Techniques and tools for analyzing intrusion alerts

Author:

Ning Peng1,Cui Yun1,Reeves Douglas S.1,Xu Dingbang1

Affiliation:

1. North Carolina State University, Raleigh, NC

Abstract

Traditional intrusion detection systems (IDSs) focus on low-level attacks or anomalies, and raise alerts independently, though there may be logical connections between them. In situations where there are intensive attacks, not only will actual alerts be mixed with false alerts, but the amount of alerts will also become unmanageable. As a result, it is difficult for human users or intrusion response systems to understand the alerts and take appropriate actions. This paper presents a sequence of techniques to address this issue. The first technique constructs attack scenarios by correlating alerts on the basis of prerequisites and consequences of attacks. Intuitively, the prerequisite of an attack is the necessary condition for the attack to be successful, while the consequence of an attack is the possible outcome of the attack. Based on the prerequisites and consequences of different types of attacks, the proposed method correlates alerts by (partially) matching the consequences of some prior alerts with the prerequisites of some later ones. Moreover, to handle large collections of alerts, this paper presents a set of interactive analysis utilities aimed at facilitating the investigation of large sets of intrusion alerts. This paper also presents the development of a toolkit named TIAA, which provides system support for interactive intrusion analysis. This paper finally reports the experiments conducted to validate the proposed techniques with the 2000 DARPA intrusion detection scenario-specific datasets, and the data collected at the DEFCON 8 Capture the Flag event.

Publisher

Association for Computing Machinery (ACM)

Subject

Safety, Risk, Reliability and Quality,General Computer Science

Reference38 articles.

1. AT&T Research Labs. GraphViz---Open Source Graph Layout and Drawing Software. Available at http://www.research.att.com/sw/tools/graphviz/.]] AT&T Research Labs. GraphViz---Open Source Graph Layout and Drawing Software. Available at http://www.research.att.com/sw/tools/graphviz/.]]

Cited by 119 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Fusion Analysis of Intelligent Connected Vehicle Security Events Based on Multidimensional Heterogeneous Data;Communications in Computer and Information Science;2024

2. Enhancing Security in 5G Networks: A Hybrid Machine Learning Approach for Attack Classification;2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA);2023-12-04

3. Temporal-Gated Graph Neural Network with Graph Sampling for Multi-step Attack Detection;2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom);2023-11-01

4. Research on university network security situation assessment model;International Conference on Computer Network Security and Software Engineering (CNSSE 2023);2023-06-26

5. An effective attack scenario construction model based on identification of attack steps and stages;International Journal of Information Security;2023-05-28

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3