International Association
for Cryptologic Research

XCB, a tweakable enciphering mode, is part of IEEE Std. 1619.2 for shared storage media. We show that all versions of XCB are not secure through three plaintext recovery attacks. A key observation is that XCB behaves like an LRW1-type tweakable block cipher for single-block messages, which lacks CCA security. The first attack targets one-block XCB, using three queries to recover the plaintext. The second one requires four queries to recover the plaintext that excludes one block. The last one requires seven queries to recover the full plaintext. The first attack applies to any scheme that follows the XCB structure, whereas the latter two attacks work on all versions of XCB, exploiting the separable property of the underlying universal hash function. To address these flaws, we propose the XCB* structure, an improved version of XCB that adds only two XOR operations. We prove that XCB* is STPRP-secure when using AXU hash functions, SPRPs, and a secure random-IV-based stream cipher.

Random number generators (RNGs) are essential for cryptographic applications. In most practical applications, the randomness of RNGs is provided by entropy sources. If the randomness is less than the expected, the security of cryptographic applications could be undermined. Accurate entropy estimation is a critical method for the evaluation of RNG security, and significant overestimation and underestimation are both inadvisable. The NIST Special Publication 800-90B is one of the most common certifications for entropy estimation. It makes no assumption of the entropy source and provides min-entropy estimation results by a set of entropy estimators. It estimates the entropy sources in two tracks: the IID (independent and identically distributed) track and non-IID track. In practice, non-IID entropy sources are more common, as physical phenomenon, sampling process or external perturbation could cause the dependency of the outputs. In this paper, we prove that the Collision Estimate and the Compression Estimate in non-IID track could provide significant underestimates in theory. In order to accurately estimate the min-entropy of non-IID sources, we provide a formula of minentropybased on conditional probability, and propose a new estimator to approximate the result of this formula. Finally, we perform experiments to compare our estimator with the NIST estimators using simulated non-IID data. Results show that our estimator gives close estimates to the real min-entropy.