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Евсютин Олег Олегович

Московский институт электроники и математики им. А.Н. Тихонова

Профиль на hse.ru ↗ тел.: +7 (495) 772-95-90 | 12675 | +7 (923) 403-09-21
Публикаций
63
Языков
2
Наград
15
Конференций
0
Профиль Публикации (63) Курсы (9)

Профессиональные интересы

цифровые водяные знакиинформационная безопасностьцифровая обработка изображенийцифровая стеганография

Должности

  • Руководитель департамента — Московский институт электроники и математики им. А.Н. Тихонова, Департамент кибербезопасности
  • Заведующий кафедрой — Московский институт электроники и математики им. А.Н. Тихонова, Кафедра информационной безопасности киберфизических систем
  • Доцент — Московский институт электроники и математики им. А.Н. Тихонова, Кафедра информационной безопасности киберфизических систем
  • Ведущий научный сотрудник — Московский институт электроники и математики им. А.Н. Тихонова, Кафедра информационной безопасности киберфизических систем
  • Академический руководитель образовательной программы — Информационная безопасность и технологии искусственного интеллекта, Кибербезопасность

Био

  • · Начал работать в НИУ ВШЭ в 2019 году.

Образование

  • 2018 · Ученое звание: Доцент
  • 2012 · Кандидат наук: Национальный исследовательский Томский государственный университет
  • 2009 · Специалист: Томский государственный университет систем управления и радиоэлектроники, специальность «Комплексное обеспечение информационной безопасности автоматизированных систем», квалификация «Специалист по защите информации»

Награды и поощрения

  • · Благодарность проректора НИУ ВШЭ (ноябрь 2025)
  • · Благодарность проректора НИУ ВШЭ (октябрь 2024)
  • · Благодарность первого проректора НИУ ВШЭ (декабрь 2023)
  • · Почетная грамота Московского института электроники и математики (февраль 2021)
  • · Премия Правительства Российской Федерации (декабрь 2018)
  • · Надбавка за публикацию в журнале из Списка А (и приравненном к нему научном издании) (2025–2026, 2023–2024)
  • · Надбавка за публикацию в международном рецензируемом научном издании (2022–2023, 2021–2022, 2020–2021)
  • · Надбавка за регулярные публикации в международных рецензируемых научных изданиях (2024–2029)
  • · Лучший преподаватель — 2020–2025
  • · Группа высокого профессионального потенциала (кадровый резерв НИУ ВШЭ)Категория "Будущие профессора" (2020–2021)
  • · Лучший академический руководитель в номинации «Удовлетворенность студентов качеством образовательной программы» — 2023–2025
  • · Лучший академический руководитель в номинации «Прием иностранных студентов» — 2025
  • · Лучший академический руководитель в номинации «Цифровые навыки студентов» — 2025
  • · Лучший академический руководитель в номинации «Привлечение студентов» — 2023–2025
  • · Лучший академический руководитель в номинации «Межфакультетское взаимодействие» — 2023

Гранты и проекты

  • 2027 · «Методы встраивания цифровых водяных знаков в мультимедиа-данные с использованием мягких вычислений и помехоустойчивого кодирования», 2025–2027, грант РНФ № 25-11-00215.
  • 2024 · «Методы встраивания дополнительной информации в цифровые объекты, устойчивые к цифро-аналоговым и аналого-цифровым преобразованиям», 2021–2024, грант РНФ № 21-71-10113.
  • 2021 · «Методы встраивания информации в данные беспроводных сенсорных сетей и цифровые изображения для обеспечения безопасности в «интернете вещей», 2019–2021, грант РНФ № 19-71-00106.

Идентификаторы исследователя

Публикации (63)

Overview of methods to improve execution time in image steganography and watermarking

2026 · ARTICLE · en

The cybersecurity problems remain extremely relevant in the modern world. Every year image steganography and watermarking schemes are proposed that solve the problems of hidden confidential data transfer and image authentication, respectively. The authors attempt to maximize the main embedding indicators, such as capacity, invisibility, and robustness. However, in practice, the time effectiveness of embedding schemes also becomes paramount. Some schemes can provide outstanding embedding quality according to the main embedding indicators but have unsuitable time complexity for real-world applications. Others, on the contrary, aim to satisfy the requirements of real applications, sacrificing the main indicators in the process. Some authors manage to achieve the trade-off between embedding efficiency and algorithm complexity using special measures. Yet, in many works, these solutions are not covered in detail. In this paper, an overview of relevant studies in image steganography and watermarking, the authors of which apply various techniques for speed improvement, is presented. Algorithmic, software, and hardware approaches to improving computation time are analyzed separately, and the most widespread solutions are highlighted. The overview ends with promising research directions for improving the performance of additional information embedding into digital images in the context of execution time.

