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Evaluation of Spam Detection and Prevention Frameworks for Email and Image Spam - A State of Art. Pedram Hayati, Vidyasagar Potdar Digital Ecosystems and Business Intelligence (DEBI) Institute Curtin University of Technology http://debii.curtin.edu.au/~pedram/

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Evaluation of spam detection and prevention frameworks for email and image spam a state of art

Evaluation of Spam Detection and Prevention Frameworks for Email and Image Spam - A State of Art

Pedram Hayati, Vidyasagar Potdar

Digital Ecosystems and Business Intelligence (DEBI) Institute

Curtin University of Technology

http://debii.curtin.edu.au/~pedram/

http://debii.curtin.edu.au/~vidy/


Outline
Outline Email and Image Spam - A State of Art

  • INTRODUCTION

  • SPAMMING MOTIVATIONS

  • ANTI-SPAM STRATEGIES

  • EMAIL SPAM

    • EMAIL SPAM METHODS

    • EMAIL SPAM SURVEY

  • IMAGE SPAM

    • IMAGE SPAM METHODS

    • IMAGE SPAM SURVER

  • CONCLOUSION


Introduction
INTRODUCTION Email and Image Spam - A State of Art

  • Rapid adoption of the Internet

  • The ease with which content can be generated and published has also made it easier to create spam.

  • Spam can be simply stated as information which does not add value to the web user

  • E.g. inappropriate, unsolicited, repeated and irrelevant content in email messages, search results, blogs, forums, social communities and product reviews.

  • the aim of this paper is to survey the current literature in the field of anti-spam with focus on specific anti-spam techniques used in email spam and image spam.


Spamming motivations
SPAMMING MOTIVATIONS Email and Image Spam - A State of Art

  • Revenue Generation

    • publishing advertisements on websites. Google AdSense™

  • Higher Search Engine Ranking

    • incorporate search engine optimization techniques to get their website a higher rank in search results

  • Promoting Products and Services

    • spammers are paid by companies to promote their products or services

  • Stealing Information

    • setup hidden programs in user’s computers to gain back door entry

  • Phishing

    • to steal sensitive information (such as credit card numbers, password, etc.)


Anti spam strategies
ANTI-SPAM STRATEGIES Email and Image Spam - A State of Art

  • Spam Detection Strategy

    • Try to identify the likelihood of spam in a system either automatically or manually

  • Spam Prevention Strategy

    • Deal with the problem of spam in different way. In this strategy, system designers create challenges for the spammers and make spamming a difficult task


Anti spam strategies1
ANTI-SPAM STRATEGIES Email and Image Spam - A State of Art

Spam Detection Strategy

Spam Prevention Strategy


Email spam
EMAIL SPAM Email and Image Spam - A State of Art

  • Email spam refers to sending irrelevant, inappropriate and unsolicited email messages to numerous people

  • Low entrance barrier and low cost of sending emails, which makes it one of the most popular forms of spam

  • The purpose of email spam is advertising, promotion, and spreading backdoors or malicious programs


Email spam methods
EMAIL SPAM METHODS Email and Image Spam - A State of Art


Email spam survey
EMAIL SPAM SURVEY Email and Image Spam - A State of Art

  • Majority of methods are detection based.

  • Majority is not suitable for non-English language.

  • Behaviour-based methods can not detect spam on the fly and spammers can manipulate their behavior to game the system easily.


Image spam
IMAGE SPAM Email and Image Spam - A State of Art

  • Spammers put their spam content into the images.

  • They embed text such as advertisement text in the images and attach these images to emails.

  • Anti-spam filters that analyse content of email cannot detect spam text in images


Image spam methods
IMAGE SPAM METHODS Email and Image Spam - A State of Art


Image spam survey
IMAGE SPAM SURVEY Email and Image Spam - A State of Art

  • OSR-based methods are vulnerable to content obscuring tactics and reasonably slow.

  • Meta-based methods can be easily exploit by changing image file attributes.

  • Template-based methods are vulnerable to real world images.


Conclousion
CONCLOUSION Email and Image Spam - A State of Art

  • Behaviour-based methods need time to create user profile can not detect spam on the fly.

  • Needed methods to detect spam on non-English content.

  • OSR-based methods are slow and vulnerable.

  • Template-based methods are vulnerable to real world images


Thanks any questions
Thanks! Any Questions? Email and Image Spam - A State of Art


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