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CEAS
2004
Springer
14 years 2 months ago
The Impact of Feature Selection on Signature-Driven Spam Detection
Signature-driven spam detection provides an alternative to machine learning approaches and can be very effective when near-duplicates of essentially the same message are sent in h...
Aleksander Kolcz, Abdur Chowdhury, Joshua Alspecto...
DIS
2007
Springer
14 years 3 months ago
Unsupervised Spam Detection Based on String Alienness Measures
We propose an unsupervised method for detecting spam documents from Web page data, based on equivalence relations on strings. We propose 3 measures for quantifying the alienness (...
Kazuyuki Narisawa, Hideo Bannai, Kohei Hatano, Mas...
CEAS
2007
Springer
14 years 3 months ago
CallRank: Combating SPIT Using Call Duration, Social Networks and Global Reputation
The growing popularity of IP telephony systems has made them attractive targets for spammers. Voice call spam, also known as Spam over Internet Telephony (SPIT), is potentially a ...
Vijay Balasubramaniyan, Mustaque Ahamad, Haesun Pa...
CEAS
2008
Springer
13 years 10 months ago
Improving Image Spam Filtering Using Image Text Features
In this paper we consider the approach to image spam filtering based on using image classifiers aimed at discriminating between ham and spam images, previously proposed by other a...
Giorgio Fumera, Fabio Roli, Battista Biggio, Ignaz...
HIS
2004
13 years 10 months ago
An Empirical Performance Comparison of Machine Learning Methods for Spam E-Mail Categorization
The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Using a classifier based on machine learning techniques ...
Chih-Chin Lai, Ming-Chi Tsai