Analysis of Application Programs for Anomaly Detection for Profiling and Monitoring Database Access Patterns

  • P. Venkateswara Rao, P. Bharath Kumar, B. Kalyan Babu, P.J.V. Sai Teja

Abstract

Techniques for detection of anomalies in accesses to database systems accesses have been widely investigated.  Conventional data security techniques, such as access control and encryption, must be augmented with techniques to detect anomalies in data access that may indicate exfiltration attempts. In this paper, we present the design and evaluation of DBSAFE, a system to detect, alert on, and respond to anomalies in database access designed specifically for relational database management systems (DBMS).  sIn this paper, we focus on data leakage detection by monitoring database activities. We present a framework that automatically learns normal user behavior, in terms of database activities, and detects anomalies as deviation from such behavior. In addition, our approach explicitly indicates the root cause of an anomaly. Finally, the framework assesses the severity of data leakages based on the sensitivity of the disclosed data.

Published
2020-03-26
How to Cite
B. Kalyan Babu, P.J.V. Sai Teja, P. V. R. P. B. K. (2020). Analysis of Application Programs for Anomaly Detection for Profiling and Monitoring Database Access Patterns. International Journal of Advanced Science and Technology, 29(4s), 1241 - 1247. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/6777