Information Leakage in Index Coding With Sensitive and Non-Sensitive Messages
Yucheng Liu, Lawrence Ong, Phee Lep Yeoh, Parastoo Sadeghi, Jörg Kliewer, Sarah J. Johnson · 2022 IEEE International Symposium on Information Theory (ISIT) · 2022
Information leakage to a guessing adversary in index coding is studied, where some messages in the system are sensitive and others are not. The non-sensitive messages can be used by the server like secret keys to mitigate leakage of the sensitive messages to the adversary. We construct a deterministic linear coding scheme, developed from the rank minimization method based on fitting matrices (Bar-Yossef et al. 2011). The linear scheme leads to a novel upper bound on the optimal information leakage rate, which is proved to be tight over all deterministic scalar linear codes. We also derive a converse result from a graph-theoretic perspective, which holds in general over all deterministic and stochastic coding schemes.