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О безопасности схемы биометрической аутентификации, основанной на нейронной сети
Математические вопросы криптографии. 2014. Vol. 5. No. 2. P. 87–98.
Маршалко Г. Б.
We show that neuron weights used in neural network-based biometric authentication scheme defined in GOST R 52633 standard series contain all the information on biometric data and secret key of the legitimate user. So, the complexity of evaluating (with known tables of neuron weights) the legitimate user's secret key is equivalent to the complexity of evaluating one solution of a corresponding system of linear inequalities. Thus, first, neuron weights should be considered as a part of a secret key of the authentication system, and, second, several methods for neural networks protection proposed in the standard are inefficient.
Portnoy S., Efremov A., Voloshin A., , in: 2026 Systems of Signal Synchronization, Generating and Processing in Telecommunications (SYNCHROINFO).: IEEE, 2026. P. 1–4.
This paper presents a deep learning-based optimization of a list-decoding algorithm for a concatenated Hamming-Reed-Solomon code transmitted over an AWGN channel with BPSK modulation. The proposed method reformulates early termination of the erasure-pattern list as a weighted regression problem, addressing class imbalance through an asymmetric Weighted Mean Squared Error (WMSE) loss function that penalizes index ...
Added: October 1, 2026
International Joint Conferences on Artificial Intelligence, 2026.
Added: October 1, 2026
Ryumina E., Aksenov A., Сысоев Д. С. et al., IEEE Computer Society, 2026.
Ambivalence/hesitancy recognition in unconstrained videos is a challenging problem due to the subtle, multimodal, and context-dependent nature of this behavioral state. In this paper, a multimodal approach for video-level ambivalence/hesitancy recognition is presented for the 10th ABAW Competition. The proposed approach integrates four complementary modalities: scene, face, audio, and text. Scene dynamics are captured with ...
Added: September 30, 2026
Ivanov F., Kotov F., IEEE Access 2026 Vol. 14 P. 104662–104679
U-UV codes, based on the Plotkin (U, U + V) construction, provide a unified framework that includes polar and Reed–Muller codes and enables flexible design through the choice of component codes. While modern capacity-approaching codes achieve excellent performance at large block lengths, their efficiency at short and moderate lengths remains limited, especially under low-latency constraints. ...
Added: September 30, 2026
Djambong Tenkeu H., Institute for System Programming of the RAS, 2026.
Added: September 29, 2026
Ivanashev Y., Доклады Российской академии наук. Математика, информатика, процессы управления (ранее - Доклады Академии Наук. Математика) 2026 Т. 529 С. 93–101
Язык L является нижним для релятивизируемого сложностного класса C, если CL=C. Для классов #P, GapP и SpanP известны точные нижние классы языков: Low(#P) = UP ∩ coUP, Low(GapP) = SPP и Low(SpanP) = NP ∩ coNP. В этой статье мы доказываем, что Low(TotP) = P, и приводим характеризации нижних классов функций для #P, GapP, TotP ...
Added: September 28, 2026
Piliugin L., Antropov A., Lobashev E. et al., Journal of Nuclear Materials 2026 Vol. 632 Article 156876
The effects of dislocations on the mobility of gas nanobubbles pinned to them are considered as novel unex- plored mechanisms of accelerated fission gas release and investigated using classical molecular dynamics of helium bubbles in FCC aluminum. Non-equilibrium methods are developed to calculate the mobility of a pinned bubble both along and across the dislocation ...
Added: September 28, 2026
Kashpurovich I., Oleynichenko A., Stegailov V., Supercomputing Frontiers and Innovations 2026 Vol. 13 No. 1 P. 52–73
We report a high-performance implementation of the resolution-of-the-identity Hartree–Fock method that fully exploits the permutational symmetry of three-center electron repulsion integrals (ERI). The present implementation adopts a hybrid MPI+OpenMP parallelization strategy. Two different algorithmic approaches (with and without the pre-transformation of ERIs) are compared. A custom data layout introduced previously is employed. Designed to efficiently ...
Added: September 28, 2026
Teregulov T., Loubenets E. R., / Series Quantum Physics "arXiv". 2026. No. 2609.31472.
We develop a new three-party quantum secret-sharing (QSS) protocol based on a three-qubit W state. This protocol encodes the secret-sequence bits using X gates and employs randomly selected Hadamard operations and measurement bases to generate information and security-test rounds. We evaluate the efficiency of the proposed protocol and analyze its security against an internal adversary ...
Added: September 28, 2026
Silakov D., Системный администратор 2026 С. 84–89
Social media users rarely think about what lies behind the beautiful facade of activity feeds, teeming with photos and video stories. However, the widespread popularity of such platforms generates a huge amount of all sorts of content that needs to be stored, processed quickly, and displayed, and in the era of AI, it also needs ...
Added: September 28, 2026
Prokhorov A., Wei Z., Sang H. et al., Journal of Productivity Analysis 2026 Vol. 65 P. 1–16
The stochastic frontier model (SFM) is widely employed in the analysis of productivity and efficiency, yet strict parametric forms, such as the Cobb-Douglas and Translog functions, are often assumed for modeling production, leading to potential misspecification issues. While semi- and nonparametric SFMs offer greater flexibility, they face challenges in imposing monotonicity and concavity to maintain ...
Added: September 28, 2026
Qian X., Guan X., Zhang B. et al., Journal of Global Optimization 2026
Inverse quickest path problem on networks ...
Added: September 27, 2026
Switzerland: Springer Cham, 2026.
