This article delves into strategies for businesses to bolster cybersecurity and mitigate financial losses post-cyber-attacks. It leverages Lean Six Sigma methodologies and data from past research on significant data breaches in US and EU stock markets. The study investigates the link between cyber-attacks and stock market dynamics, with a focus on reputation management. Gaussian distribution and Six Sigma methodology are used for probability analysis. Key findings underscore the significance of predictability, precision, and reputation management in cyber-risk mitigation. Effective reputation management reduces insurance costs and market share loss, while inadequate management results in higher expenses. The research introduces novel insights into safeguarding a company's value, reducing vulnerabilities, and advocating for Cyber Autonomy and reputation management to lower insurance premiums and enhance protective measures.
The aim of this work is to identify the possible pivot patterns that can emerge when applying Gaussian elimination with complete pivoting (GECP) to an Hadamard matrix of order 20. A computational approach was used, with the intention of discovering as many of these pivot patterns as possible, by randomly generating Hadamard matrices from previously known ones, applying GECP to them and recording their pivot patterns.
Current weather has a significant impact on efficient flight planning in civil aviation. Configuration of areas with dangerous weather conditions, wind direction, and speed could not be precisely known at the pre-flight planning stage. Dynamic in-flight modifications of flight-planned trajectory based on current weather data can support efficient trajectory maintaining. Automatic Dependent Surveillance-Broadcast (ADS-B) supports civil aviation with precise coordinates of all airspace users. In the paper, we consider using a set of historical airplane trajectory data for particular round-trip flight connection to analyze trajectory variation based on current weather impact. We analyze parameter distributions with the help of kernel density function for total trajectory length and total flight time. Obtained distributions are useful for estimating confidence bands for a particular value of probability.
The present study aims to investigate the behaviour of several data sets when linear regression is applied to them. According to the correlation, which characterizes all the real data sets, useful remarks are derived concerning the method that will be selected for the specification of the regression parameter of the model.
The method of behavioral energy-loaded testing considered in this paper are based on Petri nets, extended by temperature and volt/ampere characteristics, and have the features of a comprehensive consideration of behavioral and energy characteristics in their relationship, performed in event aspect. These features connect the allowable boundary temperature-voltage characteristics with behavioral events/actions in positions/transitions of Petri nets. The use of the proposed method of such a special additional analysis of energy characteristics in complex testing technologies makes it possible to increase the completeness and flexibility of testing computer systems while reducing its execution time.
This paper deals with the problem of detecting the malware by using emulation approach. Modern malware include various avoid techniques, to hide its anomaly actions. Advantages of using sandbox and emulation technologies are described. Various anti-emulation techniques that are used in modern malware considered. Obfuscation as one primary approach to hide malware malicious actions described and discussed. State of emulator is presented, and the advantages of its usage are covered. Distributed model for malware detection is considered. Basic emulator and its current capabilities presented. Prepared files that represent malware are described. Experimental results for developed files that differs with included avoid techniques are presented. Disadvantages of proposed approach is described. Future research and sandbox improvement are described.
The analysis of existing platforms and tools for designing systems on chip is given. The variants of soft-processor architectures that are relevant at the current moment are considered, prospective directions of research and integration into embedded systems are determined. The overview of solutions based on the RISC-V architecture and softcore processors based on them was conducted. The existing solutions from FPGA vendors to realize the possibilities of partial reconfiguration of the system are considered. The typical problems encountered in the design of embedded systems and possible tools which can be used for requirements analysis are presented.
