2025

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Перегляд 2025 за Дата публікації

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    Oblivious S-functions and Their Security against Rotational Cryptanalysis
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Yakovliev, Serhii; Voloshyn, Ihor
    This paper considers a specific class of ARX primitives: oblivious S-functions, which are distinguishedby their computational states being independent of each other. We present generic analytical expressionsfor the rotation probabilities of oblivious S-functions, which characterize security against rotationalcryptanalysis. We also examile particular classes of oblivious S-functions, including generalizedNORX-like mappings and LRX-analogues for multiplication by three. For these mappings, we providenumerical values of the rotation probabilities.
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    Intrusion detecting systems and blockchain technology
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Sikolenko, Eduard
    In this article, the information about intrusion detection systems and intrusion prevention systems was analyzed. General information, differences, main advantages and disadvantages of intrusion detection and prevention systems were described. The blockchain technology was analyzed as well. The main information on the blockchain technology was shown: the history of creation, sphere of application, working principle, potential threats and specifics of consensus mechanism. Based on the information given, it is planned to apply the blockchain technology in intrusion detection systems to increase the level of security
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    Modeling competing artificial intelligence systems for energy and users
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Lande, Dmitry V.; Danyk, Yuriy
    The article addresses the problem of modeling competition between two artificial intelligence systems (AI-1 and AI-2) that interact within a shared environment under limited resources such as users and energy. The study focuses on analyzing the strategic behavior and adaptability of these systems, as well as their impact on competitive outcomes through mathematical models and methods, including differential equations, the Lancaster model, and Boyd cycles (OODA-loop). Special attention is given to formalizing the interaction of systems using basic primitives ("Condition," "Loop," "Function") and their compositions, enabling the description of complex behavioral strategies of AI systems. The paper presents a detailed mathematical formalization of the dynamics of user and energy distribution between systems, taking into account factors such as user satisfaction, response accuracy, query processing speed, and energy efficiency. The research also includes numerical calculations and simulations demonstrating how initial conditions and system parameters influence competitiveness. The proposed models can be applied for predicting AI system behavior in real-world scenarios such as information campaigns, cyber conflicts, and resource optimization in digital environments.
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    Lightweight Cryptography in UAV systems
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Skorobahatko, Maksym; Voitsekhovkyi, Andrii
    The development and adoption of lightweight cryptographic algorithms have become increasingly important due to the growing volume of data transmitted by unmanned aerial vehicles (UAVs) and other unmanned systems. These systems demand security solutions that are both efficient and resource-conscious. Lightweight cryptography offers a promising balance of performance, low energy consumption, and implementation simplicity. In this paper, we present the first comparative analysis specifically focused on lightweight cryptographic algorithms for UAVs, assessing their suitability for real-time control and data protection in resource-constrained environments. A key contribution of our work is a practical experiment measuring processor load, memory usage, and energy consumption of selected algorithms on drone hardware. The results provide a clear evaluation of each algorithm’s effectiveness and efficiency under realistic operating conditions,
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    Stealthy cyberattacks on control systems using an adaptive soft-constrained optimization method
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Novikov, Oleksii; Ilin, Mykola; Stopochkina, Iryna; Duduladenko, Volodymyr
    This paper presents a novel approach for designing stealthy cyberattacks on automated control systems of critical infrastructure. The core idea lies in employing an adaptive soft-constrained optimization method, which simultaneously maximizes the impact functional of the attacker while keeping the attacked trajectory within the invisibility range of a standard fault detection mechanism. The proposed approach is based on a variational problem formulation, the construction of adjoint equations, and a gradient-based procedure with dynamic penalty parameter updates. Numerical simulation is conducted on a second-order test dynamic system. The results demonstrate the algorithm's effectiveness and convergence, as well as the feasibility of generating a controlled attack that successfully bypasses WLS-based detection methods. The method can be used to test the resilience of industrial systems to cyber threats through security scenario modeling
