Early Identification of Services in HTTPS Traffic

Authors: Wazen M. Shbair, Thibault Cholez, Jerome Francois, Isabelle Chrisment
Published: 2020-08-19

Source: https://arxiv.org/abs/2008.08350

PDF: https://arxiv.org/pdf/2008.08350

AIにより推定されたラベル

性能評価指標 通信効率 機械学習手法

※ こちらのラベルはAIによって自動的に追加されました。そのため、正確でないことがあります。
詳細は文献データベースについてをご覧ください。

Abstract

Traffic monitoring is essential for network management tasks that ensure security and QoS. However, the continuous increase of HTTPS traffic undermines the effectiveness of current service-level monitoring that can only rely on unreliable parameters from the TLS handshake (X.509 certificate, SNI) or must decrypt the traffic. We propose a new machine learning-based method to identify HTTPS services without decryption. By extracting statistical features on TLS handshake packets and on a small number of application data packets, we can identify HTTPS services very early in the session. Extensive experiments performed over a significant and open dataset show that our method offers a good accuracy and a prototype implementation confirms that the early identification of HTTPS services is satisfied.