We present a solution for modeling the dependencies of an IT infrastructure and determine the availability of components and services therein using Markov logic networks (MLN). MLNs offer a single representation of probability and first-order logic and are well suited to model dependencies and threats. We identify different kinds of dependency and show how they can be translated into an MLN. The MLN infrastructure model allows us to use marginal inference to predict the availability of IT infrastructure components and services. We demonstrate that our solution is well suited for supporting IT Risk management by analyzing the impact of threats and comparing risk mitigation efforts
The assessment and mitigation of risks related to the availability of the IT infrastructure is becom...
Markov Logic Networks (MLNs) represent relational knowledge using a combination of first-order logic...
This paper provides a practical approach to construct and learn a Bayesian network model that will e...
We present a solution for modeling the dependencies of an IT infrastructure and determine the avail...
Information systems play a crucial role in most of today’s business operations. High availability an...
IT infrastructure is a crucial part in most of today's business operations. High availability and re...
Emerging smart manufacturing technologies combine physical production networks with digital IT syste...
Purpose This paper aims to examine the connection between information system (IS) availabilit...
Abstract—In this paper, we investigate the availability modeling of computer networks with redundanc...
The increasing costs and frequency of security incidents require organizations to apply proper IT ri...
The assessment and mitigation of risks related to the availability of the IT infrastructure is becom...
The method proposed in this paper represents a novel approach where graph-theoretic models used in a...
Study of network risks allows to develop insights into the methods of building robust networks, whic...
This article proposes an approach for the derivation of multi-hazard fragility functions, through th...
Requirement engineering is a key issue in the development of a software project. Like any other deve...
The assessment and mitigation of risks related to the availability of the IT infrastructure is becom...
Markov Logic Networks (MLNs) represent relational knowledge using a combination of first-order logic...
This paper provides a practical approach to construct and learn a Bayesian network model that will e...
We present a solution for modeling the dependencies of an IT infrastructure and determine the avail...
Information systems play a crucial role in most of today’s business operations. High availability an...
IT infrastructure is a crucial part in most of today's business operations. High availability and re...
Emerging smart manufacturing technologies combine physical production networks with digital IT syste...
Purpose This paper aims to examine the connection between information system (IS) availabilit...
Abstract—In this paper, we investigate the availability modeling of computer networks with redundanc...
The increasing costs and frequency of security incidents require organizations to apply proper IT ri...
The assessment and mitigation of risks related to the availability of the IT infrastructure is becom...
The method proposed in this paper represents a novel approach where graph-theoretic models used in a...
Study of network risks allows to develop insights into the methods of building robust networks, whic...
This article proposes an approach for the derivation of multi-hazard fragility functions, through th...
Requirement engineering is a key issue in the development of a software project. Like any other deve...
The assessment and mitigation of risks related to the availability of the IT infrastructure is becom...
Markov Logic Networks (MLNs) represent relational knowledge using a combination of first-order logic...
This paper provides a practical approach to construct and learn a Bayesian network model that will e...