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    Influence of SRM filters preprocessing on stego data localization in digital images
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Yatsura, Pavlo; Progonov, Dmytro
    Early detection and counteraction to unauthorized transmission of sensitive information via publicly available networks are topical tasks today. Of special interest are steganalysis methods aimed for effective destruction of hidden messages embedded into innocuous media files, like digital images. However, practical usage of such methods introduces significant changes into statistical and spectralparameters of processed images, thus revealing the intrusion into stego channels. There are proposed novel methods for localization positions of embedded stego bits into cover images and pointwise processing only these positions. The article quantifies the impact of cover images preprocessing on accuracy of stego bits localization. The case of Spatial Rich Model (SRM) filters usage is considered, while stego bits position detection is performed using novel deep neural networks, such as Unet, LinkNet, PSPNet and FPN models. The results of comparative analysis of localization accuracy proved effectiveness of SRM filters usage, namely to increase of localization accuracy up to five times (from 2.01% to 10.9% of Intersection-over-Union metric values) even for modern adaptive embedding (like MG and MiPOD) and low cover image payload values (about of 3%-5%). Obtained results create preconditions for development of high-accuracy methods for localization positions of stego bits embedded into cover images according to novel embedding methods.
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    An Iterative Algorithm for Interdependent Estimation of Node and Link Weights in Corporate Networks for Cyber Risk Analysis
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Alekseichuk, Lesia; Lande, Dmytro
    The paper proposes a new iterative algorithm MRRW-PageRank (Mutually-Reinforced Risk-Weighted PageRank) for assessing cyber risks in corporate information systems based only on network topology. The algorithm solves the problem of determining link weights, which remains insufficiently solved in existing approaches to centrality analysis. Unlike traditional methods, where link weights are given or assumed to be the same, MRRW-PageRank establishes an interdependence between the importance of nodes and the probability of using paths to them, which models the nature of malicious paths. Node weights are updated according to the modified PageRank based on weighted links, and link weights are recalculated as a function of the importance of the target node and its input degree. The process is repeated iteratively until convergence. The algorithm is implemented as a codeless prompt based on a minimal logical framework, which provides the ability to execute in no-code environments and integrate with LLM agents. A simulation on a model network with 12 objects is presented, demonstrating the effectiveness of the method in prioritizing critical resources and identifying vulnerable penetration paths. The proposed approach is especially relevant at the stages of system design, topology audit, or initial security assessment, when there is no empirical data on vulnerabilities or behavior.
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    Quantum cryptanalysis of ciphers based on generalized Feistel and Lai-Massey schemes
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Fesenko, Andrii
    This paper investigates generalizations of the Lai-Massey scheme, including unified constructionscombining it with the Feistel scheme (MD GLM, UFLM, L-Feistel, and quasi-Feistel). New reductionsto the quasi-Feistel scheme are provided. Known efficient quantum attacks are analyzed, includingchosen-plaintext attacks on 3 rounds and chosen-ciphertext attacks on 4 rounds for a special case of thequasi-Feistel cipher using Simon’s algorithm. It is demonstrated that restrictions in that work led to thedegeneration of the quasi-Feistel scheme into the standard Feistel scheme, replicating known quantumattacks on the Feistel scheme. New two-round distinguishing attacks are presented for the L-Feistel andMD-1 GLM schemes, enabling round key recovery
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    Bit-sliced Algorithm for the 512-point Number Theoretic Transform
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Kripaka, Illia; Fesenko, Andrii
    A method for computing the 512-digit number theoretic transform used in the Vershyna digital signature scheme, employing bitwise digit operations, is proposed. The correctness of the developed algorithm and its efficient constant-time performance have been proven. The obtained results indicate that the proposed approach is adaptive and can be applied to computations with other polynomials. This enables its easy integration into various cryptosystems to ensure protection against side-channel attacks. The proposed method does not require changes to the digital signature scheme itself, introducing modifications only to the polynomial multiplication function.
