Cybersecurity: A Statistical Predictive Model for the Expected Path Length

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ISSN Print: 2153-1234
ISSN Online: 2153-1242
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"Cybersecurity: A Statistical Predictive Model for the Expected Path Length"
written by Pubudu Kalpani Kaluarachchi, Chris P. Tsokos, Sasith M. Rajasooriya,
published by Journal of Information Security, Vol.7 No.3, 2016

has been cited by the following article(s):

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CrossRef

[1]	Cybersecurity: Identifying the Vulnerability Intensity Function (VIF) and Vulnerability Index Indicator (VII) of a Computer Operating System
	Journal of Information Security, 2022

[2]	Machine Learning Approach to Predict Computer Operating Systems Vulnerabilities
	2020

[3]	An Analytical Approach to Assess and Compare the Vulnerability Risk of Operating Systems.
	2020

[4]	An Analytical Approach to Assess and Compare the Vulnerability Risk of Operating Systems
	2020

[5]	Bayesian Reliability Analysis of the Power Law Process and Statistical Modeling of Computer and Network Vulnerabilities with Cybersecurity Application
	2020

[6]	Stochastic models of just-in-time systems and windows of vulnerability in terms of the processes of birth and death
	Вестн. Сам. гос. техн. ун-та. Сер. Физ.-мат. Науки, 2019

[7]	Nonhomogeneous Risk Rank Analysis Method for Security Network System
	2019

[8]	Original Paper Risk Rank Analysis Method for Vulnerabilities in a Network System
	Urban Studies and Public Administration, 2019

[9]	Security Metric Methods for Network Multistep Attacks Using AMC and Big Data Correlation Analysis
	Security and Communication Networks, 2018

[10]	Cyber Security: Nonlinear Stochastic Models for Predicting the Exploitability
	2017

[11]	Cyber Attack Analysis Based on Markov Process Model
	ProQuest Dissertations Publishing, 2017

[12]	Cybersecurity: A Stochastic Predictive Model to Determine Overall Network Security Risk Using Markovian Process
	2017

[13]	Non-Homogeneous Stochastic Model for Cyber Security Predictions
	2017

[14]	Cybersecurity: Stochastic Analysis and Modelling of Vulnerabilities to Determine the Network Security and Attackers Behavior
	ProQuest Dissertations Publishing, 2017

[15]	Cybersecurity: Probabilistic Behavior of Vulnerability and Life Cycle
	ProQuest Dissertations Publishing, 2017

[16]	Stochastic Modelling of Vulnerability Life Cycle and Security Risk Evaluation
	2016

[1]	Practical Applications of Stochastic Modelling Communications in Computer and Information Science, 2023 DOI:10.1007/978-3-031-44053-3_1

[2]	Machine Learning Approach to Predict Computer Operating Systems Vulnerabilities 2020 3rd International Conference on Computer Applications & Information Security (ICCAIS), 2020 DOI:10.1109/ICCAIS48893.2020.9096731

[3]	Stochastic models of just-in-time systems and windows of vulnerability in terms of the processes of birth and death Вестник Самарского государственного технического университета. Серия «Физико-математические науки», 2019 DOI:10.14498/vsgtu1725

[4]	Non-Homogeneous Stochastic Model for Cyber Security Predictions Journal of Information Security, 2018 DOI:10.4236/jis.2018.91002

[5]	Security Metric Methods for Network Multistep Attacks Using AMC and Big Data Correlation Analysis Security and Communication Networks, 2018 DOI:10.1155/2018/5787102

[6]	Cybersecurity: A Stochastic Predictive Model to Determine Overall Network Security Risk Using Markovian Process Journal of Information Security, 2017 DOI:10.4236/jis.2017.82007

[7]	Cyber Security: Nonlinear Stochastic Models for Predicting the Exploitability Journal of Information Security, 2017 DOI:10.4236/jis.2017.82009

[8]	Stochastic Modelling of Vulnerability Life Cycle and Security Risk Evaluation Journal of Information Security, 2016 DOI:10.4236/jis.2016.74022

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