TY - GEN
T1 - Application of Differential Privacy for Collaborative Filtering Based Recommendation System
T2 - 12th International Symposium on Parallel Architectures, Algorithms and Programming, PAAP 2021
AU - Hou, Dongkun
AU - Zhang, Jie
AU - Ma, Jieming
AU - Zhu, Xiaohui
AU - Man, Ka Lok
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Collaborative Filtering (CF) is the main technology in recommendation systems. It requires more users' private information to predict personal preferences, so exists the risk of privacy disclosure. Differential Privacy (DP) is a powerful privacy-preserving approach, and it has been widely applied in CF-based recommendation system. However, a comprehensive summary of DP in CF-based recommendation system is lack although many privacy-preserving CF algorithms have been proposed. This paper reviews the existing research based on the principle of DP and the application of CF algorithms. We firstly introduce the theoretical basis and the mechanism employed by DP. Then, two types of CF-based recommendation algorithms with DP are summarized including memory-based and model-based algorithms. Moreover, the optimized CF algorithms with DP in specific application fields are illustrated.
AB - Collaborative Filtering (CF) is the main technology in recommendation systems. It requires more users' private information to predict personal preferences, so exists the risk of privacy disclosure. Differential Privacy (DP) is a powerful privacy-preserving approach, and it has been widely applied in CF-based recommendation system. However, a comprehensive summary of DP in CF-based recommendation system is lack although many privacy-preserving CF algorithms have been proposed. This paper reviews the existing research based on the principle of DP and the application of CF algorithms. We firstly introduce the theoretical basis and the mechanism employed by DP. Then, two types of CF-based recommendation algorithms with DP are summarized including memory-based and model-based algorithms. Moreover, the optimized CF algorithms with DP in specific application fields are illustrated.
KW - Collaborative Filtering
KW - Differential Privacy
KW - Literature Review
KW - Recommendation System
KW - Survey
UR - https://www.scopus.com/pages/publications/85126844451
U2 - 10.1109/PAAP54281.2021.9720452
DO - 10.1109/PAAP54281.2021.9720452
M3 - Conference Proceeding
AN - SCOPUS:85126844451
T3 - Proceedings - International Symposium on Parallel Architectures, Algorithms and Programming, PAAP
SP - 97
EP - 101
BT - 2021 12th International Symposium on Parallel Architectures, Algorithms and Programming, PAAP 2021
PB - IEEE Computer Society
Y2 - 10 December 2021 through 12 December 2021
ER -