Publication Date

Fall 2015

Degree Type

Master's Project

Degree Name

Master of Science (MS)


Computer Science


Now-a-days, enterprises’ acceptance over the Cloud is increasing but businesses are now finding issues related to security. Everyday, users store a large amount of data in the Cloud and user input may be malicious. Therefore, security has become the critical feature in the applications stored in the Cloud. Though there are many existing systems which provide us different encryption algorithms and security methods, there is still a possibility of attacks to applications and increasing data modifications. The idea behind this project is to find attacks and protect the applications stored in the Cloud using log analysis. The proposed solution detects the SQL injection attack, which is supposed to be the most critical security risk of vulnerable applications. The goal of this research is to detect the SQL injection attacks for an application stored in the Cloud by analyzing the logs. To achieve this, the proposed system automates the intrusion detection process for an application by performing log analysis. Log Analysis is performed by combining the implementation of two different methodologies called learn and detect methodology and pattern recognition system. The accuracy of SQL injections detected on log data is dependent on the order in which these two methodologies are applied. The outcome after applying these two methodologies results in information which helps a security analyst to understand and know the root cause of every attack that is detected on an application.