Computer Science and Cybersecurity

Summary of DNS traffic filtering trends as a component of modern information systems security

Danylo Chepel — 2024-09-09

The study analyzes sources related to methods and technologies for DNS (Domain Name System) traffic filtering. Five main directions are identified that are actively used to enhance security at the DNS level. All examined technologies offer improvements in the quality of DNS filtering. It is emphasized that combining different approaches simultaneously can enhance overall security. The summary of research results on DNS traffic security issues indicates certain problems in the quality of the threat intelligence channels used. Therefore, the implementation of AI and LM technologies should enhance the "depth" of extracting useful information about current threats. It is emphasized that the consideration of information security issues should be conducted exclusively in the context of preventing the disparity of artificial intelligence (AI) capabilities in favor of the adversary (i.e., cybercriminals). Practically, this means that future DNS filtering systems should widely implement the latest advancements in VR, AI, LM, and DL technologies. This is particularly important in countering Domain Generation Algorithm (DGA) mechanisms and the spread of botnets. The specific issues of ensuring a consensus on the security and performance of current information and communication systems when implementing DNS encryption tools are highlighted. The primary problem associated with DNS traffic encryption is the potential for its misuse by attackers to conceal their destructive activities (phishing, spam, etc.).

The analysis of Hermite factor of BKZ algorithm on small lattices

Ivan Gorbenko — 2024-09-12

Lattice cryptography is one of the promising directions in modern cryptography research. Digital signatures and key encapsulation mechanisms on lattices have already been used in practice. In the future, such quantum-resistant transformations on lattices replace all standards that are not resistant to attacks on quantum computers. This makes the analysis of their security extremely relevant. Analysis of the security of cryptographic transformations on lattices is often reduced to the estimation of the minimum block size in the lattice reduction algorithm. For the expansion of small vectors, a reduction algorithm can be obtained for a given block size, the GSA model is often used, which uses the so-called Hermitian factor to predict the size of the vectors that the lattice reduction algorithm can obtain given the parameters. Asymptotic formulas have been developed to evaluate it in practice, but the question of their accuracy on cryptographic lattices has not been fully investigated. The work obtained estimates of the accuracy of the existing asymptotic estimates of the Hermite factor for lattices of sizes 120, 145, 170 for the classical BKZ algorithm. Research was conducted using the fpylll library. It was shown that the existing estimators are equivalent from a practical point of view and have a sufficiently small root mean square deviation from the true values. A formula was obtained that binds the root-mean-square error of approximation of the Hermit factor to the cryptographic parameters of lattices. The obtained results are useful for refining the security assessments of existing cryptographic transformations.

Security in the era of wireless innovations: analysis of potential threats and protective measures

Yevheniia Matvieieva — 2024-09-10

In today's interconnected world, wireless data transmission technologies have seamlessly integrated into the fabric of modern business operations. As reliance on these technologies grows, so does the imperative to ensure robust cyber security measures. Particularly in the age of wireless innovations, exemplified by the proliferation of the Internet of Things (IoT), the discourse surrounding the security of wireless technologies underscores the necessity of comprehending both established threats and the continuous emergence of new vulnerabilities. This underscores the urgent need for timely detection and mitigation strategies. While the convenience afforded by wireless data transmission technologies grants society unprecedented access to information and facilitates the management of diverse devices, processes, and systems, it also exposes users and modern information and communication systems (ICS) to significant cyber threats and vulnerabilities. Consequently, there arises a pressing need to address these challenges comprehensively. This research dissects contemporary methodologies aimed at restricting access to wireless networks, identifying potential vulnerabilities, and crafting effective responses to cyberattacks. It delves into various facets of cyber security, including data encryption, user authentication mechanisms, traffic monitoring protocols, and anomaly detection algorithms. Furthermore, it delves into the crucial aspect of educating personnel on wireless security practices, equipping them with threat awareness and incident response capabilities. Given the dynamic landscape of cybersecurity technologies and threats, this work seeks to establish a foundational understanding of the security landscape within wireless networks. By doing so, it aims to outline pragmatic strategies for effectively managing security risks, thereby fortifying the resilience of modern organizations and safeguarding critical information assets.

