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News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Оценка киберрисков в проектах интернета вещей

Научно-технические ведомости Санкт-Петербургского государственного политехнического университета. Экономические науки. 2021. Т. 14. № 6. С. 102–116.
Grishunin Sergei V., Пищалкина И. И., Сулоева С. Б.

The Internet of Things (IoT) opens up vast opportunities for innovation, ranging from industrial enterprises to healthcare and consumers. However, the development of Internet of Things projects creates significant risks for developers and users. The number and frequency of IoT attacks is increasing, while the direct and indirect damage are on the rise. Thus, one infected device can make the entire ecosystem of a company vulnerable to attacks with potential failures: from violating the privacy of individual users to a massive failure of public systems and a threat to people’s lives. The relevance of the article is explained by the increase in the number of cyber attacks, the speed of the emergence of new threats and the increase in damage from attacks. Therefore, the article examines the decrease in the effectiveness of the existing mechanisms for assessing cyber risks and fills the gaps in research in this area. The authors developed Cyber ROI indicator (CyROI), which allows reflecting cyber risks and measuring the effectiveness of investments in the development of the Internet of Things, taking into account cybercrime and related control measures. Next, an approach to cyber risk assessment for Internet of Things (IoT) projects was formed, based on the principles of risk controlling and including the stages of risk identification, risk tree modeling, risk assessment and analysis of results. In addition to the formation of the approach itself, a structural and logical scheme for assessing cyber risks was presented with its tools described. Unlike analogues, the developed approach provides a holistic approach to the assessment of cyber risks; it allows integrating and coordinating all related actions and tools, simulating the confidence interval of possible return on investment, and shows the chances to go beyond risk appetite and risk tolerance. The proposed approach makes the assessment of cyber risks dynamic, iterative, responsive to changes in the cyber environment. Moreover, this approach has significant scientific and practical application. Compared to existing approaches, the author’s approach to cyber risk assessment has more flexibility, takes into account correlations between risks, allows you to assess the impact of each risk factor on CyROI and calculate a large number of scenarios.

Research target: Economics and Management Computer Science
Language: Russian
Full text
DOI
Text on another site
Keywords: cyber securityкибербезопасность Internet of ThingsИнтернет вещейrisk controllingcyber risksриск-контроллингкиберриски
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