Key words
information security, neural networks, signal analysis, information security monitoring systems, cyber-physical systems.
articles
Authors:
Semenov V., Lebedev I., Sukhoparov M. Published in
№ 5(77)
30 october 2018 year
Rubric: Data protection
Rubric: Data protection
Identification of the state of individual elements of cyber-physical systems based on external behavioral characteristics
The task of determining information security state of objects using the information of signals of
electromagnetic emissions of individual elements of devices of cyber-physical systems was investigated.
We consider the main side channels of information with which it is possible to monitor the state
of the system and analyze the software and hardware environment. Such «independent» methods of
monitoring allow analyzing the state of the system based on external behavioral characteristics within
the framework of conceptual models of autonomous agents. The statistical characteristics of signals
allowing to identify changes in the state of local devices of systems are considered. Was described an
experiment aimed at obtaining statistical information on the operation of individual elements of cyberphysical
systems. The efficiency of the neural networks approach for solving the described classification
problem, in particular, two-layer feed-forward neural networks with sigmoid hidden neurons
was investigated. The results of the experiments showed that the proposed approach is superior to the
quality of detection of anomalous states by classification based on internal indicators of the functioning
of the system. With minimal time of accumulation of statistical information using the proposed
approach based on neural networks, it becomes possible to identify the required state of the system
with a probability close to 0.85. The proposed approach of the analysis of the statistical data based
on neural networks can be used for definition of states of information safety of independent devices
of cyber-physical systems.
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