Privacy Protection of Digital Speech Based on Homomorphic Encryption

2016 ◽  
pp. 365-376
Author(s):  
Canghong Shi ◽  
Hongxia Wang ◽  
Qing Qian ◽  
Huan Wang
Keyword(s):  
Privacy Protection ◽  
Homomorphic Encryption

A security privacy protection scheme for data collection of smart meters based on homomorphic encryption

Eurocon 2013 ◽  
2013 ◽  
Author(s):  
Niu Yukun ◽  
Tan Xiaobin ◽  
Chen Shi ◽  
Wang Haifeng ◽  
Yu Kai ◽  
...  
Keyword(s):  
Data Collection ◽  
Privacy Protection ◽  
Homomorphic Encryption ◽  
Smart Meters ◽  
Protection Scheme

scholarly journals Privacy Protection Scheme for Data Aggregation in Wireless Sensor Networks Based on PRDA+ Protocol

2018 ◽  
Vol 14 (11) ◽  
pp. 40
Author(s):  
Bohua Guo ◽  
Yanwu Zhang
Keyword(s):  
Data Aggregation ◽  
Privacy Protection ◽  
Random Number ◽  
Polynomial Regression ◽  
Homomorphic Encryption ◽  
Weighted Average ◽  
Base Station ◽  
Wireless Sensor ◽  
Protection Scheme ◽  
Protection Method

<p class="0abstract"><span lang="EN-US">To improve the data aggregation privacy protection scheme in wireless sensor network (WSN), a new scheme is put forward based on the privacy protection of polynomial regression and the privacy protection method based on the homomorphic encryption. The polynomial data aggregation (PRDA+) protocol is also proposed. In this scheme, the node and the base station will pre-deploy a secret key, and the random number generator encrypts the random number for the seed through the private key, which protects the privacy of the data. Then, by comparing the decrypted aggregate data through the correlation between the two metadata, the integrity protection of the data is realized. A weighted average aggregation scheme that can be verified is proposed. In view of the different importance of user information, the corresponding weights are set for each sensor node. EL Gamal digital signature is used to authenticate sensor nodes. The results show that the signature verification algorithm enables the scheme to resist data tampering and data denial, and to trace the source of erroneous data.</span></p>

scholarly journals Verifiable Location-Encrypted Spatial Aggregation Computing for Mobile Crowd Sensing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Kun Niu ◽  
Changgen Peng ◽  
Weijie Tan ◽  
Zhou Zhou ◽  
Yi Xu
Keyword(s):  
Privacy Protection ◽  
Spatial Information ◽  
Homomorphic Encryption ◽  
Security Analysis ◽  
Spatial Aggregation ◽  
Mobile Crowd Sensing ◽  
Sensitive Data ◽  
Sensing Data ◽  
Crowd Sensing ◽  
Mobile Crowd

Benefiting from the development of smart urban computing, the mobile crowd sensing (MCS) network has emerged as momentous communication technology to sense and collect data. The users upload data for specific sensing tasks, and the server completes the aggregation analysis and submits to the sensing platform. However, users’ privacy may be disclosed, and aggregate results may be unreliable. Those are challenges in the trust computation and privacy protection, especially for sensitive data aggregation with spatial information. To address these problems, a verifiable location-encrypted spatial aggregation computing (LeSAC) scheme is proposed for MCS privacy protection. In order to solve the spatial domain distributed user ciphertext computing, firstly, we propose an enhanced-distance-based interpolation calculation scheme, which participates in delegate evaluator based on Paillier homomorphic encryption. Then, we use aggregation signature of the sensing data to ensure the integrity and security of the data. In addition, security analysis indicates that the LeSAC can achieve the IND-CPA indistinguishability semantic security. The efficiency analysis and simulation results demonstrate the communication and computation overhead of the LeSAC. Meanwhile, we use the real environment sensing data sets to verify availability of proposed scheme, and the loss of accuracy (global RMSE) is only less than 5%, which can meet the application requirements.

scholarly journals CONFIDENTIALITY PROTECTIVE USER PROFILE MATCHING IN PUBLIC NETWORKS

2021 ◽  
pp. 152-158
Author(s):  
Maddala Mounika ◽  
K. Tulasi Krishna Kumar Nainar
Keyword(s):  
Privacy Protection ◽  
Data Privacy ◽  
Online Dating ◽  
Homomorphic Encryption ◽  
User Profile ◽  
User Profiles ◽  
User Query ◽  
Profile Matching ◽  
Multiple Servers ◽  
Elgamal Encryption

We consider a scenario where a user queries a user profile database, maintained by a social networking service provider, to identify users whose profiles match the profile specified by the querying user. A typical example of this application is online dating. Most recently, an online dating website, Ashley Madison, was hacked, which results in disclosure of a large number of dating user profiles. This data breach has urged researchers to explore practical privacy protection for user profiles in a social network. Here, we propose a privacy-preserving solution for profile matching in social networks by using multiple servers. Our solution is built on homomorphic encryption and allows a user to find out matching users with the help of multiple servers without revealing to anyone the query and the queried user profiles in clear. Our solution achieves user profile privacy and user query privacy as long as at least one of the multiple servers is honest. Our experiments demonstrate that our solution is practical. KEY WORDS: User profile matching, data privacy protection, ElGamal encryption.

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