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Using Deep Learning for Information Security

Published by Acalvio

This whitepaper delves into the application of deep learning for detecting anonymized network traffic, particularly focusing on identifying TOR traffic. It explains how adversaries use TOR to exfiltrate data anonymously, evading traditional network intrusion detection systems. The paper presents a deep learning-based solution to detect TOR traffic by analyzing packet flows, utilizing features such as inter-arrival times and flow durations. The solution achieves high precision and recall rates, outperforming traditional machine learning models in identifying hidden threats and enhancing cybersecurity defenses.

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Related Categories Cybersecurity, Artificial Intelligence, Deep Learning, AI Ethics, AI Applications, Data Preprocessing, Model Training, Model Evaluation, Threat detection, Security Analytics, Sales & Marketing, Predictive Analysis

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