Abstract
The detection and handling of data leakages is becoming a critical issue for organizations. To this end, data leakage solutions are usually employed by organizations to monitor network traffic and the use of portable storage devices. These solutions often produce a large number of alerts, whose analysis is time-consuming and costly for organizations. To effectively handle leakage incidents, organizations should be able to focus on the most severe incidents. Therefore, alerts need to be prioritized with respect to their severity. This work presents a novel approach for the quantification of data leakages based on their severity. The approach quantifies leakages with respect to the amount and sensitivity of the leaked information as well as the ability to identify the data subjects of the leaked information. To specify and reason on data sensitivity in an application domain, we propose a data model representing the knowledge in the domain. We validate our approach by analyzing data leakages within a healthcare environment.
Keywords: Data Leakage Detection; Severity Metrics; Data Sensitivity Model
Original language | English |
---|---|
Title of host publication | Data and Applications Security and Privacy XXVIII (28th Annual IFIP WG 11.3 Working Conference, DBSec 2014, Vienna, Austria, July 14-16, 2014) |
Editors | V. Atluri, G. Pernul |
Publisher | Springer |
Pages | 98-113 |
ISBN (Print) | 978-3-662-43935-7 |
DOIs | |
Publication status | Published - 2014 |
Event | 28th Annual IFIP WG 11.3 Working Conference on Data and Applications Security (DBSec 2014), July 14-16, 2014, Vienna, Austria - Vienna, Austria Duration: 14 Jul 2014 → 16 Jul 2014 |
Publication series
Name | Lecture Notes in Computer Science |
---|---|
Volume | 8566 |
ISSN (Print) | 0302-9743 |
Conference
Conference | 28th Annual IFIP WG 11.3 Working Conference on Data and Applications Security (DBSec 2014), July 14-16, 2014, Vienna, Austria |
---|---|
Abbreviated title | DBSec 2014 |
Country/Territory | Austria |
City | Vienna |
Period | 14/07/14 → 16/07/14 |
Fingerprint
Dive into the research topics of 'Data leakage quantification'. Together they form a unique fingerprint.Prizes
-
Best Student Paper Award at 28th Annual IFIP WG 11.3 Working Conference on Data and Applications Security (DBSec 2014)
Vavilis, S. (Recipient), Petkovic, M. (Recipient) & Zannone, N. (Recipient), 2014
Prize: Other › Career, activity or publication related prizes (lifetime, best paper, poster etc.) › Scientific