Network-based malcode detection technology

WU Bing1; YUN Xiao-chun2; GAO Qi1

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Network-based malcode detection technology

更新时间：2024-10-14

- Network-based malcode detection technology
- Issue 11, Pages: 87-91(2007)
- 作者机构：
  
  哈尔滨工业大学计算机网络与信息安全技术研究中心 2. 中国科学院计算技术研究所
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP309.5
- Published：2007
- 稿件说明：
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WU Bing1, YUN Xiao-chun2, GAO Qi1. Network-based malcode detection technology[J]. 2007, (11): 87-91.
DOI：

WU Bing1, YUN Xiao-chun2, GAO Qi1. Network-based malcode detection technology[J]. 2007, (11): 87-91. DOI：

摘要

通过对传统分布式IDS的分析

指出基于详细协议分析的多引擎小规则集的系统结构用于网络级恶意代码检测的缺陷

设计了单引擎大特征集的网络级恶意代码检测模型及恶意代码特征描述语言;分析了网络数据流的特征

通过对特征串进行优化的方法

避免特征串后缀与数据流的频繁碰撞及链表分支不平衡的问题

大幅度提高了WM算法检测网络恶意代码的效率。

Abstract

Following the analysis for traditional distributed IDS

disadvantages that applying structure of multiple engine and small rules set to detect network-level malcode were pointed out

which is based on detailed protocol decoding.Detection model and anti-malcode markup language of network-level malcode were designed for single engine and big rules set.The characteristics of network data flow were analyzed.By optimization of patterns

frequent collisions between suffix with data flow and unbalanced branched of chained list were avoided.The efficiency by using WM algorithm to detect malcode on network level can be remarkably increased.

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Related Author

Rui MEI

Ge NING

Liang-liang WANG

Wei-ping WEN

XIU Zhi-hua

LIU Meng-juan

HONG Pei-lin

LI Jin-sheng

Related Institution

Department of Information Security, School of Software and Microelectronics, Peking University

中国科学技术大学电子工程与信息科学系信息网络实验室

Infonet Lab., Dept. of Electronic Engineering and Information Science, University of Science and Technology of China

School of Software,Jiangxi Normal University

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