JITA

JITA Journal of Information Technology and Applications

Vol. 6 No. 2 (2018): JITA - APEIRON

Dalibor Drljača, Branko Latinović

Frameworks for Audit of an Information System in Practice

Original scientific paper

DOI: https://doi.org/10.7251/JIT1602078D

Abstract

The IT function became the backbone of the company and the central driving force of the entire operations of an organization. Modern electronic commerce is very dependent on the quality of information system supported with information technology. Safety aspects of business and electronic transactions transfer (Internet-supported), particularly in the banking sector, require a more complex audit of the organization, both financial and the information system audit. This paper presents the basic and in practice most frequently applied standards and guidelines for checking of security controls in information systems. The work presents the COBIT and ITIL as the two most prevalent methodologies for quality audit of information systems with the presentation of two ISO 27000 series of standards on information security.

Keywords: audit frameworks, IT audit, IT Governance, COBIT, ITIL, ISO27000.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.