К вопросу о защите информации в интеллектуализированных образцах вооружения

Information security is a fundamental and urgent issue in the digital transformation era. Cryptographic techniques and digital signatures have been applied to protect and authenticate relevant information. However, with the advent of quantum computers and quantum algorithms, classical cryptographic techniques have been in danger of collapsing because quantum computers can solve complex problems in polynomial time. Stemming from that risk, researchers worldwide have stepped up research on post-quantum algorithms to resist attack by quantum computers. In this review paper, we survey studies in recent years on post-quantum cryptography (PQC) and provide statistics on the number and content of publications, including a literature overview, detailed explanations of the most common methods so far, current implementation status, implementation comparisons, and discussion on future work. These studies focused on essential public cryptography techniques and digital signature schemes, and the US National Institute of Standards and Technology (NIST) launched a competition to select the best candidate for the expected standard. Recent studies have practically implemented the public key encryption/key encapsulation mechanism (PKE/KEM) and digital signature schemes on different hardware platforms and applied various optimization measures based on other criteria. Along with the increasing number of scientific publications, the recent trend of PQC research is increasingly evident and is the general trend in the cryptography industry. The movement opens up a promising avenue for researchers in public key cryptography and digital signatures, especially on algorithms selected by NIST.

Introduction to Machine Learning with Applications in Information Security provides a class-tested introduction to a wide variety of machine learning algorithms, reinforced through realistic applications. The book is accessible and doesn’t prove theorems, or otherwise dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core machine learning topics in-depth, including Hidden Markov Models, Principal Component Analysis, Support Vector Machines, and Clustering. It also includes coverage of Nearest Neighbors, Neural Networks, Boosting and AdaBoost, Random Forests, Linear Discriminant Analysis, Vector Quantization, Naive Bayes, Regression Analysis, Conditional Random Fields, and Data Analysis. Most of the examples in the book are drawn from the field of information security, with many of the machine learning applications specifically focused on malware. The applications presented are designed to demystify machine learning techniques by providing straightforward scenarios. Many of the exercises in this book require some programming, and basic computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of programming experience should have no trouble with this aspect of the book. Instructor resources, including PowerPoint slides, lecture videos, and other relevant material are provided on an accompanying website: http://www.cs.sjsu.edu/~stamp/ML/. For the reader’s benefit, the figures in the book are also available in electronic form, and in color. About the Author Mark Stamp has been a Professor of Computer Science at San Jose State University since 2002. Prior to that, he worked at the National Security Agency (NSA) for seven years, and a Silicon Valley startup company for two years. He received his Ph.D. from Texas Tech University in 1992. His love affair with machine learning began in the early 1990s, when he was working at the NSA, and continues today at SJSU, where he has supervised vast numbers of master’s student projects, most of which involve a combination of information security and machine learning.

Fatal accidents are a major issue hindering the wide acceptance of safety-critical systems that employ machine learning and deep learning models, such as automated driving vehicles. In order to use machine learning in a safety-critical system, it is necessary to demonstrate the safety and security of the system through engineering processes. However, thus far, no such widely accepted engineering concepts or frameworks have been established for these systems. The key to using a machine learning model in a deductively engineered system is decomposing the data-driven training of machine learning models into requirement, design, and verification, particularly for machine learning models used in safety-critical systems. Simultaneously, open problems and relevant technical fields are not organized in a manner that enables researchers to select a theme and work on it. In this study, we identify, classify, and explore the open problems in engineering (safety-critical) machine learning systems—that is, in terms of requirement, design, and verification of machine learning models and systems—as well as discuss related works and research directions, using automated driving vehicles as an example. Our results show that machine learning models are characterized by a lack of requirements specification, lack of design specification, lack of interpretability, and lack of robustness. We also perform a gap analysis on a conventional system quality standard SQuaRE with the characteristics of machine learning models to study quality models for machine learning systems. We find that a lack of requirements specification and lack of robustness have the greatest impact on conventional quality models.

Technologies of virtual and augmented reality are gaining popularity. Virtual reality is used in many areas, including beginning to be used in the field of information and computer security. In addition, virtual reality interfaces are also susceptible to attacks. However, there are still few works on research in this area. This article provides an overview of existing solutions to computer security problems using virtual and augmented reality interfaces, as well as an overview and classification of the identified threats for these interfaces themselves.

Advanced encryption and decryption strategies are of great significance for information protection and data security. Visual optical information encryption and decryption technology plays an important role in the field of information security. However, the current optical information encryption technologies have shortcomings such as the need for external decryption equipment, the inability to read out repeatedly, and information leakage, which hinder their practical application. By combining the excellent thermal response characteristics of the MXene-isocyanate propyl triethoxy silane (IPTS)/polyethylene (PE) bilayer and the structural color generated from the laser fabricated biomimetic structural color surface, an approach of encrypt, decrypt, and transmit information has been proposed. The microgroove-induced structural color is attached to the MXene-IPTS/PE bilayer to form a colored soft actuator (CSA) to realize information encryption and decryption, and information transmission. Benefiting from the unique photon-thermal response of the bilayer actuator and the precise spectrum response of the microgroove-induced structural color, the information encryption and decryption system has the advantages of being simple and reliable, which has the potential application in the field of optical information security.

True random numbers are essential for ensuring information security and supporting simulations across various industries. With the exponential growth of data driven by advancements in artificial intelligence, robust encryption for communications has become increasingly important. While software-based deterministic random number algorithms are cost-effective and easy to use, they are vulnerable to attacks by powerful supercomputers, highlighting the need for more secure alternatives. As portable electronic devices and information-gathering sensors proliferate, portable true random number generators (TRNGs) are critical for maintaining security. In this work, hybrid material-based photodetectors composed of anionic polymers and perovskites that maximize stochastic photogeneration for TRNG applications are presented. By integrating perovskite photodetectors with simple electronic circuits, compact, low-power TRNG devices have been developed that are versatile and resilient to environmental factors. These devices generate 10000 bitss-1 without resets or delays, achieving significant miniaturization. The generated 10 Mbit random number is validated through US National Institute of Standards and Technology (NIST) testing. Using a 480000-bit random sequence, perfect image encryption, ensuring protection against hacking are demonstrated. Additionally, the perovskite TRNG can operate under external light even when embedded in pork skin, realizing its potential as an implantable device for personal security and authentication.

INTRODUCTION Today, in large part, information security is the implementation of controls and best practices suggested by consultants, standard governing bodies (i.e. National Institute of Standards & Technology) (NIST), International Organization for Standardization / International Electrotechnical Commission (ISO/IEC), etc.), the organization's information security department and, sometimes, the organization's employees. While the use of global standards of practice, top management and the information security department within the organization to guide information security planning and implementations may be useful, existing research consistently shows a positive relationship exists between user involvement in planning and the effectiveness of the information systems function within organizations (Gottschalk, 1999; Sambamurthy et al., 1994; Segars & Grover, 1998). A deliverable of the information security planning process is the organization's information security policies and procedures. Standard governing bodies (NIST, ISO/IEC) and researchers (Bidgoli, 2003; Garrison & Posey, 2006) stress the importance of creating information security policies and provide guidance on the different types of information security policies that an organization may need. This research attempts to examine the impact of end-user involvement and formalized information security policies on the effectiveness of the information security function within organizations. Specifically, this study focuses on two antecedent variables, collaborative exchange and formalization, and how it impacts the effective utilization of the information security strategies of deterrence, detection and recovery. Collaborative exchange is an assessment of the extent of collaboration between upper-level management, end users and the information security function. Formalization is an assessment of the extent of established formal information security policies within an organization. The purpose of this research is twofold. First, this research aims to examine the individual effects of formalization and collaborative exchange on the effectiveness of information security detection, deterrence, and recovery activities. Much of the effort expended in the management of information security is in developing and enforcing information security policies. By examining formalization separately, the impact of information security policy development on effective utilization of information security strategies can be assessed. The second aim of this research is to examine the impact of collaborative exchange and formalization in concert on the effectiveness of information security detection, deterrence, and recovery activities. Evaluating complementary effect of collaborative exchange and formalization on effective utilization of information security strategies provides evidence supporting the importance of establishing information security policies with input and effort from all major constituencies within the organization. This study makes several contributions to the literature and practice. First, this research provides insight into how management choices in regards to establishing formal communication channels and developing information security policies may impact the effectiveness of the information security function. Second, the presence of the dependent variable, effectiveness of detection, deterrence and recovery activities, gives academics and practitioners a success measure which can guide more effective decision making in the information security domain. The remainder of this manuscript is organized as follows. The next section discusses the literature supporting the constructs of interest in this study. The following two sections will present the methodological approach taken in this study and the results of data collection. The next section will present the efforts in data analysis. The last section will present a discussion of the important findings and limitations of this research. …

