Modeling and Detecting False Data Injection Attacks against Railway Traction Power Systems

Modern urban railways extensively use computerized sensing and control technologies to achieve safe, reliable, and well-timed operations. However, the use of these technologies may provide a convenient leverage to cyber-attackers who have bypassed the air gaps and aim at causing safety incidents and service disruptions. In this paper, we study false data injection (FDI) attacks against railways' traction power systems (TPSes). Specifically, we analyze two types of FDI attacks on the train-borne voltage, current, and position sensor measurements - which we call efficiency attack and safety attack -- that (i) maximize the system's total power consumption and (ii) mislead trains' local voltages to exceed given safety-critical thresholds, respectively. To counteract, we develop a global attack detection (GAD) system that serializes a bad data detector and a novel secondary attack detector designed based on unique TPS characteristics. With intact position data of trains, our detection system can effectively detect the FDI attacks on trains' voltage and current measurements even if the attacker has full and accurate knowledge of the TPS, attack detection, and real-time system state. In particular, the GAD system features an adaptive mechanism that ensures low false positive and negative rates in detecting the attacks under noisy system measurements. Extensive simulations driven by realistic running profiles of trains verify that a TPS setup is vulnerable to the FDI attacks, but these attacks can be detected effectively by the proposed GAD while ensuring a low false positive rate.Comment: IEEE/IFIP DSN-2016 and ACM Trans. on Cyber-Physical System

Transparency of a geographically distributed test platform for fuel cell electric vehicle powertrain systems based on x-in-the-loop approach

X-in-the-loop is a new vehicle development and validation method for increasingly complex vehicle systems, which integrates the driver and the environment. In view of recent developments in fuel cell electric vehicle powertrain systems, Tongji University and Karlsruhe Institute of Technology have jointly developed a set of distributed test platforms based on the X-in-the-loop approach. This platform contains models and test equipment for a fuel cell electric vehicle powertrain system. Due to the involvement of remote connection and the Internet, test with connected test benches will suffer great uncertainty cause of signal transfer delay. To figure out this uncertainty, the concept of transparency is introduced. Four parameters were selected as transparency parameters in this distributed test platform. These include vehicle speed, fuel cell output power, battery output power, and electric motor torque under several different configuration settings. With the help of transparency theory and statistical methodology, especially Analysis of Variance (ANOVA), the transparency of these four parameters was established, vehicle speed, electric motor torque, battery power, and fuel cell power are affected by network state, the degree of influence is enhanced in turn. Using new defined parametric and non-parametric methods, this paper identifies the statistical significance and the transparency limitations caused by Internet under these several configurations. These methods will generate inputs for developer setting the distributed test configuration. These results will contribute to optimize the process of geographically distributed validation and joint development

Electric Vehicle Efficient Power and Propulsion Systems

Vehicle electrification has been identified as one of the main technology trends in this second decade of the 21st century. Nearly 10% of global car sales in 2021 were electric, and this figure would be 50% by 2030 to reduce the oil import dependency and transport emissions in line with countries’ climate goals. This book addresses the efficient power and propulsion systems which cover essential topics for research and development on EVs, HEVs and fuel cell electric vehicles (FCEV), including: Energy storage systems (battery, fuel cell, supercapacitors, and their hybrid systems); Power electronics devices and converters; Electric machine drive control, optimization, and design; Energy system advanced management methods Primarily intended for professionals and advanced students who are working on EV/HEV/FCEV power and propulsion systems, this edited book surveys state of the art novel control/optimization techniques for different components, as well as for vehicle as a whole system. New readers may also find valuable information on the structure and methodologies in such an interdisciplinary field. Contributed by experienced authors from different research laboratory around the world, these 11 chapters provide balanced materials from theorical background to methodologies and practical implementation to deal with various issues of this challenging technology. This reprint encourages researchers working in this field to stay actualized on the latest developments on electric vehicle efficient power and propulsion systems, for road and rail, both manned and unmanned vehicles