We study the achievable level of information-theoretic security for symmetric encryption under low-entropy keys (e.g., passwords and biometrics), where classical notions such as perfect secrecy and entropic security are usually unattainable. We consider a model in which messages and keys are drawn independently from distributions . Prior work on homophonic ciphers (HC) and honey encryption (HE) suggests that randomized encryption tailored to can improve security. We ask what the optimal achievable level is among all symmetric encryption schemes, and which necessary and/or sufficient conditions on encryption schemes characterize when this level can be achieved.
For key confidentiality (KC), we show that the optimal achievable level is , i.e., the ciphertext reveals only negligible information about the key. Moreover, this holds if and only if, informally, decrypting under any key induces sampling of messages according to . HC and HE following this principle achieve this level, whereas -agnostic schemes do not in general. For message confidentiality (MC) against message-recovery attacks, we show that the optimal bound on the adversary’s success probability is , where is the baseline success probability of guessing the most likely message or key under . We construct a scheme tailored to that attains , and prove that -agnostic schemes (including HC and HE) cannot in general achieve this bound. Our results on necessary and/or sufficient conditions characterize fundamental principles governing the use of randomness in probabilistic encryption.
The main technical challenge is to handle a discretization-induced negligible error that must be propagated throughout the derivation of our bounds and necessary and/or sufficient conditions. To facilitate the analysis, we introduce a continuous-ciphertext framework that separates structural constraints from discretization error.