Strengthening MT6D Defenses with LXC-Based Honeypot Capabilities

Moving Target IPv6 Defense (MT6D) imparts radio-frequency hopping behavior to IPv6 networks by having participating nodes periodically hop onto new addresses while giving up old addresses. Our previous research efforts implemented a solution to identify and acquire these old addresses that are being discarded by MT6D hosts on a local network besides being able to monitor and visualize the incoming traffic on these addresses. This was essentially equivalent to forming a darknet out of the discarded MT6D addresses, but the solution presented in the previous research effort did not include database integration for it to scale and be extended. This paper presents a solution with a new architecture that not only extends the previous solution in terms of automation and database integration but also demonstrates the ability to deploy a honeypot on a virtual LXC (Linux Container) on-demand based on any interesting traffic pattern observed on a discarded address. The proposed architecture also allows an MT6D host to query the solution database for network activity on its relinquished addresses as a JavaScript Object Notation (JSON) object. This allows an MT6D host to identify suspicious activity on its discarded addresses and strengthen the MT6D scheme parameters accordingly. We have built a proof-of-concept for the proposed solution and analyzed the solution’s feasibility and scalability

A theory for understanding and quantifying moving target defense

Doctor of PhilosophyComputing and Information SciencesScott A. DeLoachThe static nature of cyber systems gives attackers a valuable and asymmetric advantage - time. To eliminate this asymmetric advantage, a new approach, called Moving Target Defense (MTD) has emerged as a potential solution. MTD system seeks to proactively change system configurations to invalidate the knowledge learned by the attacker and force them to spend more effort locating and re-locating vulnerabilities. While it sounds promising, the approach is so new that there is no standard definition of what an MTD is, what is meant by diversification and randomization, or what metrics to define the effectiveness of such systems. Moreover, the changing nature of MTD violates two basic assumptions about the conventional attack surface notion. One is that the attack surface remains unchanged during an attack and the second is that it is always reachable. Therefore, a new attack surface definition is needed. To address these issues, I propose that a theoretical framework for MTD be defined. The framework should clarify the most basic questions such as what an MTD system is and its properties such as adaptation, diversification and randomization. The framework should reveal what is meant by gaining and losing knowledge, and what are different attack types. To reason over the interactions between attacker and MTD system, the framework should define key concepts such as attack surface, adaptation surface and engagement surface. Based on that, this framework should allow MTD system designers to decide how to use existing configuration choices and functionality diversification to increase security. It should allow them to analyze the effectiveness of adapting various combinations of different configuration aspects to thwart different types of attacks. To support analysis, the frame- work should include an analytical model that can be used by designers to determine how different parameter settings will impact system security