基于被动分簇算法的即时通信网络协议漏洞检测

doi:10.13229/j.cnki.jdxbgxb20200814

摘要/Abstract

摘要：

为有效挖掘出网络协议漏洞，防止恶意攻击者泄露协议机密信息，维护协议运行环境安全，提出了一种基于被动分簇算法的即时通信网络协议漏洞检测方法。该方法使用被动分簇算法中先声明者优先机制挑选簇首，按照网络健壮性和能源有效性间的均衡原则明确网关节点；对待检测协议实施形式化定义，获得协议工作详细流程；采用AFL模糊检测工具对协议的正、负样本过采样，得到完整样本集合；将前向反馈网络和支持向量机分别当作生成对抗式网络中的生成模型与判别模型，利用拉格朗日算法得到检测用例数据，将其代入协议系统内完成漏洞检测。仿真结果证明，所提方法具有极高的漏洞检测精度与效率，能有效确保网络协议运行安全性。

关键词: 被动分簇, 即时通信网络, 协议漏洞, 漏洞检测, 深度学习

Abstract:

In order to effectively mine network protocol vulnerabilities， prevent malicious attackers from divulging protocol confidential information， and maintain the security of protocol running environment， a vulnerability detection method of instant messaging network protocol based on passive clustering algorithm is proposed. In passive clustering algorithm， the first declarator priority mechanism is used to select the cluster head， and the gateway node is defined according to the balance principle between network robustness and energy efficiency； the protocol to be detected is formally defined to obtain the detailed workflow of the protocol； the positive and negative samples of the protocol are oversampled by AFL fuzzy detection tool to obtain the complete sample set， and the forward feedback network and support vector are obtained The machine is regarded as the generation model and the discrimination model in the generative adversary network， and the detection case data is obtained by using Lagrange algorithm， which is substituted into the protocol system to complete the vulnerability detection. Simulation results show that the proposed method has high accuracy and efficiency of vulnerability detection， and can effectively ensure the security of network protocol operation.

Key words: passive clustering, instant messaging network, protocol vulnerability, vulnerability detection, deep learning

中图分类号:

TP357

张杰,景雯,陈富. 基于被动分簇算法的即时通信网络协议漏洞检测[J]. 吉林大学学报(工学版), 2021, 51(6): 2253-2258.

Jie ZHANG,Wen JING,Fu CHEN. Vulnerability detection of instant messaging network protocol based on passive clustering algorithm[J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(6): 2253-2258.

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实验次数	文献［3］	文献［4］	本文方法
2	8.9	8.5	5.4
4	9.1	9.5	5.8
6	10.1	9.7	5.6
8	10.2	9.8	5.7