Is Privacy Controllable?

TL;DR

This paper explores whether privacy can be controlled by reframing privacy as control over information and applying control theory to model user actions and information disclosure. It proposes a conceptual model with a human controller, an actuator, a privacy level $P$, and a utility output $Output$, analyzing both open-loop and closed-loop configurations and introducing a Pareto frontier to capture trade-offs between benefits and costs. The analysis highlights time delays, feedback reliability, and multiple subsystems, and identifies controllability issues summarized in Table $tab1$, illustrating when privacy states are difficult to steer. While not exhaustive, the work connects control-theoretic notions to existing privacy literature, outlines directions toward feedback-enabled privacy mechanisms and privacy-by-design, and discusses practical limitations and opportunities for empirical validation.

Abstract

One of the major views of privacy associates privacy with the control over information. This gives rise to the question how controllable privacy actually is. In this paper, we adapt certain formal methods of control theory and investigate the implications of a control theoretic analysis of privacy. We look at how control and feedback mechanisms have been studied in the privacy literature. Relying on the control theoretic framework, we develop a simplistic conceptual control model of privacy, formulate privacy controllability issues and suggest directions for possible research.

Figures (3)

• Figure 1: Privacy comfort as utility based on costs and benefits curves
• Figure 2: Privacy comfort as Pareto-optimal frontier
• Figure 3: A block diagram representation of the privacy control model