Abstract
With the wide application of Internet of Things (IoT), a huge number of data are collected from IoT networks and are required to be processed, such as data mining. Although it is popular to outsource storage and computation to cloud, it may invade privacy of participants’ information. Cryptography-based privacy-preserving data mining has been proposed to protect the privacy of participating parties’ data for this process. However, it is still an open problem to handle with multiparticipant’s ciphertext computation and analysis. And these algorithms rely on the semihonest security model which requires all parties to follow the protocol rules. In this paper, we address the challenge of outsourcing ID3 decision tree algorithm in the malicious model. Particularly, to securely store and compute private data, the two-participant symmetric homomorphic encryption supporting addition and multiplication is proposed. To keep from malicious behaviors of cloud computing server, the secure garbled circuits are adopted to propose the privacy-preserving weight average protocol. Security and performance are analyzed.
Highlights
In the modern Internet of Things (IoT), huge data are collected from sensor-networks and need to be provided for analysis by high-effective techniques, such as data mining
The privacy-preserving data mining (PPDM) based on encryption method has emerged as a solution to this problem
We propose the Secure Equivalent Testing (SET) protocol to calculate the number of items for each attribute value based on the encrypted data
Summary
In the modern Internet of Things (IoT), huge data are collected from sensor-networks and need to be provided for analysis by high-effective techniques, such as data mining. Cryptography-based privacy-preserving data mining supporting one-party outsourcing has been studied [3, 4], with homomorphic encryption. They can intentionally tamper with the data, suspend the protocol anytime during the execution of the protocol, and so on To solve this problem, this paper combines the noncontact commitment and confusion circuit mechanism, studies the average computing protocol based on confusion circuit, and proposes the framework of a secure cryptography-based two-participant protocol with data storage and computation outsourcing. Each data owner has a horizontally distributed private database that is encrypted before being outsourced to the cloud for storage and computation. We propose the Secure Equivalent Testing (SET) protocol to calculate the number of items for each attribute value based on the encrypted data. To execute comparison over ciphertext, we adopt the Secure Minimum out of 2 Numbers (SMIN2) protocol
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