JITA

JITA Journal of Information Technology and Applications

Vol. 9 No. 2 (2019): JITA - APEIRON

Ivo Džakula, Branko Latinović

REDUCTION OF ICT SECURITY RISKS USING LEVEL BASED APPROACH

Original scientific paper

DOI:https://doi.org/ 10.7251/JIT1902099DZ

Abstract

Security controls are certainly one of the most preferred ways of controlling the environment in which our system is “alive”. But although they are heavily represented and used in practice, security controls tend to become the same and not change after they are introduced. To try to make the most of the opportunities that this approach provides, this paper will explain the importance of implementing ICT security controls and propose a new approach by adding emergency ICT control. This approach gives us the ability to integrate the entire organization into the development of control by providing a better, more accurate and faster basis for managing the security risks of ICT technology.

Keywords: ICT – Information and communications technology, Risk, Security controls.

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.