通过渗透测试工具包对网络数据包进行取证分析

Da-Yu Kao, Yu-Siang Wang, Fuching Tsai, Chien-Hung Chen
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引用次数: 3

摘要

网络攻击的规模和频率可能会继续增加。随着攻击者变得比以前更聪明,为防止不必要的数据盗窃所做的努力也越来越多。本文的目的是通过可重复的实验,在构成PT活动的网络数据包的持续嗡嗡声中寻找不寻常的模式。利用不同的PT工具包,如Winfingerprint, Superscan, Nmap, SoftPerfect Network Scanner, NeoTrace, Nessus Vulnerability Scanner和Path Analyzer Pro,便于网络攻击者使在线系统瘫痪。它能够从以下三个阶段识别通过连接的机器提供的大量网络信息流中的网络流量:数据收集、数据简化和数据分析。网络取证可以帮助检测攻击行为。本文将实时证据收集作为对抗攻击者的网络特征。识别网络数据包中的异常模式已被用于对抗恶意黑客,这些恶意黑客可能是任何心怀不满的客户,也可能是国家。这种方法可以很容易地部署,并且应该适用于任何类型的基于网络的评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forensic analysis of network packets from penetration test toolkits
Cyber-attacks are likely to continue to increase in size and frequency. As attackers get smarter than before, so do efforts made to protect against unwanted data theft. The purpose of this paper is to look for unusual patterns by repeatable experiments among the constant buzz of network packets that make up PT activities. The utilization of different PT toolkits, like Winfingerprint, Superscan, Nmap, SoftPerfect Network Scanner, NeoTrace, Nessus Vulnerability Scanner, and Path Analyzer Pro, facilitates cyber-attackers to bring down online system. It is capable of discerning network traffic on the vast streams of network information available through the connected machines from the following three phases: data collection, data reduction, and data analysis. Network forensics can aid in detecting attack behavior. This paper accommodates real-time evidence collection as a network feature against attackers. The identification of unusual patterns in network packets has been put to use in the ongoing battle to stay one step ahead of malicious hackers, who could be anyone from disgruntled customers to nation states. This approach can be easily deployed and should be applicable to any type of network-based assessment.
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