A Game-Theoretic Decision Model Based on the Privacy Threat Accuracy
College of Engineering
Department of Computer Science
Dr. Hoda Mehrpouyan
Users data privacy is vital to their safety and trust. Protecting users’ data through secure protocols such as homomorphic encryption and garbled circuits is the gold standard of privacy. However, they are often impractical because of their computationally expensive processes. This research proposes a new approach that protects the users' data from privacy threats while using third-party services. The privacy metrics chosen for each communication are based on different parameters such as services requirements, trust, and the data type. As a case study, a Java program was created that when given a set of obfuscated location paths, determines the accuracy of adversary estimation of the user’s location. We developed this program to determine the accuracy of an estimation based on a set of paths and a user set surface area as a baseline for accuracy. This research adds value to the general population and third-party services by maintaining user privacy and decreasing possible work done by not having to encrypt all data.
Hager, Nealon and Joshaghani, Rezvan, "A Game-Theoretic Decision Model Based on the Privacy Threat Accuracy" (2019). 2019 Undergraduate Research and Scholarship Conference. 61.