Research on privacy fraud detection of Logistic regression based on homomorphic encryption

Abstract

Fraud detection is an integral part of financial security monitoring tool; however, the traditional fraud detection method cannot detect the existing malicious fraud, and the clouds will produce data revealing that the risk of fraud detection system can not protect the privacy of detected object, so the fraud detection data privacy security becomes a significant problem,Homomorphic encryption as a demonstrable cryptography cloud privacy computing outsourcing scheme can ensure that cloud computing can perform ciphertext polynomial calculation under the dense state data without direct contact with the accurate data of users, so as to ensure data privacy security. Aiming at the data privacy security problems in the process of fraud detection, this paper combined homomorphic encryption and Logistic regression fraud detection technology to study the Logistic regression fraud detection algorithm under homomorphic ciphertext and constructed a cloud privacy fraud detection method based on customer service and cloud computing services. CKKS encryption scheme is used to encrypt the fraud data set and realize the Logistic regression fraud detection algorithm under ciphertext. The experiment proves that the difference between the fraud detection accuracy on ciphertext and plaintext is less than 3%. Under the condition of ensuring the privacy of sensitive data to be detected, the effect of the fraud detection model is not affected.