Convergence properties of functional estimates for discrete distributions
Random Structures & Algorithms - Special issue on analysis of algorithms dedicated to Don Knuth on the occasion of his (100)8th birthday
Shilling recommender systems for fun and profit
Proceedings of the 13th international conference on World Wide Web
Collaborative recommendation: A robustness analysis
ACM Transactions on Internet Technology (TOIT)
Aberrant Behavior Detection in Time Series for Network Monitoring
LISA '00 Proceedings of the 14th USENIX conference on System administration
Mining anomalies using traffic feature distributions
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Preventing shilling attacks in online recommender systems
Proceedings of the 7th annual ACM international workshop on Web information and data management
HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Segment-Based Injection Attacks against Collaborative Filtering Recommender Systems
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Analysis of a low-dimensional linear model under recommendation attacks
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Analysis and detection of segment-focused attacks against collaborative recommendation
WebKDD'05 Proceedings of the 7th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
Trustworthy knowledge diffusion model based on risk discovery on peer-to-peer networks
Expert Systems with Applications: An International Journal
Dependable filtering: Philosophy and realizations
ACM Transactions on Information Systems (TOIS)
Collaborative filtering based on significances
Information Sciences: an International Journal
HySAD: a semi-supervised hybrid shilling attack detector for trustworthy product recommendation
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Defending imitating attacks in web credibility evaluation systems
Proceedings of the 22nd international conference on World Wide Web companion
| Hi-index | 0.00 |
Recent research has identified significant vulnerabilities in recommender systems. Shilling attacks, in which attackers introduce biased ratings in order to influence future recommendations, have been shown to be effective against collaborative filtering algorithms. We postulate that the distribution of item ratings in time can reveal the presence of a wide range of shilling attacks given reasonable assumptions about their duration. To construct a time series of ratings for an item, we use a window size of k to group consecutive ratings for the item into disjoint windows and compute the sample average and sample entropy in each window. We derive a theoretically optimal window size to best detect an attack event if the number of attack profiles is known. For practical applications where this number is unknown, we propose a heuristic algorithm that adaptively changes the window size. Our experimental results demonstrate that monitoring rating distributions in time series is an effective approach for detecting shilling attacks.