In recent years, with the rapid development of mobile Internet and 5G technology, great changes have been brought to our lives, and human beings have stepped into the era of big data. These new features and techniques in 5G support many different types of mobile applications for users, which makes network security extremely challenging. Among them, more and more applications involve users’ private data, such as location information, financial information, and biological information. In order to prevent users’ privacy disclosure, most applications choose to use private protocols. However, such private protocols also provide a means for malware and malicious applications to steal users’ privacy and confidential data. From a more secure point of view, we need to provide a way for users to know how many private protocols are running on their mobile phones and distinguish which are authorized applications and which are not. Therefore, the analysis and identification of private protocols have become a hot topic in current research. How to extract the characteristics of network protocol effectively and identify the private protocol accurately becomes the most important part of this research. In this paper, we combine genetic algorithm and association rule algorithm and then propose a set of feature extraction algorithm and protocol recognition algorithm for unknown protocols. The experimental analysis based on the actual data shows that these methods can effectively solve the problems of feature extraction and recognition for unknown protocols and can greatly improve the accuracy of private protocol recognition.

中文翻译：

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无处可藏：一种新颖的专用协议识别算法

近年来，随着移动互联网和5G技术的飞速发展，我们的生活已发生了翻天覆地的变化，人类步入了大数据时代。5G中的这些新功能和技术为用户支持许多不同类型的移动应用程序，这使网络安全性极具挑战性。其中，越来越多的应用程序涉及用户的私人数据，例如位置信息，财务信息和生物信息。为了防止用户的隐私泄露，大多数应用程序选择使用私有协议。但是，此类私有协议还为恶意软件和恶意应用程序提供了一种窃取用户隐私和机密数据的手段。从更安全的角度来看，我们需要为用户提供一种方法，让他们知道他们的手机上正在运行多少个私有协议，并区分哪些是授权的应用程序，哪些不是。因此，私有协议的分析和识别已成为当前研究的热点。如何有效地提取网络协议的特征并准确识别私有协议成为本研究的重要内容。本文将遗传算法和关联规则算法相结合，提出了一套针对未知协议的特征提取算法和协议识别算法。