A Methodology for Testing Intrusion Detection Systems
IEEE Transactions on Software Engineering
Aggregation and Correlation of Intrusion-Detection Alerts
RAID '00 Proceedings of the 4th International Symposium on Recent Advances in Intrusion Detection
A Trend Analysis of Exploitations
SP '01 Proceedings of the 2001 IEEE Symposium on Security and Privacy
Snort - Lightweight Intrusion Detection for Networks
LISA '99 Proceedings of the 13th USENIX conference on System administration
Network intrusion detection: evasion, traffic normalization, and end-to-end protocol semantics
SSYM'01 Proceedings of the 10th conference on USENIX Security Symposium - Volume 10
Enhancing byte-level network intrusion detection signatures with context
Proceedings of the 10th ACM conference on Computer and communications security
Time series modeling for IDS alert management
ASIACCS '06 Proceedings of the 2006 ACM Symposium on Information, computer and communications security
Intrusion detection: introduction to intrusion detection and security information management
Foundations of Security Analysis and Design III
Towards systematic signature testing
TestCom'07/FATES'07 Proceedings of the 19th IFIP TC6/WG6.1 international conference, and 7th international conference on Testing of Software and Communicating Systems
| Hi-index | 0.00 |
This paper describes a testing environment for commercial intrusion-detection systems, shows results of an actual test run and presents a number of conclusions drawn from the tests. Our test environment currently focuses on IP denial-of-service attacks, Trojan horse traffic and HTTP traffic. The paper focuses on the point of view of an analyst receiving alerts sent by intrusion-detection systems and the quality of the diagnostic provided. While the analysis of test results does not solely targets this point of view, we feel that the diagnostic accuracy issue is extremely relevant for the actual success and usability of intrusion-detection technology. The tests show that the diagnostic proposed by commercial intrusion-detection systems sorely lack in precision and accuracy, lacking the capability to diagnose the multiple facets of the security issues occurring on the test network. In particular, while they are sometimes able to extract multiple pieces of information from a single malicious event, the alerts reported are not related to one another in any way, thus loosing significant background information for an analyst. The paper therefore proposes a solution for improving current intrusion-detection probes to enhance the diagnostic provided in the case of an alert, and qualifying alerts in relation to the intent of the attacker as perceived from the information acquired during analysis.