| Title | NMF-Based Privacy-Preserving Collaborative Filtering on Cloud Computing |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Li, Tao, Ren, Yongzhen, Ren, Yongjun, Wang, Lina, Wang, Lingyun, Wang, Lei |
| Conference Name | 2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) |
| Keywords | cloud computing, Collaboration, collaborative filtering, data privacy, data protection, Hybrid algorithm, information science, Matrix decomposition, matrix elements, Metrics, nmf, NMF-based privacy-preserving collaborative filtering, privacy, privacy protection algorithm, Privacy-preserving, pubcrawl, recommendation process, recommendation system, recommender system, recommender systems, Resiliency, Scalability, security of data, Servers, user personal information security, user privacy data, user privacy in the cloud |
| Abstract | The security of user personal information on cloud computing is an important issue for the recommendation system. In order to provide high quality recommendation services, privacy of user is often obtained by untrusted recommendation systems. At the same time, malicious attacks often use the recommendation results to try to guess the private data of user. This paper proposes a hybrid algorithm based on NMF and random perturbation technology, which implements the recommendation system and solves the protection problem of user privacy data in the recommendation process on cloud computing. Compared with the privacy protection algorithm of SVD, the elements of the matrix after the decomposition of the new algorithm are non-negative elements, avoiding the meaninglessness of negative numbers in the matrix formed by texts, images, etc., and it has a good explanation for the local characteristics of things. Experiments show that the new algorithm can produce recommendation results with certain accuracy under the premise of protecting users' personal privacy on cloud computing. |
| DOI | 10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00098 |
| Citation Key | li_nmf-based_2019 |
NMF-Based Privacy-Preserving Collaborative Filtering on Cloud Computing