Secure Computation of Maximum and Minimum Values in Data Aggregation Based on Cloud Computing

Data aggregation is the process of combining multiple data points or data sets into a larger data set. Through calculation, statistics or other means, it can provide higher level data information, which is widely used in different data types and fields such as database query, data analysis, data mining and data processing. In data processing scenarios, data aggregation functions play a key role. They are used to perform aggregate calculations on data, such as finding the maximum, minimum, and maximum difference of multiple data. However, it is important to pay special attention to protecting sensitive information and privacy when performing data aggregation. Aiming at this problem, based on the threshold NTRU encryption algorithm with additive homomorphism, combining the vector encoding method and the ciphertext re-randomization method, this paper proposes a secure calculation protocol for the maximum value, minimum value and maximum difference in multi-party data sets under the semi-honest model. To verify the security of the proposed protocol, we use the simulation paradigm approach for security proof and show that the protocol can resist the attack of the maximum number of colluders. Through theoretical analysis and simulation experiments, we show the high efficiency of the proposed scheme, and prove that the protocol has practical value.