DocumentCode
160605
Title
bit.ly/malicious: Deep dive into short URL based e-crime detection
Author
Gupta, Neeraj ; Aggarwal, A. ; Kumaraguru, Ponnurangam
Author_Institution
Cybersecurity Educ. & Res. Centre, Indraprastha Inst. of Inf. Technol., New Delhi, India
fYear
2014
fDate
23-25 Sept. 2014
Firstpage
14
Lastpage
24
Abstract
Existence of spam URLs over emails and Online Social Media (OSM) has become a massive e-crime. To counter the dissemination of long complex URLs in emails and character limit imposed on various OSM (like Twitter), the concept of URL shortening has gained a lot of traction. URL shorteners take as input a long URL and output a short URL with the same landing page (as in the long URL) in return. With their immense popularity over time, URL shorteners have become a prime target for the attackers giving them an advantage to conceal malicious content. Bitly, a leading service among all shortening services 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 of 763,160 short URLs marked suspicious by Bitly in the month of October 2013. Our results reveal that Bitly is not using its claimed spam detection services very effectively. We also show how a suspicious Bitly account goes unnoticed despite of a prolonged recurrent illegitimate activity. Bitly displays a warning page on identification of suspicious links, but we observed this approach to be weak in controlling the overall propagation of spam. We also identified some short URL based features and coupled them with two domain specific features to classify a Bitly URL as malicious or benign and achieved an accuracy of 86.41%. The feature set identified can be generalized to other URL shortening services as well. To the best of our knowledge, this is the first large scale study to highlight the issues with the implementation of Bitly´s spam detection policies and proposing suitable countermeasures.
Keywords
computer crime; social networking (online); unsolicited e-mail; Twitter; URL based e-crime detection; URL shortening; bit.ly/malicious; emails; online social media; phishing attack; pornographic content propagation; spam URL; spam detection; work-from-home scam; Accuracy; Communities; Data collection; Facebook; Real-time systems; Twitter; Uniform resource locators;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic Crime Research (eCrime), 2014 APWG Symposium on
Conference_Location
Birmingham, AL
Print_ISBN
978-1-4799-6509-0
Type
conf
DOI
10.1109/ECRIME.2014.6963161
Filename
6963161
Link To Document