As network security and privacy issues are widely concerned,more and more network traffic is transmitted by using encryption technology.The classification of encrypted traffic plays a vital role in network supervision.In or-der to solve the problems of user privacy leakage that are easy to occur in the process of encrypted traffic classifica-tion,a privacy protection method of encrypted traffic feature set based on Laplace mechanism was proposed.In this method,the label bar of the encrypted traffic feature set is disturbed to a certain extent according to the generated in-terval by generating random disturbance interval intervals,so as to protect user privacy information.Finally,the pro-posed method is verified on the ISCX VPN-NonVPN dataset.The experimental results show that the accuracy of en-crypted traffic classification can be well guaranteed under the premise of ensuring privacy,which proves the effective-ness and usability of the proposed method.
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