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
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.