Title
A Game Theoretic Approach to Strategy Generation for Moving Target Defense in Web Applications.
Abstract
The present complexity in designing web applications makes software security a difficult goal to achieve. An attacker can explore a deployed service on the web and attack at his/her own leisure. Moving Target Defense (MTD) in web applications is an effective mechanism to nullify this advantage of their reconnaissance but the framework demands a good switching strategy when switching between multiple configurations for its web-stack. To address this issue, we propose the modeling of a real world MTD web application as a repeated Bayesian game. We formulate an optimization problem that generates an effective switching strategy while considering the cost of switching between different web-stack configurations. To use this model for a developed MTD system, we develop an automated system for generating attack sets of Common Vulnerabilities and Exposures (CVEs) for input attacker types with predefined capabilities. Our framework obtains realistic reward values for the players (defenders and attackers) in this game by using security domain expertise on CVEs obtained from the National Vulnerability Database (NVD). We also address the issue of prioritizing vulnerabilities that when fixed, improves the security of the MTD system. Lastly, we demonstrate the robustness of our proposed model by evaluating its performance when there is uncertainty about input attacker information.
Year
DOI
Venue
2017
10.5555/3091125.3091155
AAMAS
Field
DocType
Citations 
Security domain,Common Vulnerabilities and Exposures,National Vulnerability Database,Computer science,Software security assurance,Robustness (computer science),Web application,Bayesian game,Optimization problem,Distributed computing
Conference
4
PageRank 
References 
Authors
0.42
16
7
Name
Order
Citations
PageRank
Sailik Sengupta1227.00
Satya Gautam Vadlamudi21338.94
Subbarao Kambhampati33453450.74
Adam Doupé435733.14
Ziming Zhao532230.52
Marthony Taguinod6674.27
Gail-Joon Ahn73012203.39