Detection of Malicious Websites Using Machine Learning Techniques

Understand

In detecting malicious websites, a common approach is the use of blacklists which are not exhaustive in themselves and are unable to generalize to new malicious sites.

• Detecting newly encountered malicious websites automatically will help reduce the vulnerability to this form of attack.
• In this study, we explored the use of ten machine learning models to classify malicious websites based on lexical features and understand how they generalize across datasets.
• Specifically, we trained, validated, and tested these models on different sets of datasets and then carried out a cross-datasets analysis.