Cybersecurity is the practice of protecting computer systems, networks, programs, and data from digital attacks, damage, or unauthorized access. Cyber security technologies and solutions may not always be compatible with existing hardware and software, which could lead to various security risks. The development of artificial intelligence has led to significant improvements and notable outcomes in identifying cyberattacks. This article reviews various artificial intelligence approaches, including different machine learning, deep learning, and reinforcement learning algorithms, in cyber-attack detection. Various cryptography methods, which are utilized for security enhancement, like symmetric, asymmetric, and homomorphic cryptography, and various authentication schemes for data security, such as multifactor, digital signature, and biometric authentication, are also studied. Several parameters are taken for analysing the performance of those algorithms, such as accuracy, positive predictive value, hit rate, F1 score, error, encryption time, decryption time, and processing time, which have values of 96.24, 96.10, 95.80, 95.95, and 21.33%, 96 and 85 s. According to this review, deep learning-based DNN algorithms outperform traditional methods in cyber-attack detection. For security enhancement, the DES algorithm yields better outcomes. Biometric authentication offers enhanced security and convenience for user verification compared to traditional authentication methods.

An approach to controlling surface plasmon polaritrons (SPPs) by means of diffraction on acoustic waves is presented. The Bragg diffraction of SPPs on an ultrasonic beam propagating along an interface of media, one of which is an isotropic dielectric, is considered. It is shown that, in addition to the formation of zeroth and first diffraction order SPP beams, SPPs will also be converted into bulk radiation. Some formulas for the intensities of zeroth and first diffraction order SPP beams are also derived for main diffraction modes. The proposed method can be used in the development of modern information processing devices along with devices for the nondestructive testing of homogeneity for dielectric coatings on metal surfaces.

The response time and sensitivity in the visible spectral range of a commercial MG-32 pyroelectric detector based on the organic crystal of tetraaminodiphenyl (NZPP Vostok JSC) with a 0.5 mm thick polypropylene input window are studied. The sensor time constant is varied by connecting a capacitance $$C$$ in the range from 2 nF to 3.8 $$\mu$$ F to the feedback circuit of the receiver amplifier. With increasing capacitance in the range of 0.1–3.8 $$\mu$$ F, the receiver time constant increased linearly from 0.2 to 5 ms, and at lower capacitances it reached saturation, setting a limit of $$\approx$$ 25 $$\mu$$ s. The voltage sensitivity is tested using a diode laser ( $$\lambda=637$$ nm); at $$C=0{.}1$$ $$\mu$$ F, it is 3600 V W $${}^{-1}$$ , which is 8 $$\%$$ less than the sensitivity of the receiver without a polypropylene window. The equivalent noise power is virtually independent of the feedback capacitance in the range of $$C=0{.}002{-}0{.}1$$ $$\mu$$ F and is $$0{.}8\times 10^{-10}$$ W Hz $${}^{-1/2}$$ , while the detectivity is $$10^{9}$$ cm W Hz $${}^{-1/2}$$ . These characteristics are approximately one or two orders of magnitude superior to those of other commercial pyroelectric detectors and the Golay optoacoustic cell, making the receiver under study quite promising and versatile for many applications.

The problem of estimation of the phase coordinates of the object whose motion is described by a system of differential equations is considered. For estimation, the Kalman filter equations following from the solution to the generalized Stratonovich equation in the Gaussian approximation are used. The generalized Stratonovich equation makes it possible to consider the cases when, as an observation signal, a multidimensional image of the observation object is applied; i.e., the scalar function of an arbitrary number of variables describing the specificity of the observation device. It is shown that the data array obtained from the used set of observation devices is included into the generalized Stratonovich equation and in the Kalman filter equations in the form of an additive combination of time derivatives of the likelihood functionals of each of the observation devices. Each of these functionals can consider the correlation of observation noises.

The scheme of the Brillouin analyzer based on a self-sweeping laser that allows interrogating the fiber line with a length of 50 km with an error at a level of 1.5 MHz at a measurement time of 30 s is presented. It is shown that, potentially, the line length can be extended up to 88 and 96 km when using standard and correlation processing methods, respectively.

The problem of increasing the fault tolerance of control software for programmable logic controllers (PLCs) and developed with the process-oriented approach is addressed. Multiple access conflicts that arise in process-oriented programs when implementing mutually exclusive operations on a single executive element are considered. The causes of these conflicts are analyzed, and a modification to the mathematical model of a process-oriented program is proposed to allow for their constructive elimination. On the one hand, the elimination of this class of conflicts increases the fault tolerance of control programs; on the other hand, it has no side effects and thus makes unnecessary any change in the general program structure. The modified model is proposed to be implemented using an extension of the poST language syntax.

Functionally defined surfaces with a complex microstructure for realistic scenes are proposed. A wave optics-based model is described for visualizing surfaces with microscale roughness, which enhance the realism of objects under various observation and illumination conditions due to diffraction and mutual interference. The model simulates light transport and surface, which serve as its input data. Diffraction effects with surface roughness are demonstrated. An approximation of spatial coherence using a Gaussian filter is considered, which ultimately allows us to visualize not only glares but also higher-order diffraction.

Here we present the study of the complex permittivity of the Sr $${}_{0.75}$$ Ba $${}_{0.25}$$ Nb $${}_{2}$$ O $${}_{6}$$ ferroelectric crystal below 1 THz in the temperature range from $${+}25$$ to $${+}200^{\circ}$$ C. Notwithstanding that the relaxor is undergoing a phase transition, we have shown that the dielectric properties change slightly. A high level of stability of the dielectric permittivity was revealed for the nonpolar axis, while for the polar one it was less than 15 $$\%$$ . The estimated terahertz electro-optic coefficient of the crystal shows the potential for the Cherenkov-type terahertz generation.

A method for reconstructing fragments of optical satellite images is proposed on the basis of a deep neural network that uses a digital image acquired for the same area by a synthetic aperture radar as additional (conditional) information. The resulting solution is based on existing deep neural networks (DiffCR and Palette) used in image reconstruction tasks, with a modified spatial–channel attention module (convolutional block attention module–CBAM) and a modified loss function. Experimental studies have demonstrated improved quantitative characteristics and visual results compared to baseline models.