Language-model-based detection cascade for efficient classification of image-based spam e-mail

Proceedings - 2009 IEEE International Conference on Multimedia and Expo, ICME 2009

Volumn , Issue , 2009, Pages 1182-1185

  Hsia, Jen Hao ^a   Chen, Ming Syan ^a,b  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b INSTITUTE OF INFORMATION SCIENCE   (Taiwan)

Author keywords

Image spam; Near duplicate image detection; pLSA; Visual bag of words

Indexed keywords

ANTI-SPAM; BINARY CLASSIFIERS; COMPUTATION OVERHEADS; DETECTION ACCURACY; IMAGE DATASETS; IMAGE SPAM; IMAGE-BASED SPAM; MODEL-BASED; NEAR-DUPLICATE IMAGE DETECTION; PLSA; PROTOTYPE SYSTEM; SPAM EMAILS; SPAM FILTER; SPAM MESSAGES; VISUAL BAG-OF-WORDS;

COMPUTATIONAL EFFICIENCY; CONTENT BASED RETRIEVAL; ELECTRONIC MAIL; MULTIMEDIA SYSTEMS; SPAMMING;

INTERNET;

EID: 70449602762     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICME.2009.5202711     Document Type: Conference Paper

References (6)

1. C.-C. Chang and C.-J. Lin, "LIBSVM: A Library for Support Vector Machines," 2001. Software available at http://www.csie.ntu.edu.tw/~cjlin/ libsvm.
2. T. Hofmann, Probabilistic latent semantic indexing, ACM SIGIR, pp. 50-57, 1999.
3. D. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, vol. 60, pp. 91-110, 2004.
4. B. Mehta et al., Detecting Image Spam using Visual Features and Near Duplicate Detection, WWW, pp. 497-506, 2008.
5. V.N. Vapnik, Statistical Learning Theory, Wiley, New York, NY, USA, 1998.
6. Z. Wang et al., Filtering Image Spam with Near-Duplicate Detection, CEAS, 2007.