Journal ArticleUnknown
Automatic Detection of NoSQL Injection Using Supervised Learning
Authors
Author Affiliations
Bangladesh University of Engineering and Technology
Year2019
Citations19
Abstract
With the advancement in big data, NoSQL databases are enjoying ever-growing popularity. The increasing use of this technology in large applications also brings security concerns to the fore. Historically, SQL injection has been one of the major security threats over the years. Recent studies reveal that NoSQL databases also have become vulnerable to injections. However, NoSQL security is yet to receive the attention it deserves from the industry or academia. In this work, we develop a tool for detecting NoSQL injections using supervised learning. To the best of our knowledge, our developed training dataset on NoSQL injection is the first of its kind. We manually design important features and apply various supervised learning algorithms. Our tool has achieved 0.93 F…
View at Publisher
BORR does not host full-text PDFs. The button above takes you to the original publisher.