Cyber-Physical Security Risk Assessment for Train Control and Monitoring Systems

SSV 2018, 1st International Workshop on System Security and Vulnerability, IEEE CNS Conference on Communications and Network Security, Pekin, CHINE, 30-/05/2018 - 01/06/2018Future railway systems should bring convenience to people's lives. In fact, due to the move away from bespoke stand- alone systems to open-platform, standardized equipments and increasing use of networked control and automation systems and connected technologies, the efficiency and the safety of railway services are improving. However, this dependence of automation, control and communication technologies makes railway systems becoming increasingly vulnerable to cyber-attacks and security threats which affects the overall performance. This paper deals with cybersecurity concerns facing these systems. As such, we analyse characteristics of railway threat landscape. Then, we discuss the direct impacts of the identified potential threats and their consequences on the whole system and we evaluate resulted risks. For space limitation, we choose to present the impact, likelihood and risk analysis for one functionality of the system, namely External Door control (EDC). Some good practices and related techniques for the development of safer, more comfortable, and more secure future railway systems are also discussed

Cyber-physical Threats and Vulnerabilities Analysis for Train Control and Monitoring Systems

IEEE ISNCC 2018, International Symposium on Networks, Computers and Communications, Rome, ITALIE, 19-/06/2018 - 21/06/2018Cyber-physical security is a major concern for the new generation of trains. In fact, trains are increasingly relying on automation, control and communication technologies in order to improve the efficiency and safety of their services as well as the comfort of passengers. This dependency introduces certainly new vulnerabilities and entry points to the system which exposes the system to new threat scenarios. This paper deals with cyber-physical security aspects of Train Control and Monitoring System

Simulation of radio wave propagation in arched cross section tunnels

5 pagesInternational audienceSince several years, wireless communication systems are developed for train to infrastructure communication needs related to railway or mass transit applications. The systems should be able to operate in specific environments like tunnels. In this context, specific radio planning tools have to be developed to optimise system deployment. Realistic tunnels geometries are generally of rectangular cross-section or arched shape. Furthermore, they are mostly curved. In order to calculate electromagnetic wave propagation in such tunnels, specific models have to be developed. Several works dealt with retransmission of GSM or UMTS [1], [2]. Few theoretical or experimental works focused on 2.4 GHz or 5.8 GHz bands. In this paper, we will propose an approach to model radio wave propagation in these frequency bands in arched shape cross-section straight tunnels using tessellation in multi-facets. The model will be based on a Ray-Tracing tool using images method. Work reported in this paper will also show the propagation loss variations according to the shape of tunnels. A parametric study on the size of facets to model the cross-section will be realized. Finally, the influence of some parameters like the dimensions of tunnels and the frequency of signals will be examined

Reconfigurable Intelligent Surface Assisted Railway Communications: A survey

The number of train passengers and the demand for high data rates to handle new technologies such as video streaming and IoT technologies are continuously increasing. Therefore the exploration of millimeter waves (mmWave) band is a key technology to meet this demand. However, the high penetration loss makes mmWave very sensitive to blocking, limiting its coverage area. One promising, efficient, and low-cost solution is the reconfigurable intelligent surface (RIS). This paper reviews the state of the art of RIS for railway communications in the mmWave context. First, we present the different types of RIS and review some optimization algorithms used in the literature to find the RIS phase shift. Then, we review recent works on RIS in the railway domain and provide future directions

Asymptotic models and curved surfaces : application to railway transportation

5 pagesInternational audienceSeveral wireless communication systems are developed for communication needs between train and ground or between trains in the railway or mass transit domains. In order to deploy these systems in specific environments, such as tunnels, straight or curved, rectangular or arch-shaped section, specific propagation models have to be developed. In this paper, we propose a method to model the radiowave propagation in straight arch-shaped tunnels by using asymptotic methods, such as ray tracing and ray launching, combined with the tessellation of the arched section. A method of interpolation of the facets normals is implemented in order to minimize the error made when using the tessellation. These results are compared to those found in the literature in order to validate our approach

WINNER model for subway tunnel at 5.8 GHz

5 pagesInternational audienceModern subways operation relies on wireless systems based on IEEE802.11x modems deployed inside tunnels. Constraints on robustness and needs for high data rates led to the use of MIMO techniques. In order to evaluate performance of MIMO systems in dynamic configurations with moving trains, it is mandatory to develop adequate dynamic channel model. In this paper, the authors present a new WINNER based model for a subway tunnel at 5.8 GHz in a representative geometric configuration with two tracks and two crossing trains and a 4x4 MIMO system. The statistical behavior of the key parameters of the new WINNER scenario are derived from the complex impulse responses obtained with a 3D ray tracing simulator and given in this paper. Five clusters are considered. The total received power and the 4x4 MIMO channel capacity are compared with the ones derived from the 3D ray tracing simulator