A Linguistics-Based Attack on Personalised Statistical E-mail Classifiers


Henry Stern
Justin Mason
Michael Shepherd

Author Addresses: 

Faculty of Computer Science
Dalhousie University
6050 University Ave.
PO Box 15000
Halifax, Nova Scotia, Canada
B3H 4R2


We present a potential vulnerability of personalised anti-spam filters where an attacker sends carefully constructed e-mail messages with the goal of negatively affecting classifier accuracy. Words from the core of the English language are randomly "injected" into spam e-mails for the express purpose of manipulating the probability tables of a naive Bayesian classifier. This attack method is shown to be successful in reducing classifier accuracy within a laboratory environment. Barriers to a real-world implementation and potential countermeasures are discussed.

Tech Report Number: 
Report Date: 
March 25, 2004
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