Encrypting traffic does not prevent an attacker from performing some types of traffic analysis. We present a straightforward traffic analysis attack against encrypted HTTP streams that is surprisingly effective in identifying the source of the traffic. An attacker starts by creating a profile of the statistical characteristics of web requests from interesting sites, including distributions of p...

Telecommuting and telelearning have gradually become mainstream lifestyles in the post-epidemic era. The extensive interconnection of massive terminals gives attackers more opportunities, which brings significant challenges to network traffic security analysis. existing attacks, often using encryption technology distributed attack methods, increase number complexity attacks. However, traditiona...

Network Function Virtualisation (NFV) advances the adoption of composable software middleboxes. Accordingly, cloud data centres become major NFV vendors for enterprise traffic processing. Due to privacy concern redirection cloud, secure middlebox systems (e.g., BlindBox) draw much attention; they can process encrypted packets against rules directly. However, most existing supporting pattern mat...

The purpose of this work is to evaluate the quality of encrypted VoIP calls with different encryption algorithms through OpenVPN software, in order to identify differences in results between encryption algorithms and also differences between non-encrypted and encrypted calls. This evaluation will take into account the MOS (Mean Opinion Score), a method to indicate user satisfaction of voice com...

Abstract To resolve the issues of low accuracy, weak universality, and easy invasion privacy in traditional encryption traffic classification methods, an method based on a convolutional neural network is offered. Firstly, according to packet size time message net traffic, original transformed into two-dimensional picture avoid relying payload violate privacy, then model embedded. The Inception ...

Many people started being concerned about their privacy in delivering private chats, photographs, contacts and other personal information through mobile instant messaging services. Fortunately, in the majority of mobile instant messaging services, encrypted communication channels (e.g., using the SSL/TLS protocols) are used by default to protect delivered messages against eavesdropping attacks....

Detecting encrypted traffic is increasingly important for deep packet inspection (DPI) to improve the performance of intrusion detection systems. We propose a machine learning approach with several randomness tests to achieve high accuracy detection of encrypted traffic while requiring low overhead incurred by the detection procedure. To demonstrate how effective the proposed approach is, the p...