This research aims to assess the suitability of Ukrainian territories for the placement of solar power stations using satellite data on climate and topographic characteristics. The suitability of the territories was determined using a weighted sum method, incorporating input parameters from climate maps sourced from ERA5-Land dataset, which included data on annual global horizontal solar irradiation (GHI), accumulated annual temperature above $25^{\circ} \mathrm{C}$, average annual wind speed, and maps of accumulated annual precipitation. Additionally, topographic maps from the SRTM dataset were utilized, providing information on elevations, slopes, and terrain shading. Furthermore, data from Wikimapia on the locations of existing major solar power stations in Ukraine were used to verify the placement optimization. The results of the study revealed that the largest portion of the country (over 48%) exhibits moderate suitability scores (0.3-0.4). Favorable territories (suitability score above 0.3) outweigh unsuitable ones for solar power stations. The southern regions and the Crimean Peninsula offer the most favorable conditions for the placement of solar farms. Overall, all analyzed major solar power stations in Ukraine were located in optimal territories. Furthermore, it was found that certain regions such as Odessa, Poltava, Kharkiv, Zaporizhia, Dnipropetrovsk, Donetsk, and Luhansk demonstrate good suitability scores (0.3-0.4), yet they are not fully exploited. These regions hold significant potential for the future construction of powerful and productive solar power stations.
In this work the analysis of possible ways of providing of identification mechanism for licensing of instances of FPGA projects is carried out. The challenges of creating AI services on FGPGA-platform and the feasibility of implementation of renting procedures for them are observed. The analysis shows that the service model involves the purchase or lease of server equipment with access to FPGA resources in a form of dedicated boards or the ability to deploy a set of assets for a particular user. It’s shown that organizing licensed access to these resources and ensuring their availability for centralized use becomes imperative. It is necessary to organize security measures. For that built-in features of FPGA chip that contain Unique Identifier (UID) of each chip element within a specific board can be used. Given the extensive application of FPGA technologies in the development of FPGA-based (FaaS) AI-oriented services, there arises a demand for the management of digital rights concerning the utilization for AI products in form of Intellectual Property cores (IP-cores).
Laptop batteries contain up to four cascades of Li-ion cells connected in series. During the use of batteries the process of unbalanced degradation of the cells is happening. The dedicated protection circuit controls the voltage at each cascade of the battery and controls the discharge or charge control keys. Overdischarge or other causes can block the controller of the battery and it appears on the secondary good market. But the remaining resource of the cells allows the continue of normal operation of the accumulator. The unlocking of the controller of the laptop battery is not trivial task. But combining of the practical experience of the recovering of different batteries allows to summarize the theoretical and practical knowledge in form of the formalized models, sequences, classifications and the practical examples of repairing of batteries. The elements of method of repairing accumulators of portable electronics are proposed. The comparison of the results of theoretical research and practical attempts of the recovering the normal operation of batteries is provided in form of classification of controller models and the result of attempts.
In this paper we present a heuristic-based formula for the estimation of matrix functionals where the function is that of the inverse one and the matrix is symmetric positive definite. The stability of the estimate is proved and error bounds are derived. Several numerical results illustrating the effectiveness of the heuristic formula are presented.
Anomaly detection remains a critical task in various domains, including cybersecurity and healthcare monitoring. Traditional approaches often rely on low-level machine learning and statistical methods, which may struggle to capture complex, multidimensional data patterns and adapt to evolving anomalies. In recent years, generative adversarial networks (GANs) have demonstrated promising potential for anomaly detection due to their ability to learn the underlying data distribution. This paper presents an anomaly detection system, which leverages a GAN-based model integrated with fuzzy logic components. We explore the integration of the GAN architecture with auxiliary components to enhance the performance and robustness of the anomaly detection system. This approach endeavors to explore the practical potential of GAN-based models in the field of anomaly detection and paves the way for future research in this rapidly evolving domain.
This paper presents the preliminary fault tree analysis of the risks connected with meteorological hazards for UAS operation. The top event tree considers the general key risks for SUAS. Then the impact of meteorological hazards into influencing factors is considered in the number of basic trees. The analysis aimed to evaluate the most critical weather-related events that can impact the failure of a UAS flight. The study was done for the observation during one summer month and took into account the restricted number of meteorological elements. The presented approach can be used for understanding the weather-related risks for particular climatic zones and areas of flight to develop strategies for risk mitigation in the frame of safety risk management when sUAS operations.
