Description

Abstract

Twitter is an online social networking service and micro blogging service that enables its users to send and read text-based messages. Twitter spam detection schemes utilize account features such as the ratio of tweets containing URLs and the account creation date. It detects a schemes are ineffective against feature fabrications or consume much time and resources. A twitter stream attempts to open a URL that has been redirected, a page with a different URL is opened. The attackers have limited resources and usually reuse them; their URL redirect chains frequently share the same URLs.  The numerous tweets from the Twitter public timeline and build a statistical classifier using them. The twitter classifier accurately and efficiently detects suspicious URLs.