Research

The following research was performed during my time as a Computer Science Graduate Student at the University of Denver during the 2012-2014 school years.

Secure Map Generation for Multiplayer, Turn-Based Strategy Games by Stephen Rice & Chris GauthierDickey

Abstract: In strategy games, players compete against each other on randomly generated maps in an attempt to prove their superior skill. Traditionally, these games rely on a client/server architecture with one player fulfilling the role of server and holding responsibility for the map generation process. We propose, analyze and evaluate a method that allows these maps to be created in a peer-to-peer fashion and thus reduce the potential for cheating. We provide an example map generation program that puts these concepts into action and demonstrate how it can be extended and customized for any game. Finally, we analyze the performance of our methods and demonstrate how it can be scaled from a two player game to an n-player game.

Download: Paper | Appendix A: Source Code

Please visit Chris GauthierDickey's website for more research on applications of peer-to-peer technologies.

Private Information Leakage on the Mobile Web by Amanda Kirk, Stephen Rice, Zach Azar & Yipu Wang

Abstract: While leakage of private information to third-parties while browsing the web is well researched in academia [4] [5] [6], relatively little exploration has been made into the realm of privacy leakage on the mobile web. Building off of previous research by Krishnamurthy et al., [1] we explore the leakage of private information on non- online social networks (non-OSN’s) via a mobile web browser. We select a subset of the categories from Krishnamurthy’s previous, desktop-focused work and investigate five sites (per category) for provable private information leakage via a mobile device. Utilizing a variety of mobile devices and a PC running network analysis software, we crawl each site under the persona of a normal user. We perform standard actions such as creating accounts, navigating pages or performing searches, as well as site specific functions like sending dating messages on relationship web sites. Once we collect data for each crawl, we quantify the leakage we observe and compare our mobile-centered findings to known results on desktop web leakage. We find that our results for private information leakage on the mobile platform are comparable to Krishnamurthy’s results from his previous study on traditional private information leakage via desktop web browsing for various non-OSN categories.

Download: Paper | Presentation

This research was performed as part of Rinku Dewri's Foundations in Information Privacy class.