This paper provides an exhaustive exploration of the challenges faced in the development and application of Virtual Reality (VR) technology. Despite VR’s revolutionary potential across various sectors, its full-fledged realization is impeded by technical, financial, and ethical hurdles. Technical issues involve the development of high-quality hardware and software, seamless integration with existing infrastructures, and the demand for extensive computational resources. Financial constraints arise from high production and maintenance costs, which limit accessibility. Ethically, VR’s immersive nature presents the potential for addiction, antisocial behavior, and data privacy concerns. The paper further discusses the trade-off decisions, complexity, technological limitations, hardware-software co-optimization, future-proofing, testing, and validation associated with VR development. Furthermore, a survey of resolutions to these challenges, as proposed in recent scientific literature, is presented. The article underscores the need for continued exploration, innovation, and refinement to overcome these hurdles and unlock the transformative power of VR technology.
The paper is devoted to the convergence of critical and non-critical IT in area of Business Analysis and Requirements Engineering. We compared the Safety and Security Life Cycle (SSLC) against the Business Analysis Life Cycle (BALC) to consider equivalency between specific stages. After that, Business Analysis techniques are proposed to cover a part of the SSLC stages with mature proven-in-use approaches. Our approach has found application in critical domains, such as the development of an Internet of Things (IoT) system for air quality monitoring and a safety-critical Programmable Logic Controller (PLC) employed within the Industrial Control Systems (ICS) for Nuclear Power Plants. These projects have revealed significant areas of improvement that warrant thorough research and discussion.
During the last two decades new types of air transportation vehicles have been developed. Integration of new aircraft types in controlled airspace requires implimintation of new surveillance technologies on board to ensure the safety of air transportation. On-board transmitter of Automatic Dependent Surveillance-Broadcast (ADS-B) will be required for any airspace user soon. ADS-B is considered the main safety system in the next generation of civil aviation. Performance of new flight vehicles requires minimizing size, reducing power, increasing functional level, and minimizing total costs. In the paper, we study potential of cheap software-defined radio like HackRF One to support low-cost on-board ADS-B equipment for civil aviation. We create a library of classes in C++ for automatic ADS-B message generation based on input data. Also, developed library was integrated into a separate software block in GNU Radio Companion. Developed block could be easily used in a variety of applications including on-board transmitter to support ADS-B.
In the paper, a method for accelerating computational implementation of the most massive open-key cryptography operation - modulo squaring of numbers whose length significantly exceeds the processor’s bit rate - is proposed and investigated. The acceleration of the calculations is achieved via the combined use of the Montgomery group reduction based on pre-calculations and dynamic reduction of the length of operands. Theoretically and experimentally, it is shown that the proposed approach reduces the modular multiplication time by 3-4 times and thereby speeds up the implementation of data protection in remote control systems based on IoT technologies.
We present the idea of creating an on-board radio direction finder for winged unmanned aerial vehicles with a wide range of unambiguous measurements and high accuracy of direction finding of radio sources. It is suggested to obtain high quality characteristics by combining signal processing in an amplitude two-antenna direction finder with wide patterns, a two-antenna direction finder with narrow patterns, and a two-antenna phase finder. For the optimal combination of different systems, which have their advantages and disadvantages, a statistical synthesis of signal processing algorithms in a six-antenna direction finder with different restrictions on input paths is performed. The analytical expressions for the marginal errors of the on-board system are obtained and their simulation is performed for different output parameters.
The primary objective of functional safety and cybersecurity co-engineering is to streamline assessment processes and enhance efficiency by implementing integrated approaches, therefore reducing overall effort and bringing several consequential advantages. Although this concept is not new, and there have already been successful attempts at its utilization in different critical domains such as nuclear, railway, and automotive, no mature approach could be easily adopted and applied during the assessment. Another challenge is that the understanding of co-engineering is essentially different, depending on domain specifics and priorities. Moreover, issues are still related to measuring efficiency achieved by co-engineering utilization. This paper addresses the current state of safety and cybersecurity co-engineering in critical domains. With a focus on nuclear, automotive, and railway domains, it proposes directions toward developing effective co-engineering frameworks for them.
