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  • Open Access

23 February 2022

13 Pages

Encrypted Malicious Traffic Detection Based on Word2Vec

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1
Graduate School of Media and Governance, Keio University, Kanagawa 252-0882, Japan
2
Faculty of Environment and Information Studies, Keio University, Kanagawa 252-0882, Japan
3
Keio University, Tokyo 108-8345, Japan
*
Author to whom correspondence should be addressed.

Abstract

Network-based intrusion detections become more difficult as Internet traffic is mostly encrypted. This paper introduces a method to detect encrypted malicious traffic based on the Transport Layer Security handshake and payload features without waiting for the traffic session to finish while preserving privacy. Our method, called TLS2Vec, creates words from the extracted features and uses Long Short-Term Memory (LSTM) for inference. We evaluated our method using traffic from three malicious applications and a benign application that we obtained from two publicly available datasets. Our results showed that TLS2Vec is promising as a tool to detect such malicious traffic.

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