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http://dx.doi.org/10.9708/jksci.2020.25.06.065

Privacy-Preserving Aggregation of IoT Data with Distributed Differential Privacy  

Lim, Jong-Hyun (Dept. of Computer Science, Sangmyung University)
Kim, Jong-Wook (Dept. of Computer Science, Sangmyung University)
Publication Information
Journal of the Korea Society of Computer and Information / v.25, no.6, 2020 , pp. 65-72 More about this Journal
Abstract
Today, the Internet of Things is used in many places, including homes, industrial sites, and hospitals, to give us convenience. Many services generate new value through real-time data collection, storage and analysis as devices are connected to the network. Many of these fields are creating services and applications that utilize sensors and communication functions within IoT devices. However, since everything can be hacked, it causes a huge privacy threat to users who provide data. For example, a variety of sensitive information, such as personal information, lifestyle patters and the existence of diseases, will be leaked if data generated by smarwatches are abused. Development of IoT must be accompanied by the development of security. Recently, Differential Privacy(DP) was adopted to privacy-preserving data processing. So we propose the method that can aggregate health data safely on smartwatch platform, based on DP.
Keywords
Internet of Things; Privacy-Preserving Aggregation; Distributed Differential Privacy; Smart Healthcare; Homomorphic Encryption; Paillier Cryptosystem;
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