A Simulation Model for Managing Survivability of Networked Information Systems

Abstract

In this paper the authors develop a model to evaluate the tradeoffs between the cost of defense mechanisms for networked systems and the resulting expected survivability after a network attack. The model consists of three submodels. The first submodel simulates the occurrence of attacks or incidents. The second submodel simulates the impact of an attack on the system. This depends on the type of attack and the defense mechanism installed in the system. The third submodel assesses the survivability of the system which depends on the degree of its degradation after the attack. By varying the level of defense in the simulation, we examine how this expected survivability changes with the defense level. Since costs are assumed to increase with the strength of the defense system, we can derive a cost/survivability curve that managers can use to decide on the appropriate level of security for their organizations. We have also explored the sensitivity of expected survivability to various parameters of the model, such as, the mix of attack types and the rate of occurrence of incidents. SUBJECT TERMS 15. NUMBER OF PAGES survivability, network systems, transition probabilities, 44 defense mechanisms, incident types

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2000
Accession Number
ADA388773

Entities

People

  • Soumyo D. Moitra
  • Suresh L. Konda

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Cyber

DTIC Thesaurus Topics

  • Communication Systems
  • Computer Network Security
  • Computer Networks
  • Cybersecurity
  • Decision Support Systems
  • Defense Mechanisms
  • Defense Systems
  • Degradation
  • Department Of Defense
  • Engineering
  • Homosexuality
  • Information Systems
  • New York
  • Simulations
  • Software Development
  • Systems Engineering
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Computational Fluid Dynamics (CFD)
  • Emergency Management and Homeland Security.
  • Regression Analysis.