Paper Info
Title
A Framework For Preserving The Privacy Of Online Users Against Xss Worms On Online Social Network
Abstract
This article presents a hybrid framework i.e. OXSSD (Online Social Network-Based XSS-Defender) that explores cross-site scripting (XSS) attack vectors at the vulnerable points in web applications of social networks. Initially, during training phase, it generates the views for each request and formulates the access control list (ACL) which encompasses all the privileges a view can have. It also ascertains all possible injection points for extracting malicious attack vectors. Secondly, during recognition phase, after action authentication XSS attack vectors are retrieved from the extracted injection points followed by the clustering of these attack vectors. Finally, it sanitizes the compressed clustered template in a context-aware manner. This context-aware sanitization ensures efficient and accurate alleviation of XSS attacks from the OSN-based web applications. The authors will evaluate the detection capability of OXSSD on a tested suite of real world OSN-based web applications (Humhub, Elgg, WordPress, Drupal and Joomla). The performance analysis revealed that OXSSD detects injection of illicit attack vectors with very low false positives, false negatives and acceptable performance overhead.
Year
DOI
Venue
2019
10.4018/IJITWE.2019010105
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY AND WEB ENGINEERING
Keywords
Field
DocType
Access Control List (ACL), Cross-Site Scripting (XSS) Attack Vectors, Request Authentication, Session, XSS Cheat Sheet
World Wide Web,Social network,Computer science,Cross-site scripting,Database
Journal
Volume
Issue
ISSN
14
1
1554-1045
Citations 
PageRank 
References 
0
0.34
12
Authors
3
Name
Order
Citations
PageRank
Pooja Chaudhary1274.54
Brij B. Gupta2184.70
shashank gupta3848.88