A statistical-based anomaly detection method for connected cars in internet of things environment

Mee Lan Han, Sangjin Lee, Ah Reum Kang, Sungwook Kang, Jung Kyu Park, Huy Kang Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

A connected car is the most successful thing in the era of Internet of Things (IoT). The connections between vehicles and networks grow and provide more convenience to users. However, vehicles become exposed to malicious attacks from outside. Therefore, a connected car now needs strong safeguard to protect malicious attacks that can cause security and safety problems at the same time. In this paper, we proposed a method to detect the anomalous status of vehicles. We extracted the invehicle traffic data from the well-known commercial car and performed the one-way ANOVA test. As a result, our statistical-based detection method can distinguish the abnormal status of the connected cars in IoT environment.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages89-97
Number of pages9
Volume9502
ISBN (Print)9783319272924
DOIs
Publication statusPublished - 2015
Event2nd International Conference on Internet of Vehicles – Safe and Intelligent Mobility, IOV 2015 - Chengdu, China
Duration: 2015 Dec 192015 Dec 21

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9502
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2nd International Conference on Internet of Vehicles – Safe and Intelligent Mobility, IOV 2015
CountryChina
CityChengdu
Period15/12/1915/12/21

Fingerprint

Internet of Things
Anomaly Detection
Railroad cars
Attack
Thing
Anomalous
Analysis of variance (ANOVA)
Safety
Traffic
Internet of things

Keywords

  • Anomaly detection
  • ANOVA
  • Connected car
  • Internet of Things

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Han, M. L., Lee, S., Kang, A. R., Kang, S., Park, J. K., & Kim, H. K. (2015). A statistical-based anomaly detection method for connected cars in internet of things environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9502, pp. 89-97). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9502). Springer Verlag. https://doi.org/10.1007/978-3-319-27293-1_9

A statistical-based anomaly detection method for connected cars in internet of things environment. / Han, Mee Lan; Lee, Sangjin; Kang, Ah Reum; Kang, Sungwook; Park, Jung Kyu; Kim, Huy Kang.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9502 Springer Verlag, 2015. p. 89-97 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9502).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Han, ML, Lee, S, Kang, AR, Kang, S, Park, JK & Kim, HK 2015, A statistical-based anomaly detection method for connected cars in internet of things environment. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 9502, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9502, Springer Verlag, pp. 89-97, 2nd International Conference on Internet of Vehicles – Safe and Intelligent Mobility, IOV 2015, Chengdu, China, 15/12/19. https://doi.org/10.1007/978-3-319-27293-1_9
Han ML, Lee S, Kang AR, Kang S, Park JK, Kim HK. A statistical-based anomaly detection method for connected cars in internet of things environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9502. Springer Verlag. 2015. p. 89-97. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-27293-1_9
Han, Mee Lan ; Lee, Sangjin ; Kang, Ah Reum ; Kang, Sungwook ; Park, Jung Kyu ; Kim, Huy Kang. / A statistical-based anomaly detection method for connected cars in internet of things environment. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9502 Springer Verlag, 2015. pp. 89-97 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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