Software-Based Platform for Education and Training of DDoS Attacks Using Virtual Networks

Walter Fuertes, Anabel Tunala, Ronnie Moncayo, Fausto Meneses, T. Toulkeridis
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引用次数: 3

Abstract

The education and training of security networks is an essential challenge for the academy, due to the vertiginous increase of threats and vulnerabilities. This study aims to implement a software-based experimental platform over virtual network environments, in order to stimulate teaching in Distributed Denial of Service (DDoS) attacks. We have used the theories of learning oriented to the experience, reflexive observation, and active experimentation of the students. This allowed to evaluate the learning objectives based on Bloom's Digital Taxonomy. From the software point of view, the experimental paradigm of Software Engineering has been applied, using Scrum as an agile methodology. During the development of the application, we implemented different roles including attackers, learners as well as victims in order to reconstruct and understand real attacks on IP networks. Hereby, for the role of attackers, we have used an interface to select the type of attack, while for the role of learners, we designed an intuitive interface that presents through natural language, to select possible firewall rules. This helped to learn, detect and mitigate potential attacks. Finally, for the role of victims, we included an analytical approach, which allowed to recognize online the impact of attacks on the performance of the computer system. The results demonstrate the functionality of the platform confirming that the introduced software meets the Usability criteria. Finally, our results present a network security learning, determined in terms of Bloom's Digital Taxonomy.
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基于软件的虚拟网络DDoS攻击教育培训平台
由于威胁和漏洞的急剧增加,安全网络的教育和培训是学院面临的一项重要挑战。本研究的目的是在虚拟网络环境中建立一个基于软件的实验平台,以促进分布式拒绝服务攻击的教学。我们采用了以学生的经验为导向的学习理论、反身性观察理论和主动实验理论。这样就可以根据布鲁姆的数字分类法来评估学习目标。从软件的角度来看,已经应用了软件工程的实验范例,使用Scrum作为敏捷方法。在应用程序的开发过程中,我们实现了不同的角色,包括攻击者、学习者和受害者,以重建和理解IP网络上的真实攻击。因此,对于攻击者的角色,我们使用了一个界面来选择攻击类型,而对于学习者的角色,我们设计了一个直观的界面,通过自然语言来呈现,选择可能的防火墙规则。这有助于了解、检测和减轻潜在的攻击。最后,对于受害者的角色,我们包含了一种分析方法,它允许在线识别攻击对计算机系统性能的影响。结果证明了平台的功能,证实了引入的软件满足可用性标准。最后,我们的结果提出了一个网络安全学习,根据布鲁姆的数字分类法确定。
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