Abstract
Now a day people are living with internet technology but those technologies brings many problems to the people through many hacking techniques. Image spam is the one among them. In the earlier stages, hackers used to annoy targeted victims with their fabricated text called spam text. Hackers are passing their bogus information on many ways such as advertising, spam emails, buttons, query distributions etc. From which spam emails are very specific to attack and they are filtered by text based filter. Then attackers nurtured their attacks on new way i.e., spreading spam mails by images. Those images are non related content to the concerned users on their corresponding mails or any web pages. Because of those spam images, text based filter couldn’t identify spam texts. On the basis of an image’s features, Attackers used to embed their spam text or mischief coded links into some of the attracted images. To identify spam contents from an image, security functions of a system must be able to recognize the characters imbedding on any images. This research paper is going to present views on image spam, Data mining approaches for dataset analysis, proposed optical character recognizer model and implementation of character recognition from images using Euclidean distance values.
Highlights
Spam contents are irrelevant information to the users who received on their emails and browsed or visited link pages
Server side filters working under classification techniques for the “state of art” on malicious text information. After introduction to these text filter modules and classification techniques the spammers moved on to embedding their spam text/code into attached images and those images takes some illegitimate actions when the user clicks on that images or does any activity on that images
The images taken from various handheld devices may have different directions and it challenges to read and recognize any characters bounded by taken image. To recognize those characters researchers has implemented many innovative ideas such as projection profiles, Rapid Annotation using Subsystem Technology (RAST) algorithm for curled texts [5], Hough Transformation etc., Vague Impression: Blurring happens at the time of capturing images from short or long distances and object movement time
Summary
Spam contents are irrelevant information to the users who received on their emails and browsed or visited link pages. Based on those patterns and characters they developed few anti spam applications for avoiding transaction vulnerabilities over email/internet [10]. Server side filters working under classification techniques for the “state of art” on malicious text information After introduction to these text filter modules and classification techniques the spammers moved on to embedding their spam text/code into attached images and those images takes some illegitimate actions when the user clicks on that images or does any activity on that images.
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