Using Granule to Search Privacy Preserving Voice in Home IoT Systems

被引：12

作者：

Li, Wei ^{[1
]}

Chen, Yumin ^{[1
]}

Hu, Huosheng ^{[2
]}

Tang, Chao ^{[3
]}

机构：

[1] Xiamen Univ Technol, Sch Comp & Informat Engn, Xiamen 361024, Peoples R China

[2] Univ Essex, Sch Comp Sci & Elect Engn, Colchester CO4 3SQ, Essex, England

[3] Hefei Univ, Dept Comp Sci & Technol, Hefei 230601, Peoples R China

来源：

IEEE ACCESS | 2020年 / 8卷

基金：

中国国家自然科学基金;

关键词：

Fuzzy search; granule computing; k-nearest neighbor; searchable encrypted voice; obfuscation function; ATTRIBUTE REDUCTION; ENCRYPTION; NETWORKS;

D O I：

10.1109/ACCESS.2020.2972975

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The Home IoT Voice System (HIVS) such as Amazon Alexa or Apple Siri can provide voice-based interfaces for people to conduct the search tasks using their voice. However, how to protect privacy is a big challenge. This paper proposes a novel personalized search scheme of encrypting voice with privacy-preserving by the granule computing technique. Firstly, Mel-Frequency Cepstrum Coefficients (MFCC) are used to extract voice features. These features are obfuscated by obfuscation function to protect them from being disclosed the server. Secondly, a series of definitions are presented, including fuzzy granule, fuzzy granule vector, ciphertext granule, operators and metrics. Thirdly, the AES method is used to encrypt voices. A scheme of searchable encrypted voice is designed by creating the fuzzy granule of obfuscation features of voices and the ciphertext granule of the voice. The experiments are conducted on corpus including English, Chinese and Arabic. The results show the feasibility and good performance of the proposed scheme.

引用

页码：31957 / 31969

页数：13

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