Data mining standards initiatives
Communications of the ACM - Evolving data mining into solutions for insights
An economic answer to unsolicited communication
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Combining email models for false positive reduction
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
"May I borrow Your Filter?" Exchanging Filters to Combat Spam in a Community
AINA '06 Proceedings of the 20th International Conference on Advanced Information Networking and Applications - Volume 02
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Understanding the network-level behavior of spammers
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Applying lazy learning algorithms to tackle concept drift in spam filtering
Expert Systems with Applications: An International Journal
Personalized Spam Filtering with Semi-supervised Classifier Ensemble
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Distributed quota enforcement for spam control
NSDI'06 Proceedings of the 3rd conference on Networked Systems Design & Implementation - Volume 3
Exploiting machine learning to subvert your spam filter
LEET'08 Proceedings of the 1st Usenix Workshop on Large-Scale Exploits and Emergent Threats
Partitioned logistic regression for spam filtering
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
A Comparative Impact Study of Attribute Selection Techniques on Naïve Bayes Spam Filters
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
Spamalytics: an empirical analysis of spam marketing conversion
Proceedings of the 15th ACM conference on Computer and communications security
A collaborative anti-spam system
Expert Systems with Applications: An International Journal
Review: A review of machine learning approaches to Spam filtering
Expert Systems with Applications: An International Journal
Data strip mining for the virtual design of pharmaceuticals with neural networks
IEEE Transactions on Neural Networks
Using sensitivity analysis and visualization techniques to open black box data mining models
Information Sciences: an International Journal
| Hi-index | 12.05 |
This paper presents a novel spam filtering technique called Symbiotic Filtering (SF) that aggregates distinct local filters from several users to improve the overall performance of spam detection. SF is an hybrid approach combining some features from both Collaborative (CF) and Content-Based Filtering (CBF). It allows for the use of social networks to personalize and tailor the set of filters that serve as input to the filtering. A comparison is performed against the commonly used Naive Bayes CBF algorithm. Several experiments were held with the well-known Enron data, under both fixed and incremental symbiotic groups. We show that our system is competitive in performance and is robust against both dictionary and focused contamination attacks. Moreover, it can be implemented and deployed with few effort and low communication costs, while assuring privacy.