Secure Recommendation
Secure Recommendation is a recommendation approach that belongs to the class of trust-preserving computational methods, distinguished by its explicit integration of security mechanisms to protect against adversarial attacks, data poisoning, and privacy breaches during the recommendation process.
207
Publications
10.6K
Citations
592
Authors
271
Institutions
Publications per year
2017–2026
111
Parents
207
Toward trustworthy recommender systems
Bamshad Mobasher, Robin Burke, Runa Bhaumik et al. · ACM Transactions on Internet Technology · 2007 · 465 citations
Shilling attacks against recommender systems: a comprehensive survey
İhsan Güneş, Cihan Kaleli, Alper Bilge et al. · Artificial Intelligence Review · 2012 · 327 citations
Classification features for attack detection in collaborative recommender systems
Robin Burke, Bamshad Mobasher, Chad Williams et al. · 2006 · 251 citations
1–5 of 207
592
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271

DePaul University
Chicago, United States
8 h-index
28 publications
4.7K citations

Chongqing University
Chongqing, China
7 h-index
25 publications
1.2K citations

Yanshan University
Qinhuangdao, China
6 h-index
16 publications
626 citations

City University of Hong Kong
Hong Kong, Hong Kong
5 h-index
7 publications
232 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
8 publications
501 citations

Macquarie University
Sydney, Australia
5 h-index
7 publications
135 citations

Delft University of Technology
Delft, The Netherlands
5 h-index
10 publications
900 citations
Nanjing University of Finance and Economics
Nanjing, China
5 h-index
12 publications
810 citations
1–8 of 271
7 publications · 157 citations
7
h-index
Repository · 6 publications · 330 citations
6
h-index
FGCS · 4 publications · 146 citations
5
h-index
5 publications · 520 citations
5
h-index
4 publications · 270 citations
4
h-index
1–5