Lookup NU author(s): Dr Paul Ezhilchelvan,
Professor Roy Maxion
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Exploiting the advances made so far in intrusion detection, alarm correlation and fault-tolerant computing, we present a middleware architecture for building a large-scale distributed data-management system that is self-healing and self-protective. The architecture has two related, novel aspects over the state of art. Tolerance to intrusions and faults is generally provided under the assumption that failures never exceed a pre-defined threshold and this assumption is justified based on design-stage provisions e.g., replica diversity. The autonomic system architected here strives to proactively maintain this failure threshold through intrusion detection at the node level and replicated alarm-correlation at the system level. The requirement for the latter leads to the construction of intrusion-aware signal-on-fail nodes so that the well-known (FLP) impossibility result does not hinder a timely construction of consistent snapshot of alarms raised by the nodes.
Author(s): Ezhilchelvan PD, Maxion R
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: Workshop on Dependable Distributed Data Management, in conjunction with 23rd International Symposium on Reliable Distributed Systems
Year of Conference: 2004
Publisher: IEEE Computer Society