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» Preventing shilling attacks in online recommender systems
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AAAI
2007
13 years 9 months ago
Unsupervised Shilling Detection for Collaborative Filtering
Collaborative Filtering systems are essentially social systems which base their recommendation on the judgment of a large number of people. However, like other social systems, the...
Bhaskar Mehta
ETRICS
2006
13 years 11 months ago
Do You Trust Your Recommendations? An Exploration of Security and Privacy Issues in Recommender Systems
Recommender systems are widely used to help deal with the problem of information overload. However, recommenders raise serious privacy and security issues. The personal information...
Shyong K. Lam, Dan Frankowski, John Riedl
DEBU
2008
165views more  DEBU 2008»
13 years 7 months ago
A Survey of Attack-Resistant Collaborative Filtering Algorithms
With the increasing popularity of recommender systems in commercial services, the quality of recommendations has increasingly become an important to study, much like the quality o...
Bhaskar Mehta, Thomas Hofmann
HICSS
2003
IEEE
118views Biometrics» more  HICSS 2003»
14 years 22 days ago
On-Line Intrusion Detection and Attack Prevention Using Diversity, Generate-and-Test, and Generalization
We have built a system for protecting Internet services to securely connected, known users. It implements a generate-and-test approach for on-line attack identification and uses s...
James C. Reynolds, James E. Just, Larry A. Clough,...
ACNS
2005
Springer
88views Cryptology» more  ACNS 2005»
14 years 1 months ago
Strengthening Password-Based Authentication Protocols Against Online Dictionary Attacks
Passwords are one of the most common cause of system break-ins, because the low entropy of passwords makes systems vulnerable to brute force guessing attacks (dictionary attacks). ...
Peng Wang, Yongdae Kim, Vishal Kher, Taekyoung Kwo...