科研之友
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摘要
When executing a program or storing data in a medical Internet of Things (mIoT) system, physical side-channels analysis, such as recent-timing, cold-reboot, and virtual-machine attacks, might obtain partial information about internal sensitive medical data/states in memory that the attacker can gain partial privacy information. Leakage-resilient cryptography has led to better implementation of many cryptographic primitives that can be proven secure against attackers who can obtain limited sensitive information about private keys, randomness, and other internal states, and therefore prevents from breaking the security. In this paper, to tolerate the sensitive information leakage in mIoT, we first present a leakage-resilient public-key encryption mechanism that is semantically secure against adaptively chosen-ciphertext attacks in the presence of key leakage under standard decisional Diffie-Hellman assumption. Our construction employs a special universal hashing in multiplicative group to provide an efficient strong extractor, and a key derivation function to derive one or more symmetric keys from a single value. Also, the plaintext space of the scheme is extended to the full domain field of group so as to provide a larger space for the message. We emphasis that our scheme can be deployed in mIoT since the limited power and energy budgets, the communication and computation cost, and the leakage attack are taken into account. Using the first scheme as a building block, we also give a protocol construction to achieve the security resilient to randomness leakage and key leakage. Our schemes feature with a shorter key size and a larger plaintext space. Concretely, the private-key contains only four elements in the finite field, and the allowable key-leakage rate is 25%, which provides a higher leakage rate than Naor Segev (leakage rate is 16.7%) and its variants. It is worth highlighting of the construction resilient to both key leakage and randomness leakage, simultaneously, and is flexible to deploy in easy-to-attack outdoor nodes such as in medical IoT and smart grids, since in these nodes the private keys and randomness are either stored or generated in outdoor privacy-aware environments.
