Abstract
This paper demonstrates how to prevent or mitigate insider threats in relational databases. It shows how different order of accesses to the same data items may pose different levels of threat. Moreover, it states the conditions that are required to regard a data item as expired. In addition, it introduces the two different methods of executing insiders’ tasks, and how to prevent insider threat in those. The models presented in this paper organize accesses to data items in a particular sequence so that the availability of data items is maximized and the expected threat is minimized to the lowest level. Furthermore, it determines when to give an insider an incorrect but acceptable value of a risky data item in order to prevent a possible threat.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gordon, L., Loeb, M., Lucyshyn, W., Richardson, R.: Computer Crime and Security Survey, http://www.cpppe.umd.edu/Bookstore/Documents/2005CSISurvey.pdf
Yaseen, Q., Panda, B.: Organizing Access Privileges: Maximizing the Availability and Mitigating the Threat of Insiders’ Knowledgebase. In: 4th International Conference on Network and System Security, Melbourne, Australia (2010)
Bishop, M., Gates, C.: Defining the Insider Threat. In: 4th Annual Workshop on Cyber Security and Information Intelligence Research. Oak Ridge, Tennessee (2008)
Brackney, R., Anderson, R.: Understanding the insider threat. Technical Report, RAND Corporation (2004)
Yaseen, Q., Panda, B.: Knowledge Acquisition and Insider Threat Prediction in Relational Database Systems. In: International Workshop on Software Security Processes, Vancouver, Canada, pp. 450–455 (2009)
Spitzner, L.: Honeypots: Catching the Insider Threat. In: 19th Annual Computer Security Applications Conference, Washington, DC (2003)
Althebyan, Q., Panda, B.: A knowledge-base model for insider threat prediction. In: IEEE Workshop on Information Assurance and Security, West Point, NY, pp. 239–246 (2007)
Farkas, C., Jajodia, S.: The Inference Problem: A Survey. ACM SIGKDD Explorations, pp. 6–11 (2002)
Farkas, C., Toland, T., Eastman, C.: The Inference Problem and Updates in Relational Databases. In: 15th IFIP WG11.3 Working Conference on Database and Application Security, Ontario, Canada, pp. 181–194 (2001)
Brodsky, A., Farkas, C., Jajodia, S.: Secure Databases: Constraints, Inference Channels and Monitoring Disclosures. IEEE Trans. on Knowledge and Data Engineering, 900–919 (2000)
Yip, R., Levitt, K.: Data Level Inference Detection in Database Systems. In: 11th Computer Security Foundations Workshop, Rockport, MA, pp. 179–189 (1998)
Yaseen, Q., Panda, B.: Predicting and preventing insider threat in relational database systems. In: Samarati, P., Tunstall, M., Posegga, J., Markantonakis, K., Sauveron, D. (eds.) WISTP 2010. LNCS, vol. 6033, pp. 368–383. Springer, Heidelberg (2010)
Morgenstern, M.: Security and Inference in Multilevel Database and Knowledge-Base Systems. ACM SIGMOD Record, 357–373 (1987)
Yaseen, Q., Panda, B.: Malicious Modification attacks by Insiders in Relational Databases: Prediction and Prevention. In: 2nd IEEE International Conference on Information Privacy, Security, Risk and Trust, Minneapolis, Minnesota (2010)
Yalamanchili, R., Panda, B.: Transaction Fusion: A Model for Data Recovery from Information Attacks. Journal of Intelligent Information Systems 23(3), 225–245 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yaseen, Q., Panda, B. (2011). Enhanced Insider Threat Detection Model that Increases Data Availability. In: Natarajan, R., Ojo, A. (eds) Distributed Computing and Internet Technology. ICDCIT 2011. Lecture Notes in Computer Science, vol 6536. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19056-8_20
Download citation
DOI: https://doi.org/10.1007/978-3-642-19056-8_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19055-1
Online ISBN: 978-3-642-19056-8
eBook Packages: Computer ScienceComputer Science (R0)