Abstract
Recommendation systems are active information filtering systems that consist of a processor that can provide recommendations to requesting users (based on the personal ratings that were submitted by all users). In order to produce accurate and personalized recommendations, databases from different agencies can be merged together as a central database. However, due to competition and the possibility of disclosing business strategies, some agencies might not want to disclose the rating information of their customers. In this paper, we propose three secure protocols to compute rank correlation coefficients (Spearman's Rho and Kendall's Tau) for recommender systems. We utilize a semantically secure homomorphic cryptosystem and a ciphertext comparison approach in our protocol design.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1022-1028 |
| Number of pages | 7 |
| Volume | 1 |
| ISBN (Electronic) | 9781467379519 |
| DOIs | |
| Publication status | Published - Dec 2 2015 |
| Event | 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015 - Helsinki, Finland Duration: Aug 20 2015 → Aug 22 2015 |
Conference
| Conference | 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015 |
|---|---|
| Country | Finland |
| City | Helsinki |
| Period | 8/20/15 → 8/22/15 |
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Keywords
- Ciphertext comparison
- Data privacy
- Homomorphic cryptosystem
- Rank correlation coefficient
- Recommender systems
ASJC Scopus subject areas
- Computer Networks and Communications
Cite this
Secure two-party rank correlation computations for recommender systems. / Wong, Kok Seng; Seo, Minjie; Kim, Myung Ho.
Proceedings - 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015. Vol. 1 Institute of Electrical and Electronics Engineers Inc., 2015. p. 1022-1028 7345386.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Secure two-party rank correlation computations for recommender systems
AU - Wong, Kok Seng
AU - Seo, Minjie
AU - Kim, Myung Ho
PY - 2015/12/2
Y1 - 2015/12/2
N2 - Recommendation systems are active information filtering systems that consist of a processor that can provide recommendations to requesting users (based on the personal ratings that were submitted by all users). In order to produce accurate and personalized recommendations, databases from different agencies can be merged together as a central database. However, due to competition and the possibility of disclosing business strategies, some agencies might not want to disclose the rating information of their customers. In this paper, we propose three secure protocols to compute rank correlation coefficients (Spearman's Rho and Kendall's Tau) for recommender systems. We utilize a semantically secure homomorphic cryptosystem and a ciphertext comparison approach in our protocol design.
AB - Recommendation systems are active information filtering systems that consist of a processor that can provide recommendations to requesting users (based on the personal ratings that were submitted by all users). In order to produce accurate and personalized recommendations, databases from different agencies can be merged together as a central database. However, due to competition and the possibility of disclosing business strategies, some agencies might not want to disclose the rating information of their customers. In this paper, we propose three secure protocols to compute rank correlation coefficients (Spearman's Rho and Kendall's Tau) for recommender systems. We utilize a semantically secure homomorphic cryptosystem and a ciphertext comparison approach in our protocol design.
KW - Ciphertext comparison
KW - Data privacy
KW - Homomorphic cryptosystem
KW - Rank correlation coefficient
KW - Recommender systems
UR - http://www.scopus.com/inward/record.url?scp=84966774715&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84966774715&partnerID=8YFLogxK
U2 - 10.1109/Trustcom.2015.478
DO - 10.1109/Trustcom.2015.478
M3 - Conference contribution
VL - 1
SP - 1022
EP - 1028
BT - Proceedings - 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -