Next Article in Journal
A Cross-Layer Optimized Opportunistic Routing Scheme for Loss-and-Delay Sensitive WSNs
Next Article in Special Issue
An Embodied Multi-Sensor Fusion Approach to Visual Motion Estimation Using Unsupervised Deep Networks
Previous Article in Journal
A Finite State Machine Approach to Algorithmic Lateral Inhibition for Real-Time Motion Detection
Previous Article in Special Issue
FPGA Based Adaptive Rate and Manifold Pattern Projection for Structured Light 3D Camera System
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle

Defense Strategies for Asymmetric Networked Systems with Discrete Components

1,*,†, 2,†, 3,†, 4,†, 5,† and 6,†
1
Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
2
Hang Seng Management College, Hong Kong
3
Faculty of Social Sciences, University of Stavanger, 4036 Stavanger, Norway
4
Department of Mechanical and Industrial Engineering, Texas A&M University, Kingsville, TX 78363, USA
5
Information Systems Technology and Design Clusteer, Singapore University of Technology and Design, Singapore 487372, Singapore
6
Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, NY 14260, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2018, 18(5), 1421; https://doi.org/10.3390/s18051421
Received: 15 February 2018 / Revised: 18 April 2018 / Accepted: 26 April 2018 / Published: 3 May 2018
  |  
PDF [1051 KB, uploaded 4 May 2018]
  |  

Abstract

We consider infrastructures consisting of a network of systems, each composed of discrete components. The network provides the vital connectivity between the systems and hence plays a critical, asymmetric role in the infrastructure operations. The individual components of the systems can be attacked by cyber and physical means and can be appropriately reinforced to withstand these attacks. We formulate the problem of ensuring the infrastructure performance as a game between an attacker and a provider, who choose the numbers of the components of the systems and network to attack and reinforce, respectively. The costs and benefits of attacks and reinforcements are characterized using the sum-form, product-form and composite utility functions, each composed of a survival probability term and a component cost term. We present a two-level characterization of the correlations within the infrastructure: (i) the aggregate failure correlation function specifies the infrastructure failure probability given the failure of an individual system or network, and (ii) the survival probabilities of the systems and network satisfy first-order differential conditions that capture the component-level correlations using multiplier functions. We derive Nash equilibrium conditions that provide expressions for individual system survival probabilities and also the expected infrastructure capacity specified by the total number of operational components. We apply these results to derive and analyze defense strategies for distributed cloud computing infrastructures using cyber-physical models. View Full-Text
Keywords: networked systems; cyber-physical infrastructures; aggregated correlation functions; sum-form, product-form and composite utility functions networked systems; cyber-physical infrastructures; aggregated correlation functions; sum-form, product-form and composite utility functions
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Rao, N.S.V.; Ma, C.Y.T.; Hausken, K.; He, F.; Yau, D.K.Y.; Zhuang, J. Defense Strategies for Asymmetric Networked Systems with Discrete Components. Sensors 2018, 18, 1421.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top