加密
计算机科学
相(物质)
数据挖掘
计算机安全
物理
量子力学
作者
Yipeng Wang,Huijie He,Yingxu Lai,Alex X. Liu
出处
期刊:IEEE ACM Transactions on Networking
[Institute of Electrical and Electronics Engineers]
日期:2022-09-30
卷期号:31 (3): 1071-1086
被引量:5
标识
DOI:10.1109/tnet.2022.3209979
摘要
Encryption technology has been widely used in today's network communications. The early classification of encrypted flows is of great value to the control, allocation and management of resources in TCP/IP networks. In this paper, we propose TaTic, an early classification method for encrypted traffic, which aims to reduce the time spent observing the encrypted flows to be classified, and at the same time ensure the flow classification accuracy. TaTic is based on our key observation that the majority of encrypted flows can be classified accurately using only the first few packets, and we call such flows "easy flows", whereas the rest of encrypted flows requires more packets for fine-grained analysis to achieve accurate traffic classification, and we call such flows "hard flows". Given an encrypted flow, in the first phase, we use only the first few packets to quickly determine whether it is an easy flow or a hard flow; if it is an easy flow, we directly classify it in this phase; otherwise, we use more packets to perform traffic classification in the second phase. Therefore, we can greatly reduce the time spent in observing the flows without sacrificing the classification accuracy. Our experimental results show that TaTic can greatly reduce the unnecessary time spent in observing the flow to be classified, and at the same time ensure high classification accuracy. We compare our experimental results of TaTic with four existing methods. TaTic is superior to the existing methods in terms of both classification accuracy and average waiting time.
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