Yudha Purwanto, Kuspriyanto, Hendrawan, B. Rahardjo
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引用次数: 37
Abstract
Researches have been conducted to overcome Distributed Denial of Service (DDoS) flooding attack. Beside the use of signature based detection, anomaly based detection is also used to detect the attack. Several methods such as statistic, information theory, data mining and forecasting have been proposed. In several researches, they just focused to detect the traffic anomaly, but not to recognize the types of anomaly that were detected such as flashcrowd, types of botnet, types of DDoS, and prevention action. In this paper we categorize anomaly traffic detection system based on process and capability focus. Anomaly detection system process including traffic features, preprocessing, and detection process. Capability focus based on each main research problem to be solved, there are detectingonly anomaly, types of anomaly, and prevention system that include process to overcome the attack. At the end of paper, we provide overview of research direction and opportunities that may be done in future research.
针对DDoS (Distributed Denial of Service,分布式拒绝服务)洪水攻击进行了研究。除了使用基于签名的检测外,还使用基于异常的检测来检测攻击。提出了统计学、信息论、数据挖掘和预测等方法。在一些研究中,他们只是专注于检测流量异常,而没有识别检测到的异常类型,如flashcrowd、僵尸网络类型、DDoS类型和预防措施。本文根据流程和能力重点对异常流量检测系统进行了分类。系统异常检测过程包括流量特征、预处理、检测过程等。能力重点根据所要解决的每个主要研究问题,分为仅检测异常、异常类型和包含克服攻击过程的防御系统。在论文的最后,我们概述了未来研究的方向和可能做的机会。