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October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.

 

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KMHCR: A Key-Controlled Signal-Domain Transformation for 5G IoT Security

Journal of Signal Processing Systems. 2026. Vol. 98. Article 31.
Ronglin Z., Wei L., Jiahong C., Yuxiang C., Zulong D., Zhongming F., Jigang W., Naixue X., Xiaoyan C., Avdoshin S. M.

To address the need for lightweight and low-latency protection in massive resource-constrained 5G Internet of Things (IoT) systems, this paper proposes Key-Controlled Modulation Hopping and Constellation Rotation (KMHCR). KMHCR is designed as a physical-layer confidentiality-enhancement mechanism that avoids bit-wise full-payload encryption in the protection pipeline. It uses a shared key derived from channel-reciprocity secret key generation to drive a stateless, counter-based pseudo-random function, which determines a 5G-compliant modulation scheme and a quantized constellation rotation angle for each packet without requiring fragile per-packet state synchronization. For legitimate users, these operations introduce only lightweight signal-domain processing, whereas an unauthorized receiver must jointly infer the modulation type and the phase rotation from the observed signal. To evaluate the robustness of the proposed mechanism against intelligent attacks, we construct a 3GPP-compliant 5G adversarial dataset covering six modulation types, multiple signal-to-noise ratio regimes, and realistic channel impairments. Experimental results with multiple state-of-the-art deep learning-based AMC models show that KMHCR can substantially reduce the recoverable throughput of unauthorized receivers under the considered adversarial setting. These results support the use of KMHCR as a lightweight complementary protection mechanism for 5G IoT communications.

Research target: Computer Science
Language: English
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Keywords: Deep learningPhysical layer security5G IoTAutomatic modulation classificationConstellation rotation5G adversarial dataset
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