Parallel anomaly detection algorithm for cybersecurity on the highspeed train control system
With the rapid development of the high-speed train industry, the high-speed train control system has now been exposed to a complicated network environment full of dangers. This paper provides a speculative parallel data detection algorithm to rapidly detect the potential threats and ensure data tran...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2022-01-01
|
| Series: | Mathematical Biosciences and Engineering |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2022015?viewType=HTML |
| _version_ | 1818955062337077248 |
|---|---|
| author | Zhoukai Wang Xinhong Hei Weigang Ma Yichuan Wang Kan Wang Qiao Jia |
| author_facet | Zhoukai Wang Xinhong Hei Weigang Ma Yichuan Wang Kan Wang Qiao Jia |
| author_sort | Zhoukai Wang |
| collection | DOAJ |
| description | With the rapid development of the high-speed train industry, the high-speed train control system has now been exposed to a complicated network environment full of dangers. This paper provides a speculative parallel data detection algorithm to rapidly detect the potential threats and ensure data transmission security in the railway network. At first, the structure of the high-speed train control data received by the railway control center was analyzed and divided tentatively into small chunks to eliminate the inside dependencies. Then the traditional threat detection algorithm based on deterministic finite automaton was reformed by the speculative parallel optimization so that the inline relationship's influences that affected the data detection order could be avoided. At last, the speculative parallel detection algorithm would inspect the divided data chunks on a distributed platform. With the help of both the speculative parallel technique and the distributed platform, the detection deficiency for train control data was improved significantly. The results showed that the proposed algorithm exhibited better performance and scalability when compared with the traditional, non-parallel detection method, and massive train control data could be inspected and processed promptly. Now it has been proved by practical use that the proposed algorithm was stable and reliable. Our local train control center was able to quickly detect the anomaly and make a fast response during the train control data transmission by adopting the proposed algorithm. |
| first_indexed | 2024-12-20T10:32:05Z |
| format | Article |
| id | doaj.art-ce62340a8ac048d384df229d71b79a4b |
| institution | Directory Open Access Journal |
| issn | 1551-0018 |
| language | English |
| last_indexed | 2024-12-20T10:32:05Z |
| publishDate | 2022-01-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj.art-ce62340a8ac048d384df229d71b79a4b2022-12-21T19:43:43ZengAIMS PressMathematical Biosciences and Engineering1551-00182022-01-0119128730810.3934/mbe.2022015Parallel anomaly detection algorithm for cybersecurity on the highspeed train control systemZhoukai Wang0Xinhong Hei1Weigang Ma 2Yichuan Wang3Kan Wang4Qiao Jia 51. College of Computer Science and Engineering, Xi'an University of Technology, Xi'an 710048, China1. College of Computer Science and Engineering, Xi'an University of Technology, Xi'an 710048, China 2. Shaanxi Provincial Key Laboratory of Network Computing and Security Technology, Xi'an 710048, China1. College of Computer Science and Engineering, Xi'an University of Technology, Xi'an 710048, China1. College of Computer Science and Engineering, Xi'an University of Technology, Xi'an 710048, China 2. Shaanxi Provincial Key Laboratory of Network Computing and Security Technology, Xi'an 710048, China1. College of Computer Science and Engineering, Xi'an University of Technology, Xi'an 710048, China1. College of Computer Science and Engineering, Xi'an University of Technology, Xi'an 710048, ChinaWith the rapid development of the high-speed train industry, the high-speed train control system has now been exposed to a complicated network environment full of dangers. This paper provides a speculative parallel data detection algorithm to rapidly detect the potential threats and ensure data transmission security in the railway network. At first, the structure of the high-speed train control data received by the railway control center was analyzed and divided tentatively into small chunks to eliminate the inside dependencies. Then the traditional threat detection algorithm based on deterministic finite automaton was reformed by the speculative parallel optimization so that the inline relationship's influences that affected the data detection order could be avoided. At last, the speculative parallel detection algorithm would inspect the divided data chunks on a distributed platform. With the help of both the speculative parallel technique and the distributed platform, the detection deficiency for train control data was improved significantly. The results showed that the proposed algorithm exhibited better performance and scalability when compared with the traditional, non-parallel detection method, and massive train control data could be inspected and processed promptly. Now it has been proved by practical use that the proposed algorithm was stable and reliable. Our local train control center was able to quickly detect the anomaly and make a fast response during the train control data transmission by adopting the proposed algorithm.https://www.aimspress.com/article/doi/10.3934/mbe.2022015?viewType=HTMLcybersecurityhigh-speed traincontrol systemparallel computingdistributed computing |
| spellingShingle | Zhoukai Wang Xinhong Hei Weigang Ma Yichuan Wang Kan Wang Qiao Jia Parallel anomaly detection algorithm for cybersecurity on the highspeed train control system Mathematical Biosciences and Engineering cybersecurity high-speed train control system parallel computing distributed computing |
| title | Parallel anomaly detection algorithm for cybersecurity on the highspeed train control system |
| title_full | Parallel anomaly detection algorithm for cybersecurity on the highspeed train control system |
| title_fullStr | Parallel anomaly detection algorithm for cybersecurity on the highspeed train control system |
| title_full_unstemmed | Parallel anomaly detection algorithm for cybersecurity on the highspeed train control system |
| title_short | Parallel anomaly detection algorithm for cybersecurity on the highspeed train control system |
| title_sort | parallel anomaly detection algorithm for cybersecurity on the highspeed train control system |
| topic | cybersecurity high-speed train control system parallel computing distributed computing |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2022015?viewType=HTML |
| work_keys_str_mv | AT zhoukaiwang parallelanomalydetectionalgorithmforcybersecurityonthehighspeedtraincontrolsystem AT xinhonghei parallelanomalydetectionalgorithmforcybersecurityonthehighspeedtraincontrolsystem AT weigangma parallelanomalydetectionalgorithmforcybersecurityonthehighspeedtraincontrolsystem AT yichuanwang parallelanomalydetectionalgorithmforcybersecurityonthehighspeedtraincontrolsystem AT kanwang parallelanomalydetectionalgorithmforcybersecurityonthehighspeedtraincontrolsystem AT qiaojia parallelanomalydetectionalgorithmforcybersecurityonthehighspeedtraincontrolsystem |