Since 1982 the US National Association of Corrosion Engineers (NACE) and the US National Institute of Standards and Technology (NIST) have collaborated under the NACE-NIST Corrosion Data Program to develop data resources of interest to the materials science and engineering communities. These resources have included expert systems, which have focused primarily on materials selection and usage applications in industry. A brief history of the program is presented, the expert systems developed therein are presented, and development methodologies are described. Particular emphasis is placed on the participation of the chemical process, oil and gas and electric power industries in the NACE-NIST Corrosion Data Program.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The airborne lunar spectral irradiance (air-LUSI) mission is an inter-agency partnership between the US National Aeronautics and Space Administration and the US National Institute of Standards and Technology. Air-LUSI aims to make SI-traceable measurements of lunar spectral irradiance at visible to near-infrared wavelengths with unprecedented accuracy. To minimize uncertainty, lunar spectra are acquired above 90 % of the Earth’s atmosphere aboard NASA’s Earth Resources aircraft, a civilian descendant of the U-2 spy plane. The data collected by the air-LUSI instrument is poised to improve upon current lunar calibrations of Earth observing satellites. The air-LUSI team recently completed their Operational Flight Campaign in Palmdale, California in March 2022. In addition to the Engineering Flight Campaign of August 2018 and the Demonstration Flight Campaign of November 2019, the air-LUSI instrument has been successfully deployed on over ten lunar spectral measurement flights at altitudes of roughly 21 km. This paper presents the simplified double gimbal design that was capable of recently tracking the Moon with a root mean square tracking error of less than 0.1&deg;.

The development and deployment of machine learning systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. Lack of diligence can lead to technical debt, scope creep and misaligned objectives, model misuse and failures, and expensive consequences. Engineering systems, on the other hand, follow well-defined processes and testing standards to streamline development for high-quality, reliable results. The extreme is spacecraft systems, with mission critical measures and robustness throughout the process. Drawing on experience in both spacecraft engineering and machine learning (research through product across domain areas), we’ve developed a proven systems engineering approach for machine learning and artificial intelligence: the Machine Learning Technology Readiness Levels framework defines a principled process to ensure robust, reliable, and responsible systems while being streamlined for machine learning workflows, including key distinctions from traditional software engineering, and a lingua franca for people across teams and organizations to work collaboratively on machine learning and artificial intelligence technologies. Here we describe the framework and elucidate with use-cases from physics research to computer vision apps to medical diagnostics.

An urgent problem in the field of information security – the provision of human resources in the field of information security in the Russian Federation is presented. One of the factors influencing this is the lack of the possibility of determining at the initial stage the optimal choice of the future direction of activity of graduates of higher educational institutions with specialization in this field. To solve this problem, it is proposed to use methods of data mining, machine learning and algorithms based on artificial neural networks. For the successful application of data mining methods, several factors should be taken into account: the data set must be large enough. Secondly; the data must be structured and analyzed to extract the most important information; the data analysis methods must be adequate and accurate in order to determine the purpose of the graduate with the highest accuracy. Taking into account these factors, the article suggests a way to form the initial data set and prepare it using statistical methods to predict the success of the professional activity of an information security specialist. The results of this work can be useful for higher educational institutions, specialists in the field of information security, heads of personnel departments who are interested in optimizing the process of selecting qualified employees in this field.