This volume gathers selected, peer-reviewed contributions presented at the 19th Conference of the International Federation of Classification Societies (IFCS 2026), held on 14–16 July 2026 in Milan, Italy. Reflecting the volume’s motto, Navigating Complexity – Statistical Methods, Data Analysis, and Machine Learning for Actionable Insights, the papers showcase modern methodologies and real-world applications designed to extract ...
Added: September 25, 2026
Kraevskiy A., Sokolovskiy E., Prokhorov A., Emerging Markets Review 2026 No. 74 P. 1–19
Financial markets of emerging economies are vulnerable to extreme and cascading information spillovers, surges, sudden stops and reversals. With this in mind, we develop a new online early warning system (EWS) to detect what is referred to as ‘concept drift’ in machine learning, as a ‘regime shift’ in economics and as a ‘change-point’ in statistics. ...
Added: September 25, 2026
Дубич Е. В., Schagin D., Славянский форум 2026 № 2 (52) С. 560–565
The paper compares HTTP/2 and HTTP/3 for static resource transfer under software-simulated network degradation. The experiment shows that HTTP/3 is not universally faster, but it is more stable as latency and packet loss increase. ...
Added: September 25, 2026
Joulitov A.K., Lomazova I.A., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 4(2) P. 215–224
In process mining, DFG (Directly-Follows Graph) models are popular due to their simplicity and clarity. However, if a process is acyclic but contains concurrent events, standard algorithms for discovering DFG models can generate "fake" cycles that do not actually exist in the event log. These cycles hinder the analysis of information processes, significantly reducing the ...
Added: September 24, 2026
Добрина Д. Н., Nesterenko A., Прикладная дискретная математика. Приложение 2026 № 19 С. 151–159
Работа содержит результаты формального анализа криптографических механизмов, входящих в состав проекта методических рекомендаций «Защищенный универсальный протокол передачи данных и управления микросхемой интеллектуальной карты» (протокол SECUNDA). Получена формальная модель и перечень трудноразрешимых математических задач, трудоёмкостью решения которых можно оценить стойкость используемых криптографических механизмов. ...
Added: September 24, 2026
I.I. Sergeev, I.A. Lomazova, Modeling and Analysis of Information Systems 2026 Vol. 33 No. 3 P. 394–419
Object-centric process mining has emerged as a powerful paradigm for analyzing event data involving multiple interacting business objects. Existing discovery techniques often rely on object-centric Petri nets with fixed arc multiplicities, limiting their ability to represent parametric resource consumption and production patterns and to capture quantitative dependencies between interacting object types. In this paper, we ...
Added: September 24, 2026
Ivan Bulychev, Savchenko A., AI 2026 Vol. 7 No. 9 Article 380
Recent advances in large language model (LLM) agents have shown promise for autonomous decision-making in recommender systems. However, existing approaches suffer from two fundamental limitations: flat agent memories that conflate different information modalities and prohibitive computational costs that prevent scaling beyond a few hundred users. We propose Hybrid-GraphRAG, a recommender system that integrates hierarchical agent ...
Added: September 24, 2026
Snegirev A., Sychev S., Futures 2026 Vol. 183 P. 1–22
This study addresses the systemic identification and categorization of risks associated with AI development, arising from tensions between technological evolution and institutional, infrastructural, and economic contexts. Drawing on a constructionist methodology, we interpret technological risks as constitutive elements of expert communities' images of the future. Through in-depth interviews with 100 AI experts, proportionally representing corporate, ...
Added: September 23, 2026
Aleksei Samarin, Nazarenko A., Alexander Savelev et al., Pattern Recognition and Image Analysis 2024 Vol. 34 No. 3 P. 844–854
Improving image quality is becoming an increasingly popular task, especially when working with mobile devices. One common approach to image enhancement is the use of convolutional neural networks. However, to achieve good results, such networks must be large enough, otherwise there is a risk of unwanted artifacts. In addition, large convolutional neural networks require significant ...
Added: September 21, 2026
Aleksei Samarin, Aleksei Toropov, Alexander Savelev et al., , in: Pattern Recognition. ICPR 2024 International Workshops and Challenges.: Cham: Springer, 2025. P. 308–320.
This research explores an innovative approach to enhancing the accuracy of detecting small microorganisms in complex microscopic environments. Our study introduces a streamlined, hybrid image pre-processing model specifically designed to address the challenges of identifying diplococci in live microscopy of dynamic samples. By integrating pre-defined filtering techniques with predictive adjustments for optimal applicability, our method ...
Added: September 21, 2026
Lebedev O. B., Шмелева А. Г., Гежа Н. С., Информатика и автоматизация (Труды СПИИРАН) 2026 Т. 25 № 3 С. 720–750
This paper describes the development of a neural network model for automated analysis of medical data in electrophysiology based on deep learning methods. The relevance of this work stems from the growing need to improve the objectivity, speed, and accuracy of processing complex spatiotemporal signals, such as ECG or EEG. Convolutional neural networks (CNNs), which ...
Added: September 10, 2026
Неверов В. Д., Красавин А. В., Vagov A. et al., Physical Review B: Condensed Matter and Materials Physics 2026 Vol. 113 P. 1–6
We develop a neural network approach to solve the self-consistent Bogoliubov-de Gennes equations in strongly disordered s-wave superconductors. The method accurately reproduces inhomogeneous gap distributions and generalizes to system sizes far larger than those used in training. It reduces computational scaling from O(N6 ) to O(N2), enabling quantitative analysis of percolation phenomena and the superconductor-insulator ...
Added: September 5, 2026