Temporal sequence learning and data reduction for anomaly detection
ACM Transactions on Information and System Security (TISSEC)
DEMIDS: a misuse detection system for database systems
Integrity and internal control information systems
A Novel Intrusion Detection System Model for Securing Web-based Database Systems
COMPSAC '01 Proceedings of the 25th International Computer Software and Applications Conference on Invigorating Software Development
Learning Fingerprints for a Database Intrusion Detection System
ESORICS '02 Proceedings of the 7th European Symposium on Research in Computer Security
Architectures for Intrusion Tolerant Database Systems
ACSAC '02 Proceedings of the 18th Annual Computer Security Applications Conference
Intrusion Detection in Real-Time Database Systems via Time Signatures
RTAS '00 Proceedings of the Sixth IEEE Real Time Technology and Applications Symposium (RTAS 2000)
A Computer Host-Based User Anomaly Detection System Using the Self-Organizing Map
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5 - Volume 5
NOMAD: Traffic-based Network Monitoring Framework for Anomaly Detection
ISCC '99 Proceedings of the The Fourth IEEE Symposium on Computers and Communications
Anomaly detection of web-based attacks
Proceedings of the 10th ACM conference on Computer and communications security
Implementing Database Security and Auditing: Includes Examples for Oracle, SQL Server, DB2 UDB, Sybase
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Detecting anomalous access patterns in relational databases
The VLDB Journal — The International Journal on Very Large Data Bases
A comprehensive approach to anomaly detection in relational databases
DBSec'05 Proceedings of the 19th annual IFIP WG 11.3 working conference on Data and Applications Security
A learning-based approach to the detection of SQL attacks
DIMVA'05 Proceedings of the Second international conference on Detection of Intrusions and Malware, and Vulnerability Assessment
Detection of Database Intrusion Using a Two-Stage Fuzzy System
ISC '09 Proceedings of the 12th International Conference on Information Security
idMAS-SQL: Intrusion Detection Based on MAS to Detect and Block SQL injection through data mining
Information Sciences: an International Journal
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Data represent today a valuable asset for companies and organizations and must be protected. Most of an organization's sensitive and proprietary data resides in a Database Management System (DBMS). The focus of this thesis is to develop advanced security solutions for protecting the data residing in a DBMS. Our strategy is to develop an Intrusion Detection (ID) mechanism, implemented within the database server, that is capable of detecting anomalous user requests to a DBMS. The key idea is to learn profiles of users and applications interacting with a database. A database request that deviates from these profiles is then termed as anomalous. A major component of this work involves prototype implementation of this ID mechanism in the Post-greSQL database server. We also propose to augment the ID mechanism with an Intrusion Response engine that is capable of issuing an appropriate response to an anomalous database request.