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    Method of Security Evaluation of the LBlock-like Ciphers against Differential Cryptanalysis
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Yakymchuk, Oleksii; Lopatetskyi, Mykhailo
    This paper considers the problem of estimating the security of the lightweight block cipher LBlockagainst differential cryptanalysis. We formalize the process and present two algorithms of computingupper bounds for differential probabilities. The baseline algorithm provides approximate estimatesbased on the number of active𝑆-boxes, while the refined algorithm incorporates the full probabilitydistributions of𝑆-box differentials, yielding significantly better bounds.To illustrate the efficiency of the proposed methodology, we introduce a modified version of LBlockwith8×8𝑆-boxes, which has lower computational complexity and allows experimental evaluationon our resources. We consider different linear permutations of encryption round, analyzing affect theestimates produced by both algorithms. The results demonstrate that the refined algorithm achievesmuch smaller maximum bounds (below2−40in the best cases) compared to the baseline approach andprovides a more accurate characterization of security against differential cryptanalysis.Overall, the proposed algorithms make it possible to efficiently evaluate the provable security ofLBlock-like ciphers against differential cryptanalysis
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    Pseudorandomness Analysis of Ciphertexts in the AJPS-2 Cryptosystem
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Doroshenko, Yurii; Yadukha, Dariya
    This paper investigates the post-quantum cryptographic primitive AJPS-2 based on arithmetic moduloMersenne numbers. We describe modified versions of this cryptosystem that utilize generalizedMersenne numbers and Crandall numbers as moduli. We conduct a comparative analysis of ciphertextpseudorandomness for the original cryptosystem and its modifications using the NIST SP 800-22pseudorandomness test suite. The results show that the use of alternative moduli increases the overallstability and parameters variability of the AJPS-2 cryptosystem.
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    A method for assessing risk with accounting for the structure of threat and vulnerability relationships in a complex system
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Polutsyhanova, Viktoriia Igorivna; Smyrnov, Serhii
    The article presents a novel approach to risk assessment in complex information systems, which takes into account the structural relationships between threats, vulnerabilities, and system components. The primary focus is on developing a formalized model that enables the construction of a simplicial complex of dependencies among potential threats and vulnerabilities, as well as identifying their impact pathways on the integrity, availability, and confidentiality of the system. The use of a simplicial complex model is proposed to represent these interconnections and to determine critical nodes that are most vulnerable to compound attacks. The methodology allows for quantitative risk evaluation by calculating threat levels, the probabilities of vulnerability exploitation, and their impact on the system. A key feature of the approach is the consideration of not only individual vulnerabilities but also their interactions, which significantly enhances the accuracy of risk assessment. The results of modeling and applied analysis confirm the effectiveness of the proposed method in identifying the most critical security elements and in justifying protection priorities under limited resource conditions. The proposed method can be integrated into information security management systems to improve the protection level of complex technical infrastructures.
