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Industrial Automatic Control Systems and Controllers

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Using Recurrent Neural Networks to Detect Borrowed Code in the Interests of Information Security
A.S. Ostrovskiy, A.A. Gladkikh, R.S. Aristov, A.L. Kemurdzhian, M.Yu. Titov, O.V. Trubienko, S.I. Zhuravlev

The article demonstrates the approach to comparing software functions using the parameters of their control flow graphs using a bi-directional recurrent neural network. It is established that the neural network is able to develop an internal representation of the graph and metrics, allowing to distinguish the similar features of the algorithms necessary to search for the borrowed code.
Keywords: information security; software; recurrent neural networks.

Contacts: E-mail: mtitov_u@list.ru

Pp. 34-41.

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