Phishing and Spam Prevention Powered by Jetson Nano

Detecting spam emails is crucial for mitigating phishing attacks. In this research, this problem has been addressed as a classification task, using machine learning techniques to distinguish between emails categorized as spam and non-spam. Thus, this research focuses on classifying emails based on their content to effectively identify messages considered spam as potential phishing attempts. The applied methodology began with a dataset comprising classified emails and thorough data preprocessing to ensure data quality and validity. Various neural network setups were assessed and compared using Scikit-Learn, exploring diverse parameterizations to enhance performance. This study proposes a low-power computing solution aimed at reducing email scams carried out through phishing attacks. Besides, a specific cybersecurity solution based on machine learning was designed and successfully deployed on the NVIDIA Jetson Nano platform.