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Robust image watermarking for diverse channels with template-forming neural network

2026 · ARTICLE · en

Watermarking is a key tool in combating unauthorized content distribution, but its effectiveness is often challenged by the wide range of communication channels that can degrade or remove the watermark. We propose a block neural network-based watermarking scheme for digital images that is robust against diverse transmission channels, including compression, pre-processing, and digital-to-analog conversions such as screen photographing and print-scan processes. Instead of using a more conventional encoder-decoder, a neural network with two inputs and inter-layer connectivity is used for forming block templates that are later superimposed into a cover image, while a classification neural network is used for extraction. The method achieves reliable extraction, with an average bit error rate below 20 % even in challenging conditions. It also preserves visual quality (PSNR > 30 dB) and supports a payload of 2 bits per 32 × 32 block, enabling watermark lengths sufficient for unique identification within a single image frame.

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Adaptation of Error Correction Procedures to the Time-Bin Quantum Key Distribution Protocol Implementation

2026 · ARTICLE · en

Error correction is a crucial stage in quantum key distribution (QKD) protocols — a promising field of modern cryptography where the secrecy of the shared key information is guaranteed by the laws of quantum mechanics. Currently, there are many effective approaches to error correction in QKD. However, most of them, due to their generic nature, fail to leverage the specific features of particular protocol implementations. This work demonstrates that accounting for the hardware specifics of a QKD system implementing the time-bin protocol enables a significant increase in error correction performance. For the considered QKD system, we have experimentally obtained estimates of the Quantum Bit Error Rate (QBER) observed for each combination of bit and detector. The differences in the obtained estimates reveal that the quantum channel can be modeled as a non-uniform binary channel. Furthermore, based on computational experiments with a model of the quantum channel, it was established that adapting the error correction procedure to its properties can achieve up to a 2.7-fold reduction in the LDPC code decoding failure rate at low error levels.

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Множественное встраивание водяных знаков в пространственно-частотную область изображений на основе генетического алгоритма

2025 · ARTICLE · ru

Повсеместное использование цифрового контента повышает актуальность защиты прав авторов и обладателей такого контента, в частности, цифровых изображений. Технология цифровых водяных знаков (ЦВЗ) позволяет эффективно решать многие задачи, связанные с доказательством авторства на изображения, подтверждением их подлинности и отслеживанием незаконного копирования. Эффективный алгоритм встраивания ЦВЗ требует достижения высоких показателей незаметности и робастности, что является сложной задачей, так как улучшение одного из этих показателей обычно приводит к ухудшению другого. В этом исследовании для решения данной задачи предложен новый алгоритм невидимого встраивания ЦВЗ в гибридную пространственно-частотную область изображений, основанный на множественном встраивании и метаэвристической оптимизации. Встраивание битов ЦВЗ выполняется путём изменения блока пикселей изображения в соответствии с некоторой матрицей изменений, которая выбирается адаптивно для каждого блока с помощью генетического алгоритма. На этапе извлечения значение каждого бита ЦВЗ определяется с помощью всех встроенных копий, причём ни оригинальное изображение, ни оригинальный ЦВЗ не требуются для извлечения данных. Результаты экспериментов показывают, что предложенный алгоритм отличается высокой незаметностью и устойчивостью к ряду атак обработки изображений.

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Study of a Quantum Key Distribution Protocol with Phase-Time Coding Using Simulation Modeling

2025 · ARTICLE · en

One of the main applications of quantum communication is quantum key distribution, which solves the problem of secure distribution of cryptographic keys between remote users. This paper investigates the performance of a phase-time coding quantum key distribution protocol belonging to the BB84 protocol family. We construct a simulation model that takes into account the peculiarities of hardware operation and physical properties of the transmission medium. Computational experiments with this model have shown that stable operation of the considered protocol is possible over communication lines up to 210 km long, but this parameter can be improved by constructing a more efficient error-correcting code.

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Hybrid domain based data embedding using quantization index modulation and metaheuristic optimization

2025 · ARTICLE · en

Embedding additional information into digital images is an effective method of data privacy protection. A data hiding scheme needs to have a high level of imperceptibility to provide a high level of security. At the same time, it is necessary to maintain good capacity and ability to extract information in its original form. In this study, we propose an adaptive scheme for embedding data into the hybrid spatial-frequency domain of images based on the quantization index modulation (QIM) method. Information embedding is performed by small changes in pixels in the spatial domain using a change matrix. A genetic algorithm finds the optimal change matrix for each image block. The objective function combines visual invisibility, statistical invisibility, and extraction stability metrics. Information extraction is performed in the Discrete Cosine Transform (DCT) domain. Using the hybrid spatial-frequency domain reduces the number of DCTs and inverse DCTs when calculating objective function values during optimization. Additionally, we adaptively select quantization step values. Experimental results show that the proposed scheme is efficient in terms of embedding quality indicators. Moreover, the influence of additional information embedding on image histogram in the frequency domain is minimized. In terms of imperceptibility, our scheme achieves an average PSNR of 44.0920 dB, SSIM of 0.9995, and NCC of 0.9998 with an average capacity of 0.4640 bpp. The embedded information is extracted without errors in all cases and no additional information or re-optimization is required during extraction.

