| Title | Evaluation Framework for Future Privacy Protection Systems: A Dynamic Identity Ecosystem Approach |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Liau, David, Zaeem, Razieh Nokhbeh, Barber, K. Suzanne |
| Conference Name | 2019 17th International Conference on Privacy, Security and Trust (PST) |
| Keywords | Bayesian network mathematical representation, belief networks, data privacy, dynamic identity ecosystem approach, evaluation framework, Human Behavior, Identity Ecosystem, identity protection strategies, identity theft, information dynamic, Iterative methods, optimal policy, personal identity information, policy evaluation, policy iteration algorithm, privacy, Privacy Policies, privacy protection, privacy protection system, protection game, pubcrawl, Scalability, security of data, Stochastic game |
| Abstract | In this paper, we leverage previous work in the Identity Ecosystem, a Bayesian network mathematical representation of a person's identity, to create a framework to evaluate identity protection systems. Information dynamic is considered and a protection game is formed given that the owner and the attacker both gain some level of control over the status of other PII within the dynamic Identity Ecosystem. We present a policy iteration algorithm to solve the optimal policy for the game and discuss its convergence. Finally, an evaluation and comparison of identity protection strategies is provided given that an optimal policy is used against different protection policies. This study is aimed to understand the evolutionary process of identity theft and provide a framework for evaluating different identity protection strategies and future privacy protection system. |
| DOI | 10.1109/PST47121.2019.8949059 |
| Citation Key | liau_evaluation_2019 |
Evaluation Framework for Future Privacy Protection Systems: A Dynamic Identity Ecosystem Approach