2012 Symposium Posters

Posters > 2012

Create Moving Target Defense in Static Networks by Learning from Botnets


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Project Members
Feng Li, IUPUI; Xukai Zou, IUPUI; Wei Peng, IUPUI
Abstract
Network disruptive attacks, such as Distributed Denial-of-service (DDos) attacks, routing attacks, and Man-in-the-middle attacks, are a major impediment in the development of networks. The static nature of network configuration enables adversaries attack these networks to effectively discover and disrupt network resources remotely. Similar to network disruptive threats, the root of many security threats is the static or relatively stable status of the system, which can be easily exploited by attackers. A recent census regarding the game-changing theme of cyber security leads us to Moving Target Defense (MTD). The MTD aims to change the uneven cost between attackers and defenders caused by the static systems. Unfortunately, what to do and how to do it currently are not clear for MTD in network systems, even though there are several recent innovative security research attempts on host and software dynamics to increase the cost of the attacker. Thus, this project will address this new, yet challenging, issue of MTD in the static network systems. Although the research on MTD in static networks is in its infant stage, the attackers have actually accumulated valuable experiences and ideas in this area. The history of the botnet, which is a collection of compromised nodes (computers, which are also known as bots) connected through a network, vividly represents the evolution from static to `moving' networks. Therefore, this project starts with a thorough investigation on the moving techniques used in the recent botnets. The objective of this research is to design an innovative moving target defense framework that will improve resiliency and harden existing static networks by learning from recent botnets. This framework will make the static network move to the disadvantage of the attackers, by increasing an attacker's uncertainty, difficulty, and cost in the network disruptive attacks.