SVM with Gaussian kernel-based image spam detection on textual features
Prashant Kumar, Mantosh Biswas · 2017
With the growth of the internet and the increasing importance of emails in our daily lives, spams have become a common phenomenon posing serious threats, as it gives rise to undesired emails. Image spam is a type of email spam in which the textual message is embedded within an image presenting it as a picture. This paper proposes a Support Vector Machine (SVM) with Gaussian kernel based classifier for detection of spam. In our experiment, we have used publicly available datasets with SVM with Gaussian kernel based classifier showing that our approach gives good performance over considered classifiers for measurement of F-measure, recall, accuracy and precision.