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Alert based Suspicious and Malicious Tweet Urls Blocker System in Twitter
| Content Provider | Semantic Scholar |
|---|---|
| Author | Vidhyaprakash, R. |
| Copyright Year | 2013 |
| Abstract | With the advent of online public media, phishers using public networks like Twitter, Facebook, and Foursquare to spread phishing scams. Twitter is an hugely well-liked micro-blogging network where people place petite messages of 140 characters called tweets. It has over 100 million dynamic users who place about 200 million tweets everyday. In progress with Twitter, phisher use it as a medium to spread phishing because of this vast information dissemination. Because of short content size, and use of URL, it is difficult to detect phishing on Twitter unlike emails. Our technique, PhishAri, detects phishing on Twitter in realtime. We use Twitter explicit features along with URL features to sense whether a tweet posted with a URL is phishing or not. Some of the Twitter explicit features we use are tweet content and its characteristics like length, hash tags, and mentions. Other Twitter features used are the characteristics of the Twitter user relocation the tweet such as age of the report, number of tweets, and the follower ratio. These twitter specific features coupled with URL based features prove to be a strong mechanism to detect phishing tweets. We use instrumental learning classification techniques and detect phishing tweets. Key terms: Suspicious URL, Twitter, URL redirection, conditional redirection, classification, mail alert. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://ijiet.com/wp-content/uploads/2013/12/11.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
