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Automatic Control and Computer Sciences

Erschienen in:

01.12.2022

Botnet Attack Detection Approach in IoT Networks

verfasst von: T. M. Tatarnikova, I. A. Sikarev, P. Yu. Bogdanov, T. V. Timochkina

Erschienen in: Automatic Control and Computer Sciences | Ausgabe 8/2022

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Abstract—

An approach to detecting network attacks based on deep learning (autoencoders) is proposed. It is shown that learning examples can be obtained by connecting IoT devices to the network, as long as the traffic does not carry malicious code. Statistical values and functions extracted from traffic are proposed; patterns of IoT devices are based on them.

Vorheriger Artikel Methods of Multidimensional Aggregation of Time Series of Streaming Data for Cyber-Physical System Monitoring

Nächster Artikel Trust Evaluation Problems in Big Data Analytics

Jyothsna, V., Prasad, V.V.R., and Prasad, K.M., A review of anomaly based intrusion detection systems, Int. J. Comput. Appl., 2011, vol. 28, no. 7, pp. 26–35.

Biryukov, D.N., Lomako, A.G., and Rostovtsev, Yu.G., The appearance of anticipating cyber threats risk prevention systems, Tr. SPIIRAN, 2015, no. 39, pp. 5–25. https://doi.org/10.15622/sp.39.1

Marochkina, A., Paramonov, A., and Tatarnikova, T.M., Ultra-dense Internet of Things model network, Distributed Computer and Communication Networks. DCCN 2021, Vishnevskiy, V.M., Samouylov, K.E., and Kozyrev, D.V., Eds., Communications in Computer and Information Science, vol. 1552, Cham: Springer, 2022, pp. 111–122.https://doi.org/10.1007/978-3-030-97110-6_8

Petrenko, A.S., Petrenko, S.A., Makoveichuk, K.A., and Chetyrbok, P.V., The IIoT/IoT device control model based on narrow-band IoT (NB-IoT), 2018 IEEE Conf. of Russian Young Researchers in Electrical and Electronic Engineering (ElConRus), Moscow, 2018, IEEE, 2018, pp. 950–953.https://doi.org/10.1109/EIConRus.2018.8317246

He, Z., Zhang, T., and Lee, R.B., Machine learning based DDOS attack detection from source side in cloud, IEEE 4th Int. Conf. on Cyber Security and Cloud Computing (CSCloud), New York, 2017, IEEE, 2017, pp. 114–120. https://doi.org/10.1109/CSCloud.2017.58

Sadek, R.A., Soliman, M.S., and Elsayed, H.S., Effective anomaly intrusion detection system based on neural network with indicator variable and rough set reduction, Int. J. Comput. Sci. Iss., 2013, vol. 10, no. 2, pp. 227–233.

Tatarnikova, T.M., Restricting data leakage through non-obvious features of Android 5 smartphone, Inf.-Upr. Sist., 2019, no. 5, pp. 24–29.https://doi.org/10.31799/1684-8853-2019-5-24-29

Tatarnikova, T.M., Statistical methods for studying network traffic, Inf.-Upr. Sist., 2018, no. 5, pp. 35–43.https://doi.org/10.31799/1684-8853-2018-5-35-43

Meidan, Ya., Bohadana, M., Mathov, Ya., Mirsky, Yi., Shabtai, A., Breitenbacher, D., and Elovici, Yu., N-BaIoT: Network-based detection of IoT botnet attacks using deep autoencoders, IEEE Pervasive Comput., 2018, vol. 17, no. 3, pp. 12–22.https://doi.org/10.1109/MPRV.2018.03367731CrossRef

10.

Kalinin, M., Krundyshev, V., and Zegzhda, P., Cybersecurity risk assessment in smart city infrastructures, Machines, 2021, vol. 9, no. 4, p. 78. https://doi.org/10.3390/machines9040078CrossRef

11.

Lim, S., Kalinin, M., and Zegzhda, P., Bioinspired intrusion detection in ITC infrastructures, Technological Transformation: A New Role For Human, Machines And Management. TT 2020, Schaumburg, H., Korablev, V., and Ungvari, L., Eds., Lecture Notes in Networks and Systems, vol. 157, Cham: Springer, 2021, pp. 10–22.https://doi.org/10.1007/978-3-030-64430-7_2

Titel: Botnet Attack Detection Approach in IoT Networks
verfasst von: T. M. Tatarnikova
I. A. Sikarev
P. Yu. Bogdanov
T. V. Timochkina
Publikationsdatum: 01.12.2022
Verlag: Pleiades Publishing
Erschienen in: Automatic Control and Computer Sciences / Ausgabe 8/2022
Print ISSN: 0146-4116
Elektronische ISSN: 1558-108X
DOI: https://doi.org/10.3103/S0146411622080259

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