Privacy-Utility Tradeoff Based on α-lift

Information density and its exponential form, known as lift, play a central role in information privacy leakage measures. α-lift is the power-mean of lift, which is tunable between the worst-case measure max-lift (α=∞) and more relaxed versions (α<∞). This paper investigates the optimization problem of the privacy-utility tradeoff where α-lift and mutual information are privacy and utility measures, respectively. Due to the nonlinear nature of α-lift for α<∞, finding the optimal solution is challenging. Therefore, we propose a heuristic algorithm to estimate the optimal utility for each value of α, inspired by the optimal solution for α=∞. In proposing the algorithm, we prove and use the convexity of α-lift with respect to the lift.