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Hybrid metaheuristic algorithms for image watermarking: An experimental study

2025 · ARTICLE · en

Invisible image watermarking is a promising method for protecting the copyright of digital images such as photographs, illustrations, and scans. An effective watermarking algorithm embeds a special mark into an image that does not change the image content but can be extracted from it even after some common post-processing operations such as cropping or compression. Many authors use metaheuristic optimization algorithms to achieve a trade-off between imperceptibility and robustness of embedding. In recent years, researchers have been interested in hybrid metaheuristics, which combine operations of individual metaheuristics in some way. However, designs and compositions of hybrid metaheuristic optimization schemes for image watermarking have not been sufficiently studied to date. In this paper, we present an experimental study of various hybrid metaheuristics including sequential, interleaved, and parallel schemes for popular bioinspired optimization algorithms including genetic algorithm, differential evolution algorithm, particle swarm optimization algorithm, firefly algorithm, and artificial bee colony algorithm. We evaluate the effectiveness of hybrid metaheuristics for image watermarking using an algorithm based on changing the ratio between absolute values ​​of sums of discrete cosine transform coefficient groups as an example and perform an experimental comparison of different schemes. The results of the study show that a approach to metaheuristic hybridization and a composition of hybrid scheme significantly affect the imperceptibility and robustness of the image watermarking algorithm. In particular, the interleaved hybridization type provides the best results for the algorithm under consideration.

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Screen-Cam Imitation Module for Improving Data Hiding Robustness

2025 · ARTICLE · en

Using an attack-simulation module is a well-recognized approach to improving the robustness of end-to-end neural-network-based data-hiding schemes. However, most proposed attack simulators are limited in the types of attacks they cover, usually handling only a basic set of digital transformations. Real, in-demand use cases for data-hiding methods may involve modifications that cannot be modeled by basic digital transformations such as filtering, noise, or compression. In the screen-cam scenario, when an image containing hidden data is displayed on a screen and captured by a camera, the distortions are much more complex and typically require manual experiments that manipulate physical objects in order to replicate. This hinders both the process of creating applicable data-hiding schemes for this scenario and evaluating their effectiveness. In this work, we propose a generator neural network to simulate screen-cam distortions that can replace the manual, time-consuming operations of replicating this attack in the real world, and we show how it can be used to improve the robustness of an existing data-hiding scheme. In our example, we increased robustness by 15% in terms of bit error rate.

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Sampling Rate Optimization for LDPC-Based Information Reconciliation Protocol in QKD

2025 · CHAPTER · en

Quantum Key Distribution (QKD) is a promising field in modern cryptography where the security of key information is guaranteed by the laws of quantum mechanics. One of the key stages in QKD protocols is error estimation and reconciliation in the secret key. This procedure requires the transmission of a certain number of secret key bits over a public channel. Such transmission leads to disclosing these bits to a potential eavesdropper. The fraction of disclosed bits—the sampling rate-largely depends on the chosen approach for preliminary error estimation in the channel. This work is devoted to the optimization of the sampling rate for an LDPC code from the 5G standard. The results of our experiments show that for a QBER below 0.2 and key lengths of 264, 528, 792, and 1056 bits, it is necessary to disclose no more than 18%,11%,10%, and 7% of the key bits for error estimation, respectively. Furthermore, the proposed algorithm allows for similar optimization for any information reconciliation protocols and actual quantum bit error rates.

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On the Use of Metaheuristics of Different Classes and an Island Model for Image Steganography

2025 · CHAPTER · en

Digital steganography protects the privacy of data by hiding them in some digital containers, such as images. Protection of confidential messages by hiding them in digital images faces the problem of balancing the main performance indicators, i.e. embedding imperceptibility and capacity. Metaheuristic optimization can be used to flexibly customize embedding options, including parameters and locations of message bits within an image. Individual metaheuristics show promising results in terms of improving the performance of image steganography schemes, however they may suffer from slow convergence and local optima traps. An effective solution to this problem is the joint operation of several metaheuristics. In this study, we propose to use an island model to combine advantages of the state-of-the-art metaheuristics from different classes for information embedding in a spatial-frequency domain of images. The set of metaheuristics under study includes a whale optimization algorithm, a teaching-learning-based optimization algorithm, and a sine cosine algorithm. The experimental results show that information embedding using hybrid optimization schemes provides higher quality than using individual metaheuristics. The proposed algorithm for embedding information into images demonstrates not only the visual imperceptibility of embedding for a human eye, but also resistance to statistical steganalysis.

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Курсы (9)