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This article describes the transformation of an enterprise en route from the conventional construction according to the Industrial Control Systems (ICS) architecture to the architecture of the Industrial Internet of Things (IIoT). The main cybersecurity threats that must be taken into account in the digital transformation are considered. The distinct features of each of the phases are described.

Smart infrastructure integrates cyberphysical systems, self-organizing networks of devices, fog computing to enhance the quality and convenience of manufacturing and social life, providing efficient resource management and increasing productivity and availability of traditional services. New technologies are characterized with a high degree of heterogeneity, structural complexity, and dynamic topology that result in a large number of new information and cyber security threats. Given a high degree of integration of digital cyber space into the processes of management, monitoring, aggregation, and data transferring, an assessment of its security level is a necessary requirement to maintain and control a safe and reliable environment for handling data and performing physical processes. Risk analysis and assessment is an extremely important task at all stages of the life cycle of subsystems and components of the smart environment. It allows us to assess a level of protection, identify vulnerable assets, and counteract the most likely directions of security threats. The known methods for security risk assessment do not consider the features of modern smart technologies, and this forces us to search for new approaches. This paper proposes a comprehensive method that includes a calculation of security indicators, risk assessment and selection of protective measures, based on attack graphs and thus allows us to consider the dynamics of changes in the components of the smart infrastructure. The automated system for assessing the security risks in the smart infrastructure and choosing the protective measures has been implemented.

This article considers security provision in wireless sensor networks on the basis of the trust model. The operating principles of sensor networks are analyzed, and the classification of routing techniques is composed. Typical threats are analyzed and existing attacks against Wireless Sensor Networks (WSNs) identified. A technique of protection against malicious nodes is elaborated using the trust model. The experimental assessment of the technique for efficiency is performed by modeling its work in a WSN simulator.

This paper considers the possibility of using prefractal graph theory to ensure information security of Vehicular ad hoc Networks (VANETs) and describes prefractal graph recognition algorithms developed for this purpose.

This paper considers cybersecurity threats for vehicular ad hoc networks and also describes the developed classification of these threats.

The results of analyzing the mechanisms and channels for replicating user data have been given. The replication mechanisms have been classified. Their advantages and drawbacks have been found. A method has been proposed that uses NFC to establish the secure data replication channel.

The security of wireless self-organized networks has been considered. A “black hole” attack aimed at violating the operability of these networks has been explored and analyzed. Recommendations on defending against such an attack have been made.

In this paper, a survey is given of the approaches, methods, and algorithms used for creating personalized three-dimensional models of human's head from photographs or video. All stages of the model construction are considered in detail. These stages include image marking, camera registering, geometrical model adaptation, texture formation, and modeling of additional elements, such as eyes and hair. Some technologies of the animation of the models obtained, including that based on the MPEG-4 standard, are analyzed, and examples of the applications that use these technologies are given. In conclusion, some prospects of the developments in this field of the computer graphics are discussed.

Texture compression is recently one of the most important topics of 3D scene rendering techniques, because it allows rendering more complicated high-resolution scenes. However, because of some special requirements for these type of techniques, the commonly used block decomposition approach may introduce visual degradation of image details due to lack of colors. We present here a new approach to texture compression, which allows sharing of one color by several blocks providing a larger number of unique colors in each particular block and the best compression ratio. We also present an iterative algorithm for obtaining distributed colors on a texture, and discuss some advantages of our approach. The paper concludes with comparison of our technique with S3TC and other block decomposition methods.

The problem of generating vector representation of a raster image has been the question of present interest for decades. Although, there are many approaches to this problem, most of them suffer from sophisticated computations and irrational memory usage. We introduce here a new skeletonization algorithm that is very efficient in terms of time and memory consumption. Starting from the description of our approach to the concept of skeleton on raster grid, we present a comprehensive explanation of the algorithm. Its main idea consists of generating a special polyline for each raster line considering them in top-to-bottom direction; skeleton is constructed from points of these polylines. The skeletons obtained by our algorithm allow the precise reconstruction of the initial raster shapes; therefore they may reflect some artifacts possible on raster grid. For this reason, we also present here two algorithms of simplification and our approach to defects filtering on a stage of skeleton generation. The time of simplification by presented algorithms depends linearly on the number of input points that makes these methods fast and efficient. The paper concludes with performance evaluation and discussion of possible implementations of the introduced techniques.

Image-based object modeling has emerged as an important computer vision application. Typically, the process starts with the acquisition of the image views of an object. These views are registered within the global coordinate system using structure-and-motion techniques, while on the next step the geometric shape of an object is recovered using stereo and/or silhouette cues. This paper considers the final step, which creates the texture map for the recovered geometry model. The approach proposed in the paper naturally starts by backprojecting original views onto the obtained surface. A texture is then mosaiced from these back projections, whereas the quality of the mosaic is maximized within the process of Markov random field energy optimization. Finally, the residual seams between the mosaic components are removed via seam levelling procedure, which is similar to gradient-domain stitching techniques recently proposed for image editing. Unlike previous approaches to the same problem, intensity blending as well as image resampling are avoided on all stages of the process, which ensures that the resolution of the produced texture is essentially the same as that of the original views. Importantly, due to restriction to non-greedy energy optimization techniques, good results are produced even in the presence of significant errors on image registration and geometric estimation steps.

Visibility estimation is arguably the most difficult problem in dense 3D reconstruction from multiple arbitrary views. In this paper, we propose a simple new approach to estimating visibility based on position and orientation of local surface patches. Using our concept of oriented visibility, we present a new algorithm for multiview reconstruction based on exact global optimization of surface photoconsistency using graph cuts on a CW-complex. In contrast to many previous methods for 3D reconstruction from arbitrary views, our method does not depend on initialization and is robust to photometrically difficult situations.

Spatial patches have been introduced (Ivanov and Kuzmin, 2001) as an alternative primitive for the representation of 3D objects potentially acquired from real life. Defined as range images of small regions of an object's surface, they have proven to allow for efficient storage and rendering of such surfaces, and they also exhibit great descriptive capabilities. We present several technologies that we have developed for generating 3D objects represented by spatial patches. These technologies allowed us to convert explicitly defined surfaces, textured polygonal meshes, range images and point clouds to the proposed representation. We also describe how advantageous properties of the new primitive are exploited for efficient reconstruction from range images, discuss the particular problems that we faced during our research, provide many examples to demonstrate the results that we achieved, and conclude with discussion of future work.

DNA sequence information underpins genetic research, enabling discoveries of important biological or medical benefit. Sequencing projects have traditionally used long (400-800 base pair) reads, but the existence of reference sequences for the human and many other genomes makes it possible to develop new, fast approaches to re-sequencing, whereby shorter reads are compared to a reference to identify intraspecies genetic variation. Here we report an approach that generates several billion bases of accurate nucleotide sequence per experiment at low cost. Single molecules of DNA are attached to a flat surface, amplified in situ and used as templates for synthetic sequencing with fluorescent reversible terminator deoxyribonucleotides. Images of the surface are analysed to generate high-quality sequence. We demonstrate application of this approach to human genome sequencing on flow-sorted X chromosomes and then scale the approach to determine the genome sequence of a male Yoruba from Ibadan, Nigeria. We build an accurate consensus sequence from >30x average depth of paired 35-base reads. We characterize four million single-nucleotide polymorphisms and four hundred thousand structural variants, many of which were previously unknown. Our approach is effective for accurate, rapid and economical whole-genome re-sequencing and many other biomedical applications.