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Practical application of neural networks to protect information management systems critical facilities from DDOS-attacks

Keywords:

R.B. Rashevskiy - Student, Department of Automation and Telemechanics, Perm National Research Polytechnic University. E-mail: roman@rashevskiy.com A.S. Shaburov - Ph.D. (Eng.), Associate Professor, Department of Automation and Telemechanics, Perm National Research Polytechnic University. E-mail: shans@ at.pstu.ru


The problem of information security of critical facilities is urgent due to a significant increase in the number of targeted cyber-attacks against control informational and telecommunication systems. In this regard, it is necessary to introduce innovative solutions that ensure the effective providing protection of information in information and control systems (ICS). The methods of detection of computer attacks can be attributed with the methods based on the use of neural and immune networks. In this case, for the detection of computer attacks over a period of time there is a training of the neural network when the behavior of computer information system is considered to be normal. The launch of a neural network in the recognition mode occurs after the learning process. Availability of attack determined by the deviation in the recognition of normal behavior in the input stream. Practical application of neural networks to protect information and control systems from DDOS-attacks consists in determining legitimacy of the HTTP-request based on constructed feature-vector at the output of the neural network.
References:

 

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May 29, 2020

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