Data Splitting Based Double Layer Encryption for Secure Ciphertext Deduplication in Cloud Storage
Xin Tang, Luchao Jin · 2024
Ciphertext deduplication is an emerging technique to eliminate redundancy in cloud storage with data confidentiality guaranteed. However, the encryption key has to be synchronized among different owners of the same data, which in turn makes the existing deduplication schemes suffer from security problems such as brute-force attacks and the collusion attack. In order to deal with them in a lightweight way, we propose a data splitting based double layer encryption for secure ciphertext deduplication in cloud storage, which is the first work to solve the problem of privacy exposure at a fundamental level. Specifically, we propose a bloom filter based data splitting method and a double layer encryption based deduplication framework. Because of the high collisional property of the feature extraction method, the same content could be extracted from similar data with a great probability. By encrypting it with a shared key, and the remaining part with the secret key of the uploader, the existence privacy is well protected during the process of ciphertext deduplication as a result. According to the experimental results compared with the state-of-the art, the communication and storage overhead can be reduced over 82.28% and 5.55% under the proposed scheme, which shows that secure ciphertext de duplication can be achieved in a lightweiaht way.