Multivariate Statistical Analysis of Audit Trails for Host-Based Intrusion Detection

By Nong Ye, S. Emran, Qiang Chen, Sean Vilbert. IEEE Trans. Computers, 2002

308 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Biomedical Engineering, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/a66bda18b60ea02d0ecf6b803fd8fba90eb9e22f

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Citations in the corpus

Survey of intrusion detection systems: techniques, datasets and challenges (2019, background): “Ye et al. examine a multivariate quality control method to identify intrusions by building a long-term profile of normal activities (Ye et al., 2002).”
Anomaly-based network intrusion detection: Techniques, systems and challenges (2009, background): “Later, multivariate models that consider the correlations between two or more metrics were proposed (Ye et al., 2002).”
Generation of a new IDS test dataset: Time to retire the KDD collection (2013, methodology): “Multivariate statistical analysis of audit data [24]1 90 40”
Multivariate Process Variability Monitoring (2008, unknown): “This signifies that VV can be used efficiently for high-dimension data sets, such as those that computer scientists usually encounter, for example, when they construct a Shewhart-type control chart to detect computer intrusions (Park, 2005; Ye and Chen, 2001; Ye et al., 2002).”
A Semantic Approach to Host-Based Intrusion Detection Systems Using Contiguousand Discontiguous System Call Patterns (2014, methodology): “Statistical methods, such as described in [33], provide an alternative approach, and are well suited to offline processing and handling large amounts of training data.”
An overview of anomaly detection techniques: Existing solutions and latest technological trends (2007, methodology): “Ye et al. [19] It uses the Hotellings T 2 test to analyze the audit trails of activities in an computer system and detect host-based intrusions Host based multivariate statistical anomaly detection 2 A naive Bayesian network is a restricted network that has only two layers and assumes complete…”