Maximization of Network Robustness Considering the Effect of Escalation and Accumulated Experience of Intelligent Attackers
Date Issued
2008
Date
2008
Author(s)
Chen, Huan-Ting
Abstract
Internet has become much more important and worldwide, but it gives cyber criminals opportunities to crash a network system and conduct other cyber-crimes. Therefore, the issues of network security and robustness have come into notice. It is necessary for a network operator to understand the attacker behavior in order to efficiently allocate his limited budget. In this thesis, we propose a two-level mathematical programming model to describe the network attack and defense scenario. In the inner problem, an attacker’s objective is to compromise multiple core nodes using the minimum total attack cost. During the attack actions, the attacker may gain some experience from previous attacks to further reduce the attack costs in the future. Moreover, he can also pay extra fee to escalate on a compromised node to get higher user privileges, so that he will have higher authority to access more information on the node. We also measure the impact incurred by such information leakage in our model. As a result, the attacker will try to compromise multiple core nodes and collect valuable information, so that the total impact incurred by information leakage will exceed a threshold. Meanwhile, in the outer problem, the network operator of the target network allocates limited defense resources appropriately to maximize the total attack cost of the attacker. We adopt some Simulated Annealing-based algorithms to solve the problem and develop some initial solutions and several kinds of methods for searching neighbor solutions.
Subjects
Network Attack and Defense
Survivability
Multiple Core Nodes
Escalation
Accumulated Experience
Simulated Annealing
Optimization
SDGs
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