IEEE Transactions on Software Engineering - Special issue on computer security and privacy
An introduction to intrusion detection
Crossroads - Special issue on computer security
DEMIDS: a misuse detection system for database systems
Integrity and internal control information systems
Building the Data Warehouse
ASAX: Software Architecture and Rule-Based Language for Universal Audit Trail Analysis
ESORICS '92 Proceedings of the Second European Symposium on Research in Computer Security
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 data mining approach for database intrusion detection
Proceedings of the 2004 ACM symposium on Applied computing
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
User re-authentication via mouse movements
Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security
Intrusion Detection in RBAC-administered Databases
ACSAC '05 Proceedings of the 21st Annual Computer Security Applications Conference
Network Security Bible
James P. Anderson: An Information Security Pioneer
IEEE Security and Privacy
Automated stress detection using keystroke and linguistic features: An exploratory study
International Journal of Human-Computer Studies
A Practical Database Intrusion Detection System Framework
CIT '09 Proceedings of the 2009 Ninth IEEE International Conference on Computer and Information Technology - Volume 02
Towards the secure modelling of OLAP users behaviour
SDM'10 Proceedings of the 7th VLDB conference on Secure data management
Detection of anomalies from user profiles generated from system logs
AISC '11 Proceedings of the Ninth Australasian Information Security Conference - Volume 116
| Hi-index | 0.00 |
Data Warehouse (DW) systems maintain sensitive and crucial information, which is integrated from various heterogenous sources of organization. With the ever increasing deployment and usage of networks, these systems are becoming more vulnerable to malicious attacks. With the increased number of attacks, intrusion detection has become vital part of Information Security. In this paper, we have proposed a model for analyzing and detecting anomalous events based on user behavior analysis through usage patterns, user profiles and session management. After monitoring the events in the system, if any intrusion activity occurs, then alerts are issued to system administrators. Since a user profile is not necessarily fixed but rather it evolves with changing time, so a dynamic user behavior modeling is represented as a sequence of events and combination of fact and dimension tables accessed by the users. In this way, DW systems may be protected by the malicious attacks.