Abstract Channels and Their Robust Information-Leakage Ordering

Channels and Their Robust Information-Leakage Ordering Annabelle McIver1, Carroll Morgan2, , Geoffrey Smith3, Barbara Espinoza3, and Larissa Meinicke4 1 Macquarie University [email protected] 2 University of New South Wales and NICTA [email protected] 3 Florida International University {smithg,bespi009}@cis.fiu.edu 4 University of Queensland [email protected] Abstract. The observable output of a probabilistic system that processes a secret input might reveal some information about that input. The system can be modelled as an information-theoretic channel that specifies the probability of each output, given each input. Given a prior distribution on those inputs, entropy-like measures can then quantify the amount of information leakage caused by the channel. But it turns out that the conventional channel representation, as a matrix, contains structure that is redundant with respect to that leakage, such as the labeling of columns, and columns that are scalar multiples of each other. We therefore introduce abstract channels by quotienting over those redundancies. A fundamental question for channels is whether one is worse than another, from a leakage point of view. But it is difficult to answer this question robustly, given the multitude of possible prior distributions and leakage measures. Indeed, there is growing recognition that different leakage measures are appropriate in different circumstances, leading to the recently proposed g-leakage measures, which use gain functions g to model the operational scenario in which a channel operates: the strong g-leakage pre-order requires that channel A never leak more than channel B, for any prior and any gain function. Here we show that, on abstract channels, the strong g-leakage pre-order is antisymmetric, and therefore a partial order. It was previously shown [1] that the strong g-leakage ordering is implied by a structural ordering called composition refinement, which requires that A = BR, for some channel R; but the converse was not established in full generality, left open The observable output of a probabilistic system that processes a secret input might reveal some information about that input. The system can be modelled as an information-theoretic channel that specifies the probability of each output, given each input. Given a prior distribution on those inputs, entropy-like measures can then quantify the amount of information leakage caused by the channel. But it turns out that the conventional channel representation, as a matrix, contains structure that is redundant with respect to that leakage, such as the labeling of columns, and columns that are scalar multiples of each other. We therefore introduce abstract channels by quotienting over those redundancies. A fundamental question for channels is whether one is worse than another, from a leakage point of view. But it is difficult to answer this question robustly, given the multitude of possible prior distributions and leakage measures. Indeed, there is growing recognition that different leakage measures are appropriate in different circumstances, leading to the recently proposed g-leakage measures, which use gain functions g to model the operational scenario in which a channel operates: the strong g-leakage pre-order requires that channel A never leak more than channel B, for any prior and any gain function. Here we show that, on abstract channels, the strong g-leakage pre-order is antisymmetric, and therefore a partial order. It was previously shown [1] that the strong g-leakage ordering is implied by a structural ordering called composition refinement, which requires that A = BR, for some channel R; but the converse was not established in full generality, left open as the so-called Coriaceous Conjecture. Using ideas from [2], we here confirm the Coriaceous Conjecture. Hence the strong g-leakage ordering and composition refinement coincide, giving our partial order both structuraland leakage-testing significance. NICTA is funded by the Australian Government through the Department of Communications and the Australian Research Council through the ICT Centre of Excellence Program. M. Abadi and S. Kremer (Eds.): POST 2014, LNCS 8414, pp. 83–102, 2014. c © Springer-Verlag Berlin Heidelberg 2014