1 research outputs found
Exploration of gaps in Bitly's spam detection and relevant counter measures
Existence of spam URLs over emails and Online Social Media (OSM) has become a
growing phenomenon. To counter the dissemination issues associated with long
complex URLs in emails and character limit imposed on various OSM (like
Twitter), the concept of URL shortening gained a lot of traction. URL
shorteners take as input a long URL and give a short URL with the same landing
page in return. With its immense popularity over time, it has become a prime
target for the attackers giving them an advantage to conceal malicious content.
Bitly, a leading service in this domain is being exploited heavily to carry out
phishing attacks, work from home scams, pornographic content propagation, etc.
This imposes additional performance pressure on Bitly and other URL shorteners
to be able to detect and take a timely action against the illegitimate content.
In this study, we analyzed a dataset marked as suspicious by Bitly in the month
of October 2013 to highlight some ground issues in their spam detection
mechanism. In addition, we identified some short URL based features and coupled
them with two domain specific features to classify a Bitly URL as malicious /
benign and achieved a maximum accuracy of 86.41%. To the best of our knowledge,
this is the first large scale study to highlight the issues with Bitly's spam
detection policies and proposing a suitable countermeasure