Dublin Core
Title
Crime Predictive Model in Cybercrime Based On Social
And Economic Factors Using Bayesian And Markov Theories
(Case Study of Bank)
And Economic Factors Using Bayesian And Markov Theories
(Case Study of Bank)
Creator
Emeh Jennifer Afoma
Description
If financial institutions cannot detect incidents effectively, it cannot succeed to responding to incidents. This implies that the detection of incidents, is the most important aspect of incident response. A stochastic process with a first order dependence in discrete state and time is described as Markov chain, in the same way, Bayesian theory is a mathematical framework for reasoning and performing inference using probability. These two theories were used to predict cybercrime occurrence using centralized system in form of a model for Management Information Systems (MIS). The advancement of technology in banking has made banking business processes very convenient, but as the technology advances, cybercrimes of different nature emerges and equally at its peak. In as much as there are different measures already in place to combat these crimes, there still lies so many vulnerabilities which cannot be evitable in any information systems, especially the financial institutions, in other words prediction theory which tends to detect and predict any event can be used to combat this cybercrime activities.
The theory which was introduced by Markov in 1907 has been applied in many predictive models and at such has been able to describe various phenomena of the real world. In this research study, the application of Markov theory and Markov chain offered ideal conditions for determination of the next target of crime. Similarly, Bayesian inference also analysed the nature of cybercrime and the probability of its occurrence, moreover, it has been recommended that different factors which could possibly cause cybercrime like vulnerabilities of information system, should also be predicted using both theories.
The theory which was introduced by Markov in 1907 has been applied in many predictive models and at such has been able to describe various phenomena of the real world. In this research study, the application of Markov theory and Markov chain offered ideal conditions for determination of the next target of crime. Similarly, Bayesian inference also analysed the nature of cybercrime and the probability of its occurrence, moreover, it has been recommended that different factors which could possibly cause cybercrime like vulnerabilities of information system, should also be predicted using both theories.
Subject
MSc Management Information Systems
Publisher
Ghana Technology University College
Date
January, 2017
Contributor
Dr. Kester Quist-Aphetsi