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    Petri Net–Based Analysis of UAV Networks Availability Issues in Conditions of Adversary Counteraction
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Novikov, Oleksii; Voitsekhovskyi, Andrii; Stopochkina, Iryna; Ilin, Mykola; Ovcharuk, Mykola
    The article proposes Petri net-based models that make it possible to simulate scenarios that reflect the real operating conditions of unmanned aerial vehicles (UAVs) in the presence of hostile factors. The modeling takes into account cyber-physical aspects of UAV availability and attacks aimed at disrupting this availability, including by means of enemy electronic warfare (EW) systems. The factor of natural obstacles is also considered, in particular terrain-induced obstacles that interfere with communication between operational UAVs and the relay node.A set of basic places and transitions is proposed and implemented as a software model. The study uses both ordinary and colored Petri nets. In the ordinary Petri net, the state corresponds to the signal level of the device, and the simulation is carried out to track precisely this characteristic for each UAV in the network. Interference leads to degradation of the state, which can be improved by introducing additional relay devices into the line of sight of the current UAV, reducing the distance between the current UAV and the relay, or deliberately searching for an exit from the EW coverage area.The colored Petri net is intended for more general tasks, which include counting the active devices in the network, assessing the impact of interference on changes in the network structure, and evaluating mission success. Simulation based on this model was implemented in a Python software application, with visualization performed using the graph-oriented library Graphviz. To account for specific conditions such as terrain and changes in device parameters, an additional module was developed that extracts data from open terrain map datasets
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    Proof Of Data Possession Protocol With Hash-based Deterministic Challenges And Privately Verifiable Payments
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Strielnikov, Maksym; Kovalchuk, Liudmyla
    The research presents a novel protocol for remote verification of data outsourced to third-party storage. The protocol aims to verify the possession of data in potentially untrusted storage without downloading. We identified challenges in existing proof-of-possession protocols (PDP) by conducting a comprehensive literature review. We stated the optimal threshold for the minimal communication cost needed in existing PDP protocols to ensure the validity of the target percentage of data blocks while maintaining high confidence. Building on these findings, we propose our own PDP requires a fixed amount of communication and offers practically deterministic validity guarantees based on the security of cryptographic hash functions. We show a scenario for monetization in both cloud-native and blockchain environments to incentivize storage providers. A rigorous security analysis demonstrates resilience against forgery attacks aimed to falsify integrity checks or compromise verifiability assumptions. Our protocol significantly reduces communication overhead compared to existing solutions while eliminating the cheating probability to negligible levels.
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    Determination of Cyberattack Parameters on the Measurements System of Critical Infrastructure Facility
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Novikov, Oleksii; Ilin, Mykola; Ovcharuk, Mykola; Stopochkina, Iryna; Voitsekhovskyi, Andrii
    The paper solves the problem of determination and researching the parameters of stealth attacks on the linear Kalman filter data measurement system that bypasses the standard fault diagnosis detector. The relevance of the research is determined not only by the importance of solving cyber security problems, but also by the active use of the Kalman filter in large industrial power supply networks to evaluate the indicators of system nodes, in industrial automation systems, and others. A cyber attack on the measuring system of the Kalman filter is under consideration, the purpose of which is to disrupt the normal functioning of the filter by distorting the measurement signal, which is a mandatory component of the filter. The filtering system is equipped with a fault detector, which detects the presence of an attack on the measurement signals. The condition of the attack is invisibility for the fault detector, that is, the attacker implements a class of stealth attacks on the integrity of the information that circulates and is processed in the system. The task of finding a distorted measurement signal was solved using the variational optimization method and the gradient method of the fastest descent. A computational experiment was conducted, the quantitative characteristics of the algorithm were obtained and analyzed. The proposed method and the corresponding algorithm for determining the parameters of stealth attacks on the measurement system of critical infrastructure objects can be used to solve the problems of testing cyber defense systems
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    Research on the Possibility of Applying Acoustic Metamaterials for the Protection of Speech Information
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Lytvynenko, Nazarii; Morshch, Yevhen
    The paper analyzes modern methods of technical protection of speech information and proposes a novel approach using acoustic metamaterials. The features of existing passive and active speech protection measures (soundproof constructions, sound-absorbing materials, noise jammers) are considered, as well as the characteristics of traditional sound absorbers and their limitations at low frequencies. The principles of constructing acoustic metamaterials, in particular resonance-based and periodic metastructures are presented, and the physical effects (Bragg band gaps, wave localization, negative effective mass density, etc.) that enable metamaterials to achieve extraordinarily high sound absorption in the speech frequency range are discussed. Recommendations are given for practical implementation of such panels in secure facilities and for evaluating their effectiveness using speech intelligibility criteria. It is concluded that acoustic metamaterials are a promising new means of technical protection of speech information, not yet covered by current standards.
