Intrusion Detection has been studied for about twenty years. Intrusion Detection Systems IDSs are usually considered the second line of defense to protect against malicious activities along with the prevention-based security mechanisms such as authentication and access control. However, tradi-tional IDSs have two major weaknesses. First, they usually focus on low-level attacks or anomalies, and raise alerts independently, though there may be logical connections between them. Second, there are a lot of false alerts reported by traditional IDSs, which are mixed with true alerts. Thus, the intrusion analysts or the system administrators are often overwhelmed by the volume of alerts.
Network Payload-based Anomaly Detection and Content-based Alert Correlation. Ke Wang
"A Correlational Study: The Relationship Between Physical Activity Leve" by Ashley Danelle Eyre
Zhu, Ben Wen Privacy-preserving alert correlation and report retrieval. Masters thesis, Concordia University. Intrusion Detection Systems IDSs have been widely deployed on both hosts and networks and serve as a second line of defense. Generally, an IDS flags malicious activates as IDS alerts and forwards them to security officers for further responses. The core issue of IDSs is to minimize both false positives and false negatives. Previous research shows that alert correlation is an effective solution.
A Toolkit for Intrusion Alerts Correlation based on Prerequisites and Consequences of Attacks
Abstract Alert and event correlation is a process in which the alerts produced by one or more intrusion detection systems and events generated from different systems and security tools are analyzed and correlated to provide a more succinct and high-level view of occurring or attempted intrusions. Current correlation techniques improve the intrusion detection results and reduce the huge number of alerts in a summarized report, but still have some limitations such as a high false detection rate; missing alerts in a multi-step attack correlation; alert verifications are still limited; Zero Day attacks still have low rates of detection; Low and Slow attacks and Advanced Persistent Threats APTs cannot be detected; and some attacks have evasion techniques against IDSs. Finally, current correlation systems do not enable the integration of correlations from multiple information sources and are limited to only operate in IDS alerts. Agents and multi- agent systems have been widely used in IDSs because of their advantages. The thesis purpose is to prove the possibility of improving both IDS Accuracy and IDS Completeness through reducing either False Positive or False Negative alerts using correlation between different available information sources in the system and network environment.
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