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2019 | OriginalPaper | Buchkapitel

Outlier Detection of Internet of Vehicles

verfasst von : Yingming Zeng, Huanlei Zhao, Haibin Zhang, Qian Zhang

Erschienen in: Security, Privacy, and Anonymity in Computation, Communication, and Storage

Verlag: Springer International Publishing

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Abstract

With the development of the Internet of Things (IoT) and automobile industry in recent years, the Internet of Vehicle (IoV) has become a future direction of automobile development. Due to the large amount of vehicles, the opening of wireless media, the high-speed movement of vehicles and the impact of the environment, it is inevitable to produce abnormal data in IoVs including data tampering, loss, disorder and so on. However, there are few systematic research results for outlier detection of IoVs. The usability of the existing outlier detection schemes and their performances are not yet evaluated. To this issue, we select six applicable schemes and propose the outlier detection process for IoVs. Then we evaluate the comparison performances of the proposed schemes on real vehicle data collected by a Focus car.

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Literatur
1.
Zurück zum Zitat Zhou, Z., Gao, C., Xu, C., et al.: Social big-data-based content dissemination in internet of vehicles. IEEE Trans. Ind. Inf. 14(2), 768–777 (2018)CrossRef Zhou, Z., Gao, C., Xu, C., et al.: Social big-data-based content dissemination in internet of vehicles. IEEE Trans. Ind. Inf. 14(2), 768–777 (2018)CrossRef
2.
Zurück zum Zitat Lu, N., Cheng, N., Zhang, N., et al.: Connected vehicles: solutions and challenges. IEEE Internet Things J. 1(4), 289–299 (2014)CrossRef Lu, N., Cheng, N., Zhang, N., et al.: Connected vehicles: solutions and challenges. IEEE Internet Things J. 1(4), 289–299 (2014)CrossRef
3.
Zurück zum Zitat Praba, V.L., Ranichitra, A.: Isolating malicious vehicles and avoiding collision between vehicles in VANET. In: IEEE International Conference on Communication & Signal Processing, pp. 811–815 (2013) Praba, V.L., Ranichitra, A.: Isolating malicious vehicles and avoiding collision between vehicles in VANET. In: IEEE International Conference on Communication & Signal Processing, pp. 811–815 (2013)
4.
Zurück zum Zitat Alheeti, K.A., Gruebler, A., Mcdonaldmaier, K.D.: An intrusion detection system against malicious attacks on the communication network of driverless cars. In: IEEE Consumer Communications and Networking Conference, pp. 916–921 (2015) Alheeti, K.A., Gruebler, A., Mcdonaldmaier, K.D.: An intrusion detection system against malicious attacks on the communication network of driverless cars. In: IEEE Consumer Communications and Networking Conference, pp. 916–921 (2015)
5.
Zurück zum Zitat Zhang, M., Chen, C., Wo, T., et al.: SafeDrive: online driving anomaly detection from large-scale vehicle data. IEEE Trans. Ind. Inf. 13(4), 2087–2096 (2017)CrossRef Zhang, M., Chen, C., Wo, T., et al.: SafeDrive: online driving anomaly detection from large-scale vehicle data. IEEE Trans. Ind. Inf. 13(4), 2087–2096 (2017)CrossRef
6.
Zurück zum Zitat Ebrahim, B., Ozgul, S., Muammer, E.: Exponential smoothing of multiple reference frame components with GPUs for real-time detection of time-varying harmonics and interharmonics of EAF currents. IEEE Trans. Ind. Appl. 54, 6566–6575 (2018)CrossRef Ebrahim, B., Ozgul, S., Muammer, E.: Exponential smoothing of multiple reference frame components with GPUs for real-time detection of time-varying harmonics and interharmonics of EAF currents. IEEE Trans. Ind. Appl. 54, 6566–6575 (2018)CrossRef
7.
Zurück zum Zitat Ballal, T., Suliman, M.A., Al-Naffouri, T.Y.: Bounded perturbation regularization for linear least squares estimation. IEEE Access 5, 27551–27562 (2017)CrossRef Ballal, T., Suliman, M.A., Al-Naffouri, T.Y.: Bounded perturbation regularization for linear least squares estimation. IEEE Access 5, 27551–27562 (2017)CrossRef
8.
Zurück zum Zitat Hayashi, H., Shibanoki, T., Shima, K., et al.: A recurrent probabilistic neural network with dimensionality reduction based on time-series discriminant component analysis. IEEE Trans. Neural Netw. Learn. Syst. 26(12), 3021–3033 (2015)MathSciNetCrossRef Hayashi, H., Shibanoki, T., Shima, K., et al.: A recurrent probabilistic neural network with dimensionality reduction based on time-series discriminant component analysis. IEEE Trans. Neural Netw. Learn. Syst. 26(12), 3021–3033 (2015)MathSciNetCrossRef
9.
Zurück zum Zitat Zhang, S., Li, X., et al.: Efficient kNN classification with different numbers of nearest neighbors. IEEE Trans. Neural Netw. Learn. Syst. 9, 1774–1785 (2018)MathSciNetCrossRef Zhang, S., Li, X., et al.: Efficient kNN classification with different numbers of nearest neighbors. IEEE Trans. Neural Netw. Learn. Syst. 9, 1774–1785 (2018)MathSciNetCrossRef
10.
Zurück zum Zitat Kosasih, K., Abeyratne, U.R., Swarnkar, V., et al.: Wavelet augmented cough analysis for rapid childhood pneumonia diagnosis. IEEE Trans. Biomed. Eng. 62(4), 1185–1194 (2015)CrossRef Kosasih, K., Abeyratne, U.R., Swarnkar, V., et al.: Wavelet augmented cough analysis for rapid childhood pneumonia diagnosis. IEEE Trans. Biomed. Eng. 62(4), 1185–1194 (2015)CrossRef
11.
Zurück zum Zitat Xing, Y.Y., Wu, X.Y., Jiang, P., et al.: Dynamic Bayesian evaluation method for system reliability growth based on in-time correction. IEEE Trans. Reliab. 59(2), 309–312 (2010)CrossRef Xing, Y.Y., Wu, X.Y., Jiang, P., et al.: Dynamic Bayesian evaluation method for system reliability growth based on in-time correction. IEEE Trans. Reliab. 59(2), 309–312 (2010)CrossRef
Metadaten
Titel
Outlier Detection of Internet of Vehicles
verfasst von
Yingming Zeng
Huanlei Zhao
Haibin Zhang
Qian Zhang
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-24900-7_15