Affiliation:
1. School of Cyberspace Science, Harbin Institute of Technology, Harbin 150001, China
2. School of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
Abstract
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.
Funder
National Key R&D Program of China
Subject
Computer Networks and Communications,Information Systems
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