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Full-Text Articles in Physical Sciences and Mathematics

Vulnerabilities, Attacks, And Countermeasures In Balise-Based Train Control Systems, Yongdong Wu, Jian Weng, Zhe Tang, Xin Li, Robert H. Deng Apr 2017

Vulnerabilities, Attacks, And Countermeasures In Balise-Based Train Control Systems, Yongdong Wu, Jian Weng, Zhe Tang, Xin Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

In modern rail transport systems, balises are widely used to exchange track-train information via air-gap interface. In this paper, we first present the vulnerabilities on the standard balise air-gap interface, and then conduct vulnerability simulations using the system parameters that were specified in the European Train Control System. The simulation results show that the vulnerabilities can be exploited to launch effective and practical attacks, which could lead to catastrophic consequences, such as train derailment or collision. To mitigate the vulnerabilities and attacks, we propose to implement a challenge-response authentication process in the air-gap interface in the existing transport infrastructure.


Crowdsensing And Analyzing Micro-Event Tweets For Public Transportation Insights, Thoong Hoang, Pei Hua (Xu Peihua) Cher, Philips Kokoh Prasetyo, Ee-Peng Lim Feb 2017

Crowdsensing And Analyzing Micro-Event Tweets For Public Transportation Insights, Thoong Hoang, Pei Hua (Xu Peihua) Cher, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Efficient and commuter friendly public transportation system is a critical part of a thriving and sustainable city. As cities experience fast growing resident population, their public transportation systems will have to cope with more demands for improvements. In this paper, we propose a crowdsensing and analysis framework to gather and analyze realtime commuter feedback from Twitter. We perform a series of text mining tasks identifying those feedback comments capturing bus related micro-events; extracting relevant entities; and, predicting event and sentiment labels. We conduct a series of experiments involving more than 14K labeled tweets. The experiments show that incorporating domain knowledge …