Multilingual Phishing Detection Enhanced by OSINT and Machine Learning
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🛡️🌍 Innovative Approach to Multilingual Email Phishing Detection Using OSINT and Machine Learning. A recent study investigates the effectiveness of integrating open-source intelligence (OSINT) tools with machine learning (ML) models to enhance the detection of email phishing attacks across multilingual datasets, specifically English and Arabic. By extracting 17 features such as domain names and IP addresses using tools like Nmap and theHarvester, the research found that the Random Forest algorithm achieved the highest accuracy at 97.37%. This approach not only improved detection rates compared to traditional models but also addressed the limitations of existing ML systems that primarily focus on English data. The findings underscore the potential of combining OSINT with advanced ML techniques to bolster cybersecurity measures against phishing threats in diverse linguistic contexts.
