跨系统协同过滤推荐算法的隐私保护技术研究.

To solve the privacy security problem of the recommendation algorithm between systems,this paper developed a secure computation model based on the theory of secure multi-party computation. The model used LBlock,a lightweight block cipher algorithm,to encrypt the provided data by the third part,and used RSA public key cryptosystem to manage keys of LBlock. Applying this model to the collaborative filtering between systems with randomized perturbation techniques,the paper developed a new algorithm whose calculation method of similarity could protect the system from the attack of artificial users. It used secure vector to prevent the untrusted third party from colluding. Experiments show that algorithm not only has stronger ability to protect the user’s privacy disclosing to the system which is cooperated,but also has better quality of recommendation. [ABSTRACT FROM AUTHOR]