be important in maintaining biotechnology-based verification and security, as well as in detecting errors to enhance the security and usability of Network of Things systems. Attackers, on the other hand, use machine learning algorithms to take advantage of issues in intelligent IoT-based systems. Inspired by this, in this research, we suggests using machine learning to detect spam so as protect IoT devices. This approach assesses five machine learning models with an array of measured