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Human vs Bots: Detecting Human Attacks in a Honeypot Environment

机译:人与机器人:在蜜罐环境中检测人为攻击

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摘要

The increase in the automated attacks has motivated security researchers to focus on identifying patterns of attacker to safeguard the system. Humans have some basic behavioral characteristics and limitations, which can be identified and used to distinguish them from automated attackers. The network log data collected from a Honeypot uncovers such traits which are otherwise not noticeable. The paper analyses a SSH-based Honeypot deployed over a period of 423 days to identify human behavior traits which can essentially distinguish an automated attacker and a human attacker.
机译:自动攻击的增加促使安全研究人员专注于确定攻击者的模式以保护系统。人类具有一些基本的行为特征和局限性,可以识别并用于将其与自动攻击者区分开。从Honeypot收集的网络日志数据揭示了这些特征,否则这些特征就不会引起注意。本文分析了在423天的时间内部署的基于SSH的Honeypot,以识别人类行为特征,这些特征可以从根本上区分自动攻击者和人类攻击者。

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