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Marthony Taguinod

Researcher at Arizona State University

Publications -  9
Citations -  366

Marthony Taguinod is an academic researcher from Arizona State University. The author has contributed to research in topics: Web application & Common Vulnerabilities and Exposures. The author has an hindex of 6, co-authored 9 publications receiving 323 citations.

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Proceedings ArticleDOI

Policy-driven security management for fog computing: Preliminary framework and a case study

TL;DR: A policy-based management of resources in fog computing is proposed, expanding the current fog computing platform to support secure collaboration and interoperability between different user-requested resources in Fog computing.
Proceedings ArticleDOI

Toward a Moving Target Defense for Web Applications

TL;DR: This paper takes the first steps of applying Moving Target Defense concepts to web applications in order to create effective defensive layers, and discusses the implementation of two MTD approaches, which can mitigate several classes of web application vulnerabilities or exploits.
Proceedings ArticleDOI

A Game Theoretic Approach to Strategy Generation for Moving Target Defense in Web Applications

TL;DR: This work forms an optimization problem that generates an effective switching strategy while considering the cost of switching between different web-stack configurations and develops an automated system for generating attack sets of Common Vulnerabilities and Exposures for input attacker types with predefined capabilities.

Toward a Moving Target Defense for Web Applications (Invited Paper)

TL;DR: In this article, the authors take the first steps of applying Moving Target Defense (MTD) concepts to web applications in order to create effective defensive layers, which can mitigate several classes of web application vulnerabilities or exploits.
Posted Content

Moving Target Defense for Web Applications using Bayesian Stackelberg Games

TL;DR: In this article, the authors propose modeling of a real-world MTD web application as a repeated Bayesian game and formulate an optimization problem that generates an effective switching strategy while considering the cost of switching between different web-stack configurations.