Authors
Sukhoparov M.
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Degree
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PhD in Technique, SPIIRAS |
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E-mail
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sukhoparovm@gmail.com |
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Location
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Saint-Petersburg |
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Articles
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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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Identification of abnormal functioning during the operation devices of cyber-physical systemsThe article explores the task of determining information security state of autonomous objects using
the information obtained through a side acoustic channel. The basic prerequisites for using of external
independent monitoring systems for monitoring condition of objects at the risk of the influence
of threats to information security are considered. An experiment aimed at studying the functioning
parameters of unmanned vehicles in various functioning situations was performed. The appearance
and statistical characteristics of the signals, with the help of which it becomes possible to identify abnormal
deviations during the operation of unmanned vehicles, are shown. An algorithm of two- and
three-class classification of the states of the studied objects is presented. Analysis based on the obtained
sample is very sensitive to any changes in the software and hardware configuration. At the same
time, with a minimum time of accumulation of statistical information using the proposed approach
based on a given threshold, it becomes possible to determine the point at which the attack was began.
The proposed approach model implies the possibility of using various mathematical apparatus, statistical
methods, and machine learning to achieve specified indicators for assessing the state of information
security of an object.
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