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    A Review of modern methods for steganalysis and localization of embedded data in digital images
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Yatsura, Pavlo; Progonov, Dmytro
    The article provides a systematic review of modern steganalysis methods for digital images based on artificial neural networks. The primary stages of development of advanced cover-image models, from widely used artificial neural networks to contemporary hybrid models, are considered. Advantages and limitations of various types of neural networks for constructing stegodetectors for digital images are investigated. Based on comparative analysis of steganalysis accuracy, it is established that the use of advanced artificial neural networks achieves a detection accuracy of steganograms exceeding 90%, even at low embedding rates (less than 20%). Additionally, applying complex methods of processing both examined images, and feature vectors in multidimensional spaces with studied neural networks allows reducing the computational complexity of configuring stegodetectors without significant losses in stego images detection accuracy.
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    Threat analysis metrics of cloud storage systems
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Polutsyhanova, Viktoriia Igorivna; Smyrnov, Serhii
    The security of cloud storage systems remains a critical challenge as the in-creasing interconnection of services exposes them to a wide range of cyber threats. This paper presents a methodology for analyzing the structural characteristics of vulnerabilities and threats in cloud environments using Q-analysis and associated metrics. By modeling the interdependencies between vulnerabilities and threats, the study provides a systematic framework to construct attack profiles and evaluate their likelihood of occurrence. The approach bypasses the direct construction of simplex complexes by employing incidence matrices to derive structural trees, local maps, and connectivity graphs, thereby simplifying the analysis process. Using real-world vulnerability statistics from the Edgescan report, we identify the most exploited weak-nesses, such as cross-site scripting and broken authentication, and link them to corresponding attack vectors. A statistical model of characteristic attack profiles is then developed by applying entropy-based optimization methods, particularly the Nelder-Mead algorithm, to estimate probabilities of threat realization under structural constraints. The findings demonstrate that this method enables more accurate classification and ranking of threats, offering a practical tool for risk assessment and decision-making in cybersecurity management. Ultimately, the proposed approach provides a foundation for improving resilience of cloud storage systems through informed protection strategies
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    Differential Attack on IDEA Block Cipher Based on Its Key-Adding Function
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Parshyn, Oleksandr; Khmelnytskyi, Mykola
    This paper examines a new theoretical differential attack on the IDEA block cipher and several relatedciphers from the same design family, such as PES and MESH. We present an analysis of the mostprobable differentials, which characterise the ciphers’ security against the proposed attack. We alsopropose a design modification targeting the cipher’s key-adding function to enhance its security againstthe attack
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    Automating Cybersecurity Decision‑Making with AI and the Analytic Hierarchy Process
    (Igor Sikorsky Kyiv Polytechnic Institute, 2025) Svoboda, Igor
    Cybersecurity decisions in large organizations routinely require the integration of heterogeneous qualitative and quantitative considerations. The Analytic Hierarchy Process (AHP) offers a principled framework for such multi-criteria settings, yet reliance on human expert panels constrains scalability and cadence. This study examines whether large language model (LLM) agents can substitute for human panels within AHP without compromising methodological discipline. Seven GPT-4 personas are instantiated as virtual experts and coordinated by an AHP guide to structure and evaluate defenses against social-engineering attacks on a corporate data center. The agents elicit criteria and sub-criteria, construct pairwise comparison matrices, and synthesize priorities under standard AHP procedures. Aggregated judgments exhibit strong internal coherence (top-level consistency ratio CR = 0.016; λ_max = 7.13), yielding a stable ranking of alternatives: comprehensive employee training (0.2774), advanced intrusion detection (0.2240), cloud-based data backup (0.1938), targeted refresher training for security staff (0.1795), and physical barrier enhancements (0.1254). The results indicate that GPT-4 agents can emulate expert judgment for multi-criteria cybersecurity decisions at materially lower cost than human panels, while preserving the methodological rigor of AHP.