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» Effective diverse and obfuscated attacks on model-based reco...
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RECSYS
2009
ACM
13 years 9 months ago
Effective diverse and obfuscated attacks on model-based recommender systems
Robustness analysis research has shown that conventional memory-based recommender systems are very susceptible to malicious profile-injection attacks. A number of attack models h...
Zunping Cheng, Neil Hurley
AICS
2009
13 years 2 months ago
Robustness Analysis of Model-Based Collaborative Filtering Systems
Collaborative filtering (CF) recommender systems are very popular and successful in commercial application fields. However, robustness analysis research has shown that conventional...
Zunping Cheng, Neil Hurley
DEBU
2008
186views more  DEBU 2008»
13 years 4 months ago
A Survey of Collaborative Recommendation and the Robustness of Model-Based Algorithms
The open nature of collaborative recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Standard memory-...
Jeff J. Sandvig, Bamshad Mobasher, Robin D. Burke
MM
2010
ACM
271views Multimedia» more  MM 2010»
13 years 2 months ago
Large-scale music tag recommendation with explicit multiple attributes
Social tagging can provide rich semantic information for largescale retrieval in music discovery. Such collaborative intelligence, however, also generates a high degree of tags un...
Zhendong Zhao, Xinxi Wang, Qiaoliang Xiang, Andy M...
WORM
2004
13 years 6 months ago
Toward understanding distributed blackhole placement
The monitoring of unused Internet address space has been shown to be an effective method for characterizing Internet threats including Internet worms and DDOS attacks. Because the...
Evan Cooke, Michael Bailey, Zhuoqing Morley Mao, D...