Nowaday, emails are used in almost every field, from business to education. Emails have two subcategories, i.e., ham and spam. Email spam, also called junk emails or unwanted emails, is a type of email that can be used to harm any user by wasting his/her time, computing resources, and stealing valuable information. The ratio of spam emails is increasing rapidly day by day. Spam detection and filtration are significant and enormous problems for email and IoT service providers nowadays. Among all the techniques developed for detecting and preventing spam, filtering email is one of the most essential and prominent approaches. Several machine learning and deep learning techniques have been used for this purpose, i.e., Naïve Bayes, decision trees, neural networks, and random forest. This paper surveys the machine learning techniques used for spam filtering techniques used in email and IoT platforms by classifying them into suitable categories. A comprehensive comparison of these techniques is also made based on accuracy, precision, recall, etc. In the end, comprehensive insights and future research directions are also discussed.

For the last two decades, cybercrimes are growing on a daily basis. To track down cybercrimes and radio network crimes, digital forensic for radio networks provides foundations. The data transfer rate for the next-generation wireless networks would be much greater than today’s network in the coming years. The fifth-generation wireless systems are considering bands beyond 6 GHz. The network design of the next-generation wireless systems depends on propagation characteristics, frequency reuse, and bandwidth variation. This article declares the channel’s propagation characteristics of both line of sight (LoS) and non-LOS (NLoS) to construct and detect the path of rays coming from anomalies. The simulations were carried out to investigate the diffraction loss (DL) and frequency drop (FD). Indoor and outdoor measurements were taken with the omnidirectional circular dipole antenna with a transmitting frequency of 28 GHz and 60 GHz to compare the two bands of the 5th generation. Millimeter-wave communication comes with a higher constraint for implementing and deploying higher losses, low diffractions, and low signal penetrations for the mentioned two bands. For outdoor, a MATLAB built-in 3D ray tracing algorithm is used while for an indoor office environment, an in-house algorithmic simulator built using MATLAB is used to analyze the channel characteristics.