Byzantine Generals Playing Evolutionary Games

A New Extended Evolutionary Game Theory Approach to Strategic Information Warfare Research

ABSTRACT

The extended evolutionary game theory (EEGT) extends traditional evolutionary game theory (EGT) with survival analysis and agreement algorithms. Survival analysis, a branch of modern biostatistics, is adopted to model the consequences of the so-termed UUUR (Uncertain, latent, Unobserved or Unobservable Risks) events. Agreement algorithms can be the Agreement algorithms from the traditional fault-tolerant distributed computing or any problem-specific (user-defined) algorithms (constraints) that allow game players to dynamically check and 'vote' for a possible consensus. The EEGT was initiated in the study of reliability and survivability of distributed computer networks and is particularly suitable for addressing critical issues such as dynamic uncertainty, vulnerability, frailty, and deception, which are often associated with distributed systems under stressed environments where the occurrence of UUUR events is the norm. Strategic information warfare (SIW) clearly falls within the scope of such systems. In this paper, the EEGT is introduced to the modelling of SIW from a three-layer (tactical, strategic and operational levels) perspective.  When applied to SIW, a tertiary extension to EEGT with hedging principle is necessary at the operational level, similar to the application of the EEGT to survivability analysis.

Journal of Information Warfare

The definitive publication for the best and latest research and analysis on information warfare, information operations, and cyber crime. Available in traditional hard copy or online.

Keywords

A

AI
APT

C

C2
C2S
CDX
CIA
CIP
CPS

D

DNS
DoD
DoS

I

IA
ICS

M

S

SOA

X

XRY

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The definitive publication for the best and latest research and analysis on information warfare, information operations, and cyber crime. Available in traditional hard copy or online.

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