IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Image Analysis for Efficient Categorization of Image-based Spam E-mail
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Spam Filtering Based On The Analysis Of Text Information Embedded Into Images
The Journal of Machine Learning Research
Image Spam Filtering Using Visual Information
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Design and Evaluation of a Bayesian-filter-based Image Spam Filtering Method
ISA '08 Proceedings of the 2008 International Conference on Information Security and Assurance (isa 2008)
Filtering Short Message Spam of Group Sending Using CAPTCHA
WKDD '08 Proceedings of the First International Workshop on Knowledge Discovery and Data Mining
Using Heterogeneous Features for Anti-spam Filters
DEXA '08 Proceedings of the 2008 19th International Conference on Database and Expert Systems Application
A Novel Method for Image Spam Filtering
ICYCS '08 Proceedings of the 2008 The 9th International Conference for Young Computer Scientists
Evaluation of spam detection and prevention frameworks for email and image spam: a state of art
Proceedings of the 10th International Conference on Information Integration and Web-based Applications & Services
Detecting image spam using local invariant features and pyramid match kernel
Proceedings of the 18th international conference on World wide web
Improved spam filtering by extraction of information from text embedded image e-mail
Proceedings of the 2009 ACM symposium on Applied Computing
A Simple Method for Filtering Image Spam
ICIS '09 Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science
A survey of learning-based techniques of email spam filtering
Artificial Intelligence Review
Semi Supervised Image Spam Hunter: A Regularized Discriminant EM Approach
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Image spam clustering: an unsupervised approach
MiFor '09 Proceedings of the First ACM workshop on Multimedia in forensics
Filtering Image Spam Using Image Semantics and Near-Duplicate Detection
ICICTA '09 Proceedings of the 2009 Second International Conference on Intelligent Computation Technology and Automation - Volume 01
Fast Effective Botnet Spam Detection
ICCIT '09 Proceedings of the 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology
Active Learning Image Spam Hunter
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Text extraction for spam-mail image filtering using a text color estimation technique
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Statistical Feature Extraction for Classification of Image Spam Using Artificial Neural Networks
ICMLC '10 Proceedings of the 2010 Second International Conference on Machine Learning and Computing
Efficient Modeling of Spam Images
IITSI '10 Proceedings of the 2010 Third International Symposium on Intelligent Information Technology and Security Informatics
Impeding CAPTCHA breakers with visual decryption
AISC '10 Proceedings of the Eighth Australasian Conference on Information Security - Volume 105
Attacking image recognition CAPTCHAS: a naive but effective approach
TrustBus'10 Proceedings of the 7th international conference on Trust, privacy and security in digital business
A High Performance Image-Spam Filtering System
DCABES '10 Proceedings of the 2010 Ninth International Symposium on Distributed Computing and Applications to Business, Engineering and Science
A survey and experimental evaluation of image spam filtering techniques
Pattern Recognition Letters
BASIL: effective near-duplicate image detection using gene sequence alignment
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
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Many techniques have been proposed to combat the upsurge in image-based spam. All the proposed techniques have the same target, trying to avoid the image spam entering our inboxes. Image spammers avoid the filter by different tricks and each of them needs to be analyzed to determine what facility the filters need to have for overcoming the tricks and not allowing spammers to full our inbox. Different tricks give rise to different techniques. This work surveys image spam phenomena from all sides, containing definitions, image spam tricks, anti image spam techniques, data set, etc. We describe each image spamming trick separately, and by perusing the methods used by researchers to combat them, a classification is drawn in three groups: header-based, content-based, and text-based. Finally, we discus the data sets which researchers use in experimental evaluation of their articles to show the accuracy of their ideas.