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Monakhov, Y. M., Monakhov, M. Y., Telny, A. V., Kuznetsova, A. P..  2020.  Prediction of the Information Security State of the Protected Object Using Recurrent Correction. 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT). :602—605.

This article presents the modeling results of the ability to improve the accuracy of predicting the state of information security in the space of parameters of its threats. Information security of the protected object is considered as a dynamic system. Security threats to the protected object are used as the security system parameters most qualitatively and fully describing its behavior. The number of threats considered determines the dimension of the security state space. Based on the dynamic properties of changes in information security threats, the space region of the security system possible position at the moments of subsequent measurements of its state (a comprehensive security audit) is predicted. The corrected state of the information security system is considered to be the intersection of the area of subsequent measurement of the state of the system (integrated security audit) with the previously predicted area of the parameter space. Such a way to increase the accuracy of determining the state of a dynamic system in the space of its parameters can be called dynamic recurrent correction method. It is possible to use this method if the comprehensive security audit frequency is significantly higher than the frequency of monitoring changes in the dynamics of specific threats to information security. In addition, the data of the audit results and the errors of their receipt must be statistically independent with the results of monitoring changes in the dynamics of specific threats to information security. Improving the accuracy of the state of information security assessment in the space of the parameters of its threats can be used for various applications, including clarification of the communication channels characteristics, increasing the availability and efficiency of the telecommunications network, if it is an object of protection.

Issa, H., Tar, J. K..  2020.  Tackling Actuator Saturation in Fixed Point Iteration-based Adaptive Control. 2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI). :000221–000226.
The limited output of various drives means a challenge in controller design whenever the acceleration need of the "nominal trajectory to be tracked" temporarily exceeds the abilities of the saturated control system. The prevailing control design methods can tackle this problem either in a single theoretical step or in two consecutive steps. In this latter case in the first step the design happens without taking into account the actuator constraints, then apply a saturation compensator if the phenomenon of windup is observed. In the Fixed Point Iteration- based Adaptive Control (FPIAC) that has been developed as an alternative of the Lyapunov function-based approach the actuator saturation causes problems in its both elementary levels: in the kinematic/kinetic level where the desired acceleration is calculated, and in the iterative process that compensates the effects of modeling errors of the dynamic system under control and that of the external disturbances. The here presented approach tackles this problem in both levels by relatively simple considerations. To illustrate the method's efficiency simulation investigations were done in the FPIAC control of a modification of the van der Pol oscillator to which an additional strongly nonlinear term was added.
Höfig, K., Klug, A..  2018.  SEnSE – An Architecture for a Safe and Secure Integration of Safety-Critical Embedded Systems. 2018 26th International Conference on Software, Telecommunications and Computer Networks (SoftCOM). :1–5.

Embedded systems that communicate with each other over the internet and build up a larger, loosely coupled (hardware) system with an unknown configuration at runtime is often referred to as a cyberphysical system. Many of these systems can become, due to its associated risks during their operation, safety critical. With increased complexity of such systems, the number of configurations can either be infinite or even unknown at design time. Hence, a certification at design time for such systems that documents a safe interaction for all possible configurations of all participants at runtime can become unfeasible. If such systems come together in a new configuration, a mechanism is required that can decide whether or not it is safe for them to interact. Such a mechanism can generally not be part of such systems for the sake of trust. Therefore, we present in the following sections the SEnSE device, short for Secure and Safe Embedded, that tackles these challenges and provides a secure and safe integration of safety-critical embedded systems.

Helwa, M. K., Schoellig, A. P..  2017.  Multi-robot transfer learning: A dynamical system perspective. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). :4702–4708.

Multi-robot transfer learning allows a robot to use data generated by a second, similar robot to improve its own behavior. The potential advantages are reducing the time of training and the unavoidable risks that exist during the training phase. Transfer learning algorithms aim to find an optimal transfer map between different robots. In this paper, we investigate, through a theoretical study of single-input single-output (SISO) systems, the properties of such optimal transfer maps. We first show that the optimal transfer learning map is, in general, a dynamic system. The main contribution of the paper is to provide an algorithm for determining the properties of this optimal dynamic map including its order and regressors (i.e., the variables it depends on). The proposed algorithm does not require detailed knowledge of the robots' dynamics, but relies on basic system properties easily obtainable through simple experimental tests. We validate the proposed algorithm experimentally through an example of transfer learning between two different quadrotor platforms. Experimental results show that an optimal dynamic map, with correct properties obtained from our proposed algorithm, achieves 60-70% reduction of transfer learning error compared to the cases when the data is directly transferred or transferred using an optimal static map.

Radhika, K. R., Nalini, M. K..  2017.  Biometric Image Encryption Using DNA Sequences and Chaotic Systems. 2017 International Conference on Recent Advances in Electronics and Communication Technology (ICRAECT). :164–168.

Emerging communication technologies in distributed network systems require transfer of biometric digital images with high security. Network security is identified by the changes in system behavior which is either Dynamic or Deterministic. Performance computation is complex in dynamic system where cryptographic techniques are not highly suitable. Chaotic theory solves complex problems of nonlinear deterministic system. Several chaotic methods are combined to get hyper chaotic system for more security. Chaotic theory along with DNA sequence enhances security of biometric image encryption. Implementation proves the encrypted image is highly chaotic and resistant to various attacks.