1,539 research outputs found

    Estimating Impact and Frequency of Risks to Safety and Mission Critical Systems Using CVSS

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    Many safety and mission critical systems depend on the correct and secure operation of both supportive and core software systems. E.g., both the safety of personnel and the effective execution of core missions on an oil platform depend on the correct recording storing, transfer and interpretation of data, such as that for the Logging While Drilling (LWD) and Measurement While Drilling (MWD) subsystems. Here, data is recorded on site, packaged and then transferred to an on-shore operational centre. Today, the data is transferred on dedicated communication channels to ensure a secure and safe transfer, free from deliberately and accidental faults. However, as the cost control is ever more important some of the transfer will be over remotely accessible infrastructure in the future. Thus, communication will be prone to known security vulnerabilities exploitable by outsiders. This paper presents a model that estimates risk level of known vulnerabilities as a combination of frequency and impact estimates derived from the Common Vulnerability Scoring System (CVSS). The model is implemented as a Bayesian Belief Network (BBN)

    Reliability estimation of safety-critical software-based systems using Bayesian networks

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    Miniature mobile sensor platforms for condition monitoring of structures

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    In this paper, a wireless, multisensor inspection system for nondestructive evaluation (NDE) of materials is described. The sensor configuration enables two inspection modes-magnetic (flux leakage and eddy current) and noncontact ultrasound. Each is designed to function in a complementary manner, maximizing the potential for detection of both surface and internal defects. Particular emphasis is placed on the generic architecture of a novel, intelligent sensor platform, and its positioning on the structure under test. The sensor units are capable of wireless communication with a remote host computer, which controls manipulation and data interpretation. Results are presented in the form of automatic scans with different NDE sensors in a series of experiments on thin plate structures. To highlight the advantage of utilizing multiple inspection modalities, data fusion approaches are employed to combine data collected by complementary sensor systems. Fusion of data is shown to demonstrate the potential for improved inspection reliability

    An Approach to Modelling Information System Availability by Using Bayesian Belief Network

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    In today’s era of the ubiquitous use of information technology (IT), it is expected that the information systems provide services to end-users on continuous basis, regardless of time and location. This is especially true in organizations where information systems (IS) support real-time critical operations, particularly, in the industries in which these systems must continuously operate 24x7x365. This paper presents a modified Bayesian Belief Network model for predicting IS availability. Based on a thorough review of all IS availability dimensions, we proposed a modified set of determinants. The model is parametrized using probability elicitation process with the participation of experts from the BiH financial sector. The results showed that most influential determinants of the IS availability are a timely and precise definition of the availability requirements, quality of IT operations, management and network. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

    Multifaceted modelling of complex business enterprises

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    We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control

    Combination of Evidence in Dempster-Shafer Theory

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