Skip to content
2000
Volume 14, Issue 5
  • ISSN: 2352-0965
  • E-ISSN: 2352-0973

Abstract

Background: In the power Internet of Things (IoT), power consumption data faces the risk of privacy leakage. Traditional privacy-preserving schemes cannot ensure data privacy on the system, as the secret key pairs shall be shared between all the interior nodes once leaked. In addition, the general schemes only support summation algorithms, resulting in a lack of extensibility. Objective: To preserve the privacy of power consumption data, ensure the privacy of secret keys, and support multiple data processing methods we propose an improved power consumption data privacypreserving scheme. Method: Firstly, we have established a power IoT architecture based on edge computing. Then the data is encrypted with the multi-key fully homomorphic algorithm to realize the operation of ciphertext, without the restrictions of calculation type. Through the improved decryption algorithm, ciphertext that can be separately decrypted in cloud nodes is generated, which contributes to reducing communication costs and preventing data leakage. Results: The experimental results show that our scheme is more efficient than traditional schemes in privacy preservation. According to the variance calculation result, the proposed scheme has reached the application standard in terms of computational cost and is feasible for practical operation. Discussion: In the future, we plan to adopt a secure multi-party computation based scheme so that data can be managed locally with homomorphic encryption, so as to ensure data privacy. Conclusion: A privacy-preserving scheme based on improved multi-key fully homomorphic encryption is proposed for the power consumption data, and the experimental results demonstrate the effectiveness and advantage of the proposed scheme.

Loading

Article metrics loading...

/content/journals/raeeng/10.2174/2352096514666210713115244
2021-08-01
2025-07-11
Loading full text...

Full text loading...

/content/journals/raeeng/10.2174/2352096514666210713115244
Loading
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test