Currently, the specifics of external conditions and peculiarities of innovation activity main subjects development determine not only the need for close, long-term scientific and technical cooperation with the state for the sustainable development of territories, but also the need to develop and substantiate proposals for managing the development of innovation processes in such a system as a whole. The article proposes a model for the representation of scientific and industrial interaction in the implementation of regional innovation processes in the form of a three-dimensional "slice" of the triple helix as a resource VRIO-profile of cooperative formation, which allows to clearly demonstrate the system of relations, identify in which direction the problem area is, influencing which it will be possible to return the system to an equilibrium state of sustainable development in a strategic perspective. The analysis of modern scientific works shows the relevance, necessity and effectiveness of using methods based on neural networks to predict changes in the state of complex socio-economic systems, such as regional innovation systems. Existing approaches, as a rule, demonstrate a narrow focus and belonging to a separate enterprise or organization, and therefore do not meet all the requirements from both the implementation of the innovation process itself and the modification of the external environment. In this connection, the authors proposed an information and analytical solution for using the described model to support decision-making on the management of cooperative formations. The developed program is based on predicting the future state (position in a three-dimensional coordinate system) of the system using deep neural networks, namely recurrent. The described practical approbation of the model can in the future serve as a basis for decision-making on the choice of forms and directions of interaction of cooperative formations in the strategic perspective.
The modern development of information security tools, along with the improvement of remote access methods, allows software and hardware to be audited without the need for direct access to the system under test. One of its components is related to the implementation of software on mobile ARM processor architectures. Within this direction of development, the approach that allows integrating Linux kernel-based distributions by introducing a virtual container chroot (change root) into the Android OS- based system and, consequently, performing penetration testing without the need to use personal computers is highlighted. An example of this approach is the Kali NetHunter distribution which allows remote system administration functionality through the KeX module. Besides the obvious advantages of KeX functionality, some disadvantages should also be mentioned: firstly, the low speed of GUI processing due to translation to remote hosts and the need to support translation at operating system level; secondly, the consumption of energy resources when using the desktop features of the KeX module. In order to solve the mentioned problems, a system of virtualization of energy-efficient container for testing the vulnerabilities of critical information objects has been developed and based on the principle of multi-containerization. The software of the system is represented by two components: an enlarged module for integration of the chroot container into the DeX environment (primary), and an enlarged module for ensuring energy efficiency using predictive neural network models based on variable time intervals (secondary). As a result of comparing the effectiveness of existing and implemented approaches in penetration testing, it is noted that the proposed system can be used in testing the security of particular platforms and systems, including highly sensitive information objects or resources.
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