DocumentCode
1592491
Title
Image spam — ASCII to the rescue!
Author
Nielson, Jordan ; Aycock, John ; De Castro, Daniel Medeiros Nunes
Author_Institution
Dept. of Comput. Sci., Univ. of Calgary, Calgary, AB
fYear
2008
Firstpage
65
Lastpage
68
Abstract
We take an unorthodox approach to image spam detection, by applying existing software and decades-old technology: ASCII art. Our technique is straightforward and gets good levels of detection over a corpus with 1159 ham and 1492 spam images, with a tolerable amount of misclassifications. Furthermore, we only look at the images themselves, meaning that this method can be trivially enhanced by combining it with existing anti-spam techniques.
Keywords
image classification; security of data; unsolicited e-mail; ASCII; antispam techniques; image spam detection; Art; Bayesian methods; Character recognition; Computer science; Drives; Image converters; Mathematics; Optical character recognition software; Optical filters; Unsolicited electronic mail;
fLanguage
English
Publisher
ieee
Conference_Titel
Malicious and Unwanted Software, 2008. MALWARE 2008. 3rd International Conference on
Conference_Location
Fairfax, VI
Print_ISBN
978-1-4244-3288-2
Electronic_ISBN
978-1-4244-3289-9
Type
conf
DOI
10.1109/MALWARE.2008.4690859
Filename
4690859
Link To Document