Encrypted Speech Retrieval Scheme Based on Multiuser Searchable Encryption in Cloud Storage

Abstract

In order to solve the problem of multiuser security sharing and privacy protection of the speech data in cloud storage and realize efficient encrypted speech retrieval, an encrypted speech retrieval scheme based on multiuser searchable encryption was proposed. Firstly, the ciphertext-policy attribute-based encryption (CP-ABE) and searchable encryption (SE) are combined to support a multiuser searchable speech encryption scheme, which achieves the encryption and fine-grained access control of the speech data. Secondly, the Mel frequency cepstral coefficient (MFCC) feature of the original speech that is used as the input of the long- and short-term memory network (LSTM) is extracted to perform the deep semantic feature extraction as the speech keywords. Finally, the speech keywords are encrypted to generate a secure index, bound together with the encrypted speech, and then stored in the cloud. During the user retrieving, the keywords of query speech are extracted by utilizing the trained LSTM to generate the search trapdoor of the user and then uploaded to the cloud server, and the Euclidean distance is used for matching the security index with the search trapdoor. In addition, a proxy server is introduced to execute the partial ciphertext decryption operations to reduce computation overhead and storage space. The theoretical analysis and experimental results show that the proposed scheme has higher security and retrieval accuracy and can realize the secure storage of the massive speech data and multiuser data sharing.

Multi-User and multi-keyword verifiable encrypted speech retrieval method based on blockchain

“…To verify the superiority of the retrieval performance of the proposed method, a 384-bit deep hash binary code is used to objectively analyze the retrieval performance from multiple evaluation indexes, and the retrieval performance was compared with existing speech retrieval methods [8,25,28,29,30,40,41] that do not support multi-keyword retrieval. Table 6 shows the performance comparison results of the proposed method with existing speech retrieval methods.…”

“…The retrieval accuracy of Refs. [30,41] is the highest because the dataset used in Ref. [30] has 1000 entries, while the training dataset used in this paper has 10000 entries, resulting in significant loss of speech signals after CPOs and insufficient stability of retrieval accuracy.…”

“…Li et al [29] used the AES algorithm to encrypt speech, the long short-term memory (LSTM) model to improve retrieval accuracy and realized multi-user retrieval through the Diffie-Hellman algorithm to ensure data security. Zhang et al [30] combined encryption of ciphertext-policy attributebased encryption (CP-ABE) and SE to achieve fine-grained access control under multi-user conditions but did not support multi-keyword retrieval. Tahir et al [31] proposed a SE scheme based on fuzzy keyword ranking, which can resist discrimination attacks and protect retrieval privacy based on probability trapdoor, but only supports single keyword retrieval.…”

“…Existing encrypted speech retrieval schemes utilize various easily distinguishable speech features [22], such as perceptual hashing, biological hashing, deep hashing, audio fingerprints, etc. [23][24][25][26][27][28][29][30][31][32], which have relatively stable retrieval efficiency and accuracy. However, speech features' robustness and retrieval accuracy still need to be improved.…”

Two Layer Symmetric Cryptography Algorithm for Protecting Data from燗ttacks

“…Symmetric key cryptography is also known as secret-key cryptography. It is fast as compared to asymmetric key cryptography [22]. When the data is transmitted, the data is converted to a non-readable text by the symmetric cryptography mechanism.…”