Online social network profile data extraction for vulnerability analysis
by Sophia Alim, Ruqayya Abdulrahman, Daniel Neagu, Mick Ridley
International Journal of Internet Technology and Secured Transactions (IJITST), Vol. 3, No. 2, 2011

Abstract: The increase in social computing has provided the situation where large amounts of personal information are being posted online. This makes people vulnerable to social engineering attacks because their personal details are readily available. Our automated approach for personal data extraction was developed to extract personal details and top friends from MySpace profiles and place them into a repository. An online social network graph was generated from the repository data where nodes represent peoples' profiles. Analysis was carried out into what factors affect node vulnerability. The graph analysis identified structural features of the nodes, e.g., clustering coefficient, indegree and outdegree, which contribute towards vulnerability. From this, it was found that the number of neighbours and the clustering coefficient were major factors in making a node vulnerable because of the potential to spread personal details around the network. These results provide a good foundation for future work on online vulnerability in online social networks (OSNs).

Online publication date: Sat, 29-Nov-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Internet Technology and Secured Transactions (IJITST):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com