Bazhayev N.A., Lebedev I.S., Krivtsova I.E. Analysis of statistical data from network infrastructure monitoring to detect abnormal behavior of system local segments. Scientific and Technical Journal of Information Technologies, Mechanics and Optics
, 2017, vol. 17, no. 1, pp. 92–99. doi: 10.17586/2226-1494-2017-17-1-92-99
We propose a method of information security monitoring for a wireless network segments of low-power devices, "smart house", "Internet of Things". We have carried out the analysis of characteristics of systems based on wireless technologies, resulting from passive surveillance and active polling of devices that make up the network infrastructure. We have considered a number of external signs of unauthorized access to a wireless network by the potential information security malefactor. The model for analysis of information security conditions is based on the identity, quantity, frequency, and time characteristics. Due to the main features of devices providing network infrastructure, estimation of information security state is directed to the analysis of the system normal operation, rather than the search for signatures and anomalies during performance of various kinds of information attacks. An experiment is disclosed that provides obtaining statistical information on the remote wireless devices, where the accumulation of data for decision-making is done by comparing the statistical information service messages from end nodes in passive and active modes. We present experiment results of the information influence on a typical system. The proposed approach to the analysis of network infrastructure statistical data based on naive Bayesian classifier can be used to determine the state of information security.
information security, "soft space" wireless networks, personal networks, information security model References
1. Kumar P., Ylianttila M., Gurtov A., Lee S.-G., Lee H.-J. An efficient and adaptive mutual authentication framework for heterogeneous wireless sensor networks-based applications. Sensors
, 2014, vol. 14, no. 2, pp. 2732–2755. doi: 10.3390/s140202732
2. Sridhar P., Sheikh-Bahaei S., Xia S., Jamshidi M. Multi agent simulation using discrete event and soft-computing methodologies. Proc. IEEE Int. Conf. on Systems, Man and Cybernetics. Washington, 2003, vol. 2, pp. 1711–1716.
3. Page J., Zaslavsky A., Indrawan M. Countering security vulnerabilities using a shared security buddy model schema in mobile agent communities. Proc. 1st Int. Workshop on Safety and Security in Multi-Agent Systems, SASEMAS, 2004, pp. 85–101.
4. Zikratov I.A., Zikratova T.V., Lebedev I.S. Trust model for information security of multi-agent robotic systems with a decentralized management. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2014, no. 2, pp. 47–52. (In Russian).
5. Zikratov I.A., Lebedev I.S., Gurtov A.V. Trust and reputation mechanisms for multi-agent robotic systems. Lecture Notes in Computer Science
, 2014, vol. 8638, pp. 106–120. doi: 10.1007/978-3-319-10353-2_10
6. Wyglinski A.M., Huang X., Padir T., Lai L., Eisenbarth T.R., Venkatasubramanian K. Security of autonomous systems employing embedded computing and sensors. IEEE Micro
, 2013, vol. 33, pp. 80–86. doi: 10.1109/MM.2013.18
7. Lebedev I.S., Korzhuk V.M. The monitoring of information security of remote devices of wireless networks. Lecture Notes in Computer Science
, 2015, vol. 9247, pp. 3–10. doi: 10.1007/978-3-319-23126-6_1
8. Prabhakar M., Singh J.N., Mahadevan G.
Nash equilibrium and Marcov chains to enhance game theoretic approach for vanet security. Advances in Intelligent Systems and Computing
, 2013, vol. 174 AISC, pp. 191–199. doi: 10.1007/978-81-322-0740-5_24
9. Bazhayev N., Lebedev I., Korzhuk V., Zikratov I. Monitoring of the information security of wireless remote devices. Proc. 9th Int. Conf. on Application of Information and Communication Technologies
. Rostov-on-Don, Russian Federation, 2015, pp. 233–236. doi: 10.1109/ICAICT.2015.7338553
10. Nikolaevskiy I., Lukyanenko A., Polishchuk T., Polishchuk V.M., Gurtov A.V. isBF: scalable in-packet bloom filter based multicast. Computer Communications
, 2015, vol. 70, pp. 79–85. doi: 10.1016/j.comcom.2015.05.002
11. Al-Naggar Y., Koucheryavy A. Fuzzy logic and Voronoi diagram using for cluster head selection in ubiquitous sensor networks. Lecture Notes in Computer Science
, 2014, vol. 8638, pp. 319–330. doi: 10.1007/978-3-319-10353-2_28
12. Chehri A., Moutah H.T. Survivable and scalable wireless solution for e-health and emergency applications. Proc. 1st Int. Workshop on Engineering Interactive Computing Systems for Medicine and Health Care. Pisa, Italy, 2011, pp. 25–29.
13. Krivtsova I., Lebedev I., Sukhoparov M., Bazhayev N., Zikratov I., Ometov A., Andreev S., Masek P., Fujdiak R., Hosek J. Implementing a broadcast storm attack on a mission-critical wireless sensor network. Lecture Notes in Computer Science, 2016, vol. 9674, pp. 297–308.
14. Bazhayev N.A., Krivtsova I.E., Lebedev I.S. Availability research of remote devices for wireless networks. Scientific and Technical Journal of Information Technologies, Mechanics and Optics
, 2016, vol. 16, no. 3, pp. 467–473. doi: 10.17586/2226-1494-2016-16-3-467-473
. (In Russian).
15. Isakeev D.G., Zikratova T.V., Lebedev I.S., Shabanov D.P. The estimation of secure condition of multi-agent robotic system in case of information influence on the single component. Herald of Computer and Information Technologies, 2015, no. 1, pp. 43–49. (In Russian).