In recent years, the emergence of blockchain technology (blockchain) has become a singular, most tumultuous, and trending technology. The decentralized info in blockchain underscores information security and confidentiality. Also, the agreement mechanism in it makes positive that information is secured and legit. Throughout this paper, we have got coated the analysis on combining blockchain and machine learning technologies and demonstrate that they are attending to collaborate with efficiency and effectiveness. Machine learning might even be a general language that comes with a spread of methods, machine learning, deep learning, and reinforcement learning. These ways square measure the core technology for big information analysis. As a distributed and append-only ledger system, a blockchain can be a natural tool for sharing and handling massive information from varied sources through the incorporation of good contracts. Additional expressly, blockchain will shield information security and promote information sharing. It also permits various countries to utilize distributed computing powers, for instance, IoT, for developing on-time prediction models with varied sources of knowledge. Blockchain systems can also generate large amounts of useful data from completely different sources, and the knowledge domain analysis on combining the two technologies is of nice potential and the combination of machine learning and blockchain will give extremely precise results.

Objective: Global information and technological changes have opened up new opportunities for information and public communication processes. The purpose of the study is to analyze the level of competence of future specialists in economics and finances in the field of information security and develop recommendations for its improvement. Methods: The level of information security competencies of future specialists in economics and finance has been determined, characterized by the degree of awareness of the importance of readiness to work in corporate information security systems based on an empirical study using a survey of "Finance, banking, and insurance", "Accounting and taxation", and "Economics" students (94 people total) and a subsequent pedagogical experiment with their participation. Results: Authors of the articles have described the main methods and directions of forming the ability of a future specialist in economics and finance to work responsibly in corporate institutions, which are associated, first of all, with the introduction of a special course "Security of financial and economic information in information systems". Conclusion: The lack of readiness among economics and finance specialists to work in corporate information security systems may hinder the achievement of sustainable development. To address this issue, it is important to prepare future specialists in economics and finance for professional activity in the conditions of a corporate information security system. It is possible to prevent the development of negative phenomena in the field of information security with the help of the purposeful formation of appropriate competencies in specialists in economics and finance.

This article examines the international legal aspect and comparative characteristics of the development of information security in Russia and the countries of the world. The definition, forms, types and characteristics of various aspects and aspects of information security of information systems are revealed. Subject, object and conceptual possibilities of information security. The article is devoted to the legal regulation of information security in international cooperation. A detailed analysis of international regulatory legal acts that consolidate the foundations of information security has been carried out. The main directions of development of Russian and foreign legislation in the field of information security and the role of international bodies in ensuring information security are considered. The author concludes that the issue of improving the legal provision of information security in the field of international cooperation is clearly evidenced by the intensification of state cooperation within the framework of regional associations in the field of information security, as well as the conclusion of a number of international agreements and the adoption of joint statements in this area. In accordance with the current legislation, the article defines the level and degree of information protection. The emphasis is on the latest changes in legislation on information, information technologies as a set of measures to prevent unauthorized use, abuse, changes in information, facts, data in the historical and legal aspect of ensuring information security of information systems.

Steven R. Ray, Chief Manufacturing Systems Integration Division at the US National Institute of Standards and Technology to give his perspectives on the changing role of Information Standards in Manufacturing. As the person directing the national US response in the area of information standards for manufacturing, Steve enjoys a unique vantage point on the field. Steve notes that our times are characterised by an increase in the importance of mastering information standards as a competitive enabler. However, the scope of activities covered by information standards is growing, making it harder for companies to stay abreast of all the developments and opportunities. Steve's organisation at NIST plays a key role in assuring that US manufacturers can efficiently incorporate information standards for manufacturing into their development plans.