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Title: Impact of Network Activity Levels on the Performance of Passive Network Service Dependency Discovery

Network services often do not operate alone, but instead, depend on other services distributed throughout a network to correctly function. If a service fails, is disrupted, or degraded, it is likely to impair other services. The web of dependencies can be surprisingly complex---especially within a large enterprise network---and evolve with time. Acquiring, maintaining, and understanding dependency knowledge is critical for many network management and cyber defense activities. While automation can improve situation awareness for network operators and cyber practitioners, poor detection accuracy reduces their confidence and can complicate their roles. In this paper we rigorously study the effects of network activity levels on the detection accuracy of passive network-based service dependency discovery methods. The accuracy of all except for one method was inversely proportional to network activity levels. Our proposed cross correlation method was particularly robust to the influence of network activity. The proposed experimental treatment will further advance a more scientific evaluation of methods and provide the ability to determine their operational boundaries.
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Conference: IEEE Military Communications Conference (MILCOM 2015), October 26-28, 2015 Tampa, Florida, 1341-1347
IEEE, Piscataway, New Jersey
Research Org:
Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
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Country of Publication:
United States
network service dependency discovery; dependency graph; machine learning; correlation