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  • 1
    Electronic Resource
    Electronic Resource
    Adaptive Intrusion Detection: A Data Mining Approach (2000)
    Springer
    Artificial intelligence review 14 (2000), S. 533-567 
    Details
    ISSN: 1573-7462
    Keywords: association rules ; audit data ; classification ; feature construction ; frequent episodes ; intrusion detection
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract In this paper we describe a data mining framework for constructingintrusion detection models. The first key idea is to mine system auditdata for consistent and useful patterns of program and user behavior.The other is to use the set of relevant system features presented inthe patterns to compute inductively learned classifiers that canrecognize anomalies and known intrusions. In order for the classifiersto be effective intrusion detection models, we need to have sufficientaudit data for training and also select a set of predictive systemfeatures. We propose to use the association rules and frequentepisodes computed from audit data as the basis for guiding the auditdata gathering and feature selection processes. We modify these twobasic algorithms to use axis attribute(s) and referenceattribute(s) as forms of item constraints to compute only therelevant patterns. In addition, we use an iterative level-wiseapproximate mining procedure to uncover the low frequency butimportant patterns. We use meta-learning as a mechanism to makeintrusion detection models more effective and adaptive. We report ourextensive experiments in using our framework on real-world audit data.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1006624031083
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    Parallel processing of graph reachability in databases (1992)
    Springer
    International journal of parallel programming 21 (1992), S. 269-302 
    Details
    ISSN: 1573-7640
    Keywords: Parallel and distributed databases ; data reduction paradigm ; graph reachability ; sampling ; transitive closure
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract In this paper we consider parallel processing of a graph represented by a database relation, and we achieved two objectives. First, we propose a methodology for analyzing the speedup of a parallel processing strategy with the purpose of selecting at runtime one of several candidate strategies, depending on the hardware architecture and the input graph. Second, we study the single-source reachability problem, namely the problem of computing the set of nodes reachable from a given node in a directed graph. We propose several parallel strategies for solving this problem, and we analyze their performance using our new methodology. The analysis is confirmed experimentally in a UNIX-Ethernet environment. We also extend the results to the transitive closure problem.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/BF01421676
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    Paper (German National Licenses)
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