A novel hashing-inverted index for secure content-based retrieval with massive encrypted speeches.

The content-based speech retrieval scheme using the hash technique boasts high accuracy; however, its index structures, such as the hash table, suffer from high space cost, low search efficiency, and security concerns. Moreover, implementing keyword search or ranking retrieval is a challenging task. We suggest a secure content-based retrieval scheme that utilizes a novel hashing-inverted index to address these issues. This method converts hash sequences into keyword sequences by employing a keyword hash template to establish a hashing-inverted index. The index table and all keywords are encrypted using a lightweight homomorphic encryption scheme to ensure security. When the data user submits a trapdoor of a spoken query, the cloud server performs homomorphic Hamming distance calculation and homomorphic location calculation, which makes the search process much more secure. The experimental results show that our index is lighter, easy to maintain, and expand. The retrieval efficiency is also higher. Security analysis proves that the privacy of the index and speeches is preserved. Generally, our scheme is accurate, efficient, and secure for the massive spoken audio data. [ABSTRACT FROM AUTHOR]