Automatic security management of smart infrastructures using attack graph and risk analysis

Иванов, Д.; Kalinin, Maxim O.; Krundyshev, Vasiliy; Orel, Evgeniy

doi:10.1109/worlds450073.2020.9210410

Cited by 21 publications

(18 citation statements)

References 13 publications

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“…As can be seen from Table 2, the estimation is made according to four discount rates: 6%, 8%, 10%, 12%. [12] Further, one needs to evaluate the main indicators of the efficiency of the investment project (net present value, payback period, profitability index, and internal rate of return).…”

Section: Resultsmentioning

confidence: 99%

Assessment of development effectiveness of solar energy in Russia

et al. 2020

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Non-renewable fossils are the main source of energy in modern conditions. This method of production and consumption of energy acts as one of the main anthropogenic factors that negatively impact the environment. Besides, limited energy reserves do not guarantee the sustainable development of world energy in the long term. The way out of this situation is using renewable energy sources (RES). Renewable energy sources are one of the promising and innovative areas of energy development. These energy sources allow moving to a new high-quality level of power supply and heat supply of the country and significantly improving the ecological state of settlements. The Russian Federation has all conditions for the implementation of such innovative projects aimed at using renewable energy sources. One of such promising projects is solar energy. The perspective of using solar energy is an almost inexhaustible resource, available everywhere, and also has another advantage high environmental safety. Besides, solar energy is characterized by low indicators in terms of capital and operating costs, a lower cost of electricity compared to traditional energy as well. In this study, the perspectives for the development of solar energy in the Russian Federation are identified. The existing solar capacities in Russia are analyzed, the main developments of solar energy in the country are determined. A model for assessing the economic efficiency of floating power plants is proposed in this paper. These plants make it possible to provide electricity to entire settlements. Having been the study, conclusions are drawn about the prospects of using such power plants as sources of cheap energy and environmental compatibility.

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Section: Resultsmentioning

confidence: 99%

Assessment of development effectiveness of solar energy in Russia

et al. 2020

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“…Approaches based on graphs represent a common solution in security assessment research (see, e.g., [6], [12], [23]- [40]). Many papers customize these approaches to the specific technologies, such as smart grids [6], medical devices [29], smart infrastructures [30], web technologies [31], cloud environments [40].…”

Section: B Graph-based Approachesmentioning

confidence: 99%

A Methodological Framework for AI-Assisted Security Assessments of Active Directory Environments

Nebbione

Calzarossa

2023

IEEE Access

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The pervasiveness of complex technological infrastructures and services coupled with the continuously evolving threat landscape poses new sophisticated security risks. These risks are mostly associated with many diverse vulnerabilities related to software or hardware security flaws, misconfigurations and operational weaknesses. In this scenario, a timely assessment and mitigation of the security risks affecting technological environments are of paramount importance. To cope with these compelling issues, we propose an AI-assisted methodological framework aimed at evaluating whether the target environment is vulnerable or safe. The framework is based on the combined application of graph-based and machine learning techniques. More precisely, the components of the target together with their vulnerabilities are represented by graphs whose analysis identifies the attack paths associated with potential security threats. Machine learning techniques classify these paths and provide the security assessment of the target. The experimental evaluation of the proposed framework was performed on 220 artificially generated Active Directory environments, half of which injected with vulnerabilities. The results of the classification process were generally good. For example, the F1-score obtained by the Random Forest classifier for the assessment of vulnerable networks was equal to 0.91. These results suggest that our approach could be applied for automating the security assessment procedures of complex networked environments.

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“…The work extends the attack graph generation techniques to represent humans, processes, and policies. Ivanov et al 47 presented automated security management of smart infrastructures (e.g., smart cities) with the aim to minimize risk by eliminating the most critical vulnerabilities. Doynikova et al 48 proposed a variation of the attack graph to provide security decision support in control systems.…”

Section: Attack Graphs and Bayesian Network In Cybersecuritymentioning

confidence: 99%

Mission‐centric decision support in cybersecurity via Bayesian Privilege Attack Graph

Javorník

Husák

2022

Engineering Reports

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We present an approach to decision support in cybersecurity with respect to cyber threats and stakeholders' requirements. We approach situations in which cybersecurity experts need to take actions to mitigate the risks, such as temporarily putting an IT system out of operation, but need to consult them with other stakeholders. We propose a decision support system that uses a mission decomposition model representing the organization's functional and security requirements on its IT infrastructure. Based on the cybersecurity state assessment, that is, discovery of vulnerabilities and attacker's position, the decision support system calculates the resilience metrics for each IT infrastructure's configuration, that is, how likely are they to not be disrupted. The calculation is enabled by two novel formal models, Privilege-Exploit Attack Graph and Bayesian Privilege Attack Graph, which reduce complex attack graphs into a comprehensible bipartite graph. Moreover, they illustrate the impact of exploiting the vulnerabilities and attackers gaining the privileges. The system recommends the most resilient mission configurations that are comprehensible to both cybersecurity experts and non-technical stakeholders, who may then choose which configuration to apply. Our approach is illustrated in a case study of a real-world medical information system.

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Automatic security management of smart infrastructures using attack graph and risk analysis

Cited by 21 publications

References 13 publications

Assessment of development effectiveness of solar energy in Russia

Assessment of development effectiveness of solar energy in Russia

A Methodological Framework for AI-Assisted Security Assessments of Active Directory Environments

Mission‐centric decision support in cybersecurity via Bayesian Privilege Attack Graph

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