Cyber-physical Systems Information Research Articles

Аналіз статистичних показників дисперсії, асиметрії та ексцесу при визначенні порушень інформаційної безпеки кіберфізичних систем вітрових генераторів

The active introduction of intelligent systems that closely interact with physical processes to solve a wide range of different tasks of human life increases the relevance of risk analysis associated with the functioning of such systems. Such hybrid complex intelligent systems belong to the class of cyberphysical systems (CPS). Violations of CPS security caused by outside interference in the information flow can lead to economic losses, environmental threats, and threats to human life and health. A significant increase in incidents of violation of the safety of CPS wind turbines determines the relevance of research on methods for protecting such systems. The subject matter of the study in the article is the process of determining violations of the information security of the CPS of a wind generator based on the analysis of statistical indicators of variance, asymmetry, and kurtosis of the input parameter "Power" collected by CPS sensors. The goal is to develop an algorithm for determining violations of the information security of the CPS using methods for analyzing statistical indicators of variance, asymmetry, and kurtosis. The tasks to be solved are: to formalize the process of identifying falsified data in the information flow of the CPS; to determine the advantages and disadvantages of existing methods for ensuring the information security of the CPS; to determine the degree of changes in statistical indicators of variance, asymmetry, and kurtosis of the sample of the "Power" parameter of the wind generator in the presence of misinformation in the information flow; to analyze the possibility of supplementing and further improving the proposed algorithm. The methods used are analysis of statistical indicators of variance, asymmetry, and kurtosis of the sample of the parameter "Power" of the wind generator. The following results are obtained: the general characteristics of the CPS and features of the functioning of the CPS of the wind turbine as the object of research of this work are considered; an initial algorithm for determining violations of the information security of the CPS of wind turbine based on the use of statistical indicators of variance, asymmetry, and excess is developed; the fact of artificial substitution of data for the parameter "power" of the information flow of the CPS of a wind turbine is determined; ways to improve the developed algorithm using one-factor variance analysis, bootstrap methods are proposed. Conclusions. The scientific novelty of the results obtained consists of the development of an improved algorithm for determining the fact of data falsification in the CPS information flow based on the analysis of variance, asymmetry, and kurtosis indicators; the use of a statistical method for determining CPS security violations, analyzing the shortcomings of existing methods for determining CPS security violations and the possibility of their comprehensive improvement. The issues of the possibility of improving the developed method and testing the method in the future are also considered.

An Efficient Encryption Algorithm for the Security of Sensitive Private Information in Cyber-Physical Systems

The new developments in smart cyber-physical systems can be shown to include smart cities, Internet of things (IoT), and for the most part smart anything. To improve the security of sensitive personal information (SPI) in cyber-physical systems, we present some novel ideas related to the encryption of SPI. Currently, there are issues in traditional encryption methods, such as low speed of information acquisition, low recognition rate, low utilization rate of effective information resources, and high delay of information query. To address these issues, we propose a novel efficient encryption algorithm for the security of incremental SPI. First, our proposed method analyzes user information resources and determines valid data to be encrypted. Next, it uses adaptive acquisition methods to collect information, and uses our encryption method to complete secure encryption of SPI according to the acquisition results. Our experimental analysis clearly shows that the algorithm effectively improves the speed of information acquisition as well as effective information recognition rate, thus enhancing the security of SPI. The encryption model in turn can provide a strong guarantee for user information security.

Privacy-preserving big data analytics for cyber-physical systems

Cyber-physical systems (CPS) generate big data collected from combining physical and digital entities, but the challenge of CPS privacy-preservation demands further research to protect CPS sensitive information from unauthorized access. Data mining, perturbation, transformation and encryption are techniques extensively used to preserve private information from disclosure whilst still providing insight, but these are limited in their effectiveness in still allowing high-level analysis. This paper studies the role of big data component analysis for protecting sensitive information from illegal access. The independent component analysis (ICA) technique is applied to transform raw CPS information into a new shape whilst preserving its data utility. The mechanism is evaluated using the power CPS dataset, and the results reveal that the technique is more effective than four other privacy-preservation techniques, obtaining a higher level of privacy protection. In addition, the data utility is tested using three machine learning algorithms to estimate their capability of identifying normal and attack patterns before and after transformation.

Approaches to Modeling the Security of Cyberphysical Systems

This paper considers features of cyberphysical systems (CPSs) as complexes combining physical and information components. Approaches to modeling CPSs based on graphs and stochastic dynamics are analyzed. Common features and further directions in CPS modeling are identified. The development direction of the homeostasis-based CPS information security modeling is determined.

Systematization and security assessment of cyber-physical systems

In this paper, the features of cyber-physical systems (CPSs) from the point of view of information security have been considered and CPSs have been classified. The authors have analyzed approaches to security assessments and identified the requirements to indicators of CPS information security. A system of specific assessment indicators based on the system stability criterion and homeostatic approach is proposed.

Embracing cyber-physical system as cross-platform to enhance fusion-application value of spatial information

The whole social paradigm is moving toward the cyber-physical systems society from information society. Cyber-physical systems (CPS) (e.g. self-driving car) are currently being emerged as one of important places that heavily depend on spatial data in order to facilitate intelligent control and improve real-time on-line performance. To expedite and accelerate the realization of cyber-physical systems (hereinafter CPS) in spatial information science, this paper suggests embracing CPS as cross-platform to strengthen fusion-application value of spatial information. This approach illustrates how fusion-added services by spatial information within the CPS framework are created, orchestrated, changed and managed from traditional approach in spatial information science. It offers a sound approach to overcome the uncertainties associated with emerging technology as well as to adequately accommodate real-time operating CPS system in spatial information science. Further, such paradigm of symbolic cross-platform offer new and exciting challenges for foundational research between CPS and spatial information and provide opportunities for maturation of spatial information science in the fourth industrial revolution era.

Extracting entity-based information in cyber-physical systems

This article proposes a framework [Formula: see text] for evaluating entity extraction problem over cyber-physical system data. As known by us, this article is the first work focusing on this problem, which is an important step for identifying entities in cyber-physical system data. Directed by the initial entities, utilizing the relaxation and verification techniques, [Formula: see text] provides a path expression–based solution for entity extraction problem, which has following characteristics. First, using path expressions, [Formula: see text] provides a condensed presentation for entity locations whose size may get very large when scaling up the data size. Second, requiring only one entity example to indicate the interests, using relaxation technique, [Formula: see text] can discover other similar entities automatically. Third, by adjusting the example given to [Formula: see text], users can specify their own interesting entities and control the entities discovered by [Formula: see text]. Besides, utilizing the idea of sharing computations, by extending previous automaton techniques, an efficient implementation of [Formula: see text] is provided. Experimental results are reported, which show that [Formula: see text] can provide an effective and efficient solution to the entity extraction problem.