Finite State Machines: Preserving Privacy When Data-Mining Cellular Phone Networks

Abstract

During the last several years, researchers have begun to gain access to telecommunications data from cellular-network operators. This development heralds a methodological revolution in fields with complex and extensive data needs and the combination of continuous monitoring and real-time response would enable us to deploy increasingly intelligent infrastructure. However, when used as a research tool, the personal nature of the cellular phone raises new ethical questions regarding the trade-off between personal privacy and the public good. To date, models for mobile privacy have emerged primarily from the field of GPS studies. This article proposes a new approach, the use of Finite State Machines (FSMs), as a technique that is particularly suited to the specific computational and technical constraints of the cellular network.