Analysis of Security Threats and Vulnerabilities for Train Control and Monitoring Systems

2018 ◽  
Author(s):  
Mouna Rekik ◽  
Christophe Gransart ◽  
Marion Berbineau
Keyword(s):  
Monitoring Systems ◽  
Security Threats ◽  
Train Control

Sensor Networks Security for Pervasive Healthcare

2012 ◽  
pp. 967-983
Author(s):  
Ioannis Krontiris
Keyword(s):  
Sensor Networks ◽  
Monitoring Systems ◽  
Security Threats ◽  
Embedded Devices ◽  
Privacy And Security ◽  
Ageing Society ◽  
Pervasive Healthcare ◽  
Wear Monitoring ◽  
Research Questions

Body-worn sensors and wireless interconnection of distributed embedded devices facilitate the use of lightweight systems for monitoring vital health parameters like heart rate, respiration rate and blood pressure. Patients can simply wear monitoring systems without restricting their mobility and everyday life. This is particularly beneficial in the context of world’s ageing society with many people suffering chronic ailments. However, wireless transmission of sensitive patient data through distributed embedded devices presents several privacy and security implications. In this book chapter the authors’ first highlight the security threats in a biomedical sensor networks and identify the requirements that a security solution has to offer. Then the authors’ review some popular architectures proposed in the bibliography over the last few years and they discuss the methods that they employ in order to offer security. Finally the authors’ discuss some open research questions that have not been addressed so far and which they believe offer promising directions towards making these kinds of networks more secure.

Data Security at Remote Monitoring of Human State

2020 ◽  
pp. 42-57
Author(s):  
T.I. Buldakova ◽  
D.A. Mikov ◽  
A.V. Sokolova
Keyword(s):  
Information System ◽  
Remote Monitoring ◽  
Data Security ◽  
Medical Information ◽  
Medical Information System ◽  
Monitoring Systems ◽  
Security Threats ◽  
Telemedicine System ◽  
Access Information ◽  
Remote Monitoring Systems

The paper focuses on telemedicine systems for monitoring the human state and methods of protecting the transmitted data. To assess the state, biosignals are used, which are recorded by sensors and transmitted to a cloud medical information system. Based on the data obtained, a decision is made about the human state. Since the monitoring system works with restricted access information, it must be reliably protected. The study places an emphasis on possible information security threats for all components of the telemedicine system, analyzes various approaches to the protection of transmitted data in remote monitoring systems. It is noted that the existing methods are insufficient and additional methods of protecting the transmitted data are required. It is proposed to assess data security using the information risk management methods

Sensor Networks Security for Pervasive Healthcare

2010 ◽  
pp. 155-171
Author(s):  
Ioannis Krontiris
Keyword(s):  
Sensor Networks ◽  
Monitoring Systems ◽  
Security Threats ◽  
Embedded Devices ◽  
Privacy And Security ◽  
Ageing Society ◽  
Pervasive Healthcare ◽  
Wear Monitoring ◽  
Research Questions

Body-worn sensors and wireless interconnection of distributed embedded devices facilitate the use of lightweight systems for monitoring vital health parameters like heart rate, respiration rate and blood pressure. Patients can simply wear monitoring systems without restricting their mobility and everyday life. This is particularly beneficial in the context of world’s ageing society with many people suffering chronic ailments. However, wireless transmission of sensitive patient data through distributed embedded devices presents several privacy and security implications. In this book chapter the authors’ first highlight the security threats in a biomedical sensor networks and identify the requirements that a security solution has to offer. Then the authors’ review some popular architectures proposed in the bibliography over the last few years and they discuss the methods that they employ in order to offer security. Finally the authors’ discuss some open research questions that have not been addressed so far and which they believe offer promising directions towards making these kinds of networks more secure.

scholarly journals To a Question of Predicting Model Stability on the Basis of Multiple Scale Wavelet Transformation

2019 ◽  
Vol 23 (2) ◽  
pp. 109-123
Author(s):  
E. A. Sakrutina
Keyword(s):  
Large Scale ◽  
Process Development ◽  
Stability Study ◽  
Information Support ◽  
Monitoring Systems ◽  
Stability Conditions ◽  
Security Threats ◽  
Predicting Model ◽  
Model Stability ◽  
Risk Potential

Purpose of research. The article is devoted to the development of production predicting models and their stability conditions.Methods: Predicting models are actively used in modern control systems, in information support intellectual systems of decision-making. They have a huge role in any activity connected with signals' processing including anomalies detection of various technological processes and assessment of risk potential of critical information infrastructure objects. They can also be used in monitoring systems of security threats. Special class among predicting models is represented by the models based on experiences of proceeding processes (for example, regularities taken from the data which are saved up as a result of an object work).Results. Virtual "instant" model of an object belonging to this class is described in the article. It is presented taking into account multiple and large-scale decomposition of entrance influences vectors and the forecast of an object output. The described model gives the forecast without possible future conditions of an expected background. The approach based on the wavelet-analysis which is characterized by a unique opportunity of detailed frequency analysis in time is developed for stability study of virtual "instant" model. Stability conditions of the predicting model are received on the basis of this approach. This model has allocation conditions for approximating and detailing components for four types of ratios between memory depth on input and output.Conclusion: Predicting model of oil processing in which memory depth on an input is more than memory depth on output is described in the article. It is shown that the accuracy of virtual "instant" model forecast is higher than linear predicting model has at rare data of laboratory analysis. One of stability conditions depending on decomposition depth is shown for the constructed model. On the basis of received results analysis it is possible to draw a conclusion on applicability of received stability conditions for risk potential assessment of process development forecast implementation in monitoring systems of security threats.

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