Clustering and Classification of Time Series Sound Data

Stanislav Kachanov — 2024-09-11

This scientific article addresses two critical tasks in data analysis—time series classification and clustering, particularly focusing on heart sound recordings. One of the main challenges in analyzing time series lies in the difficulty of comparing different series due to their variability in length, shape, and amplitude. Various algorithms were employed to tackle these tasks, including the Long Short-Term Memory (LSTM), KNN, recurrent neural network for classification and the K-means and DBSCAN methods for clustering. The study emphasizes the effectiveness of these methods in solving classification and clustering problems involving time series data containing heart sound recordings. The results indicate that LSTM is a powerful tool for time series classification due to its ability to retain contextual information over time. In contrast, KNN demonstrated high accuracy and speed in classification, though its limitations became apparent with larger datasets. For clustering tasks, the K-means method proved to be more effective than DBSCAN, showing higher clustering quality based on metrics such as silhouette score, Rand score, and others. The data used in this research were obtained from the UCR Time Series Archive, which includes heart sound recordings from various categories: normal sounds, murmurs, additional heart sounds, artifacts, and extra systolic rhythms. The analysis of results demonstrated that the chosen classification and clustering methods could be effectively used for diagnosing heart diseases. Furthermore, this research opens up new opportunities for further improvement in data processing and analysis methods, particularly in developing new medical diagnostic tools. Thus, this work illustrates the effectiveness of machine learning algorithms for time series analysis and their significance in improving cardiovascular disease diagnosis.

Functional features of well-known means of network shielding

Mykhailo Sichkar — 2024-09-12

The work briefly reviews the history, types, and capabilities of the main types of firewalls (FW). Firewalls are an important tool for protecting network resources from various information security threats. With the development of technology and the changing nature of attacks, especially those involving artificial intelligence (IoT), firewalls have also evolved, acquiring new functions and capabilities. This work provides a short survey of the main types, and capabilities of firewall technology, providing solutions to issues of comprehensive protection of network equipment and information resources from modern security threats. Different types of firewalls are used depending on the conditions of operation and purpose of the basic information and communication system (ICS), as well as on the place of their (FW) integration into the network or virtual infrastructure of modern information systems. For integrated networks that require a high level of their security, productivity and flexibility, firewalls of the business segment of generation «Next-generation» and «Threat-focused NGFW» are definitely the best choice. Attention was drawn to the fact that mobile firewalls should in every way contribute to the maintenance of resource consensus and eliminate a possible disparity in the performance of networked mobile applications. Adaptability to mobility of current communication systems (Wi-Fi, GSM and others) determines the specificity of security threats for mobile devices and It defines their key feature. This feature is based on permanent readiness for seamless transitions (reconnections) between different networks in conditions of constant energy shortage and limited available computing resources (meaning gadgets). Highlights the main trends, prospects for the development and implementation of different types of firewalls, including the impact of artificial intelligence, machine learning, cloud technologies and the Internet of Things as well as important aspects of their (FW) scope. It is emphasized that the introduction of FW does not replace other security technologies and tools, but effectively expands the existing arsenal of countering new security threats (primarily as an instrument of proactive countermeasures and rapid response to complex network incidents). The article may be useful for students, researchers, and information security professionals who seek to expand their competencies related to the development and operation of modern means of network protection.

Reconstruction of three-dimensional scenes based on video flow data

Denys Hrulov — 2024-09-11

This work is dedicated to the application of modern algorithms for reconstructing spatial scenes from images to restore spatial information from video. The work is looking at a variety of modern methods, approaches, algorithms and trends in the field. The attention was paid to the sequence of development of approaches to the completion of the task. While researching the field and results related to three-dimensional reconstruction based on images and video streams, an algorithm was invented that allows constructing dense depth maps using information from all video frames. The idea is to use ready-made, commonly accepted, and tested solutions to solve two problems: COLMAP for visual odometry, and RAFT for computing optical flow. The algorithm shows quite accurate results and reconstructs the depth map in detail on arbitrary static scenes.

Development and implementation of a method for checking the integrity of the design of an object-oriented system

Mykyta Pugach — 2024-09-12

Creating modern software products is a complex and long process consisting of many parts. To achieve quality, it is necessary to carry out various measures for testing and verifying software at all stages of development. This article discusses the software design stage, which is integral and one of the most important. In most software development life cycle (SDLC) models, this stage is one of the first, so design mistakes will lead to problems in all subsequent stages. Thus, due to the high cost of error, it is very important to check the integrity of the developed design at the design stage. The article examines the problem of finding contradictions in object-oriented design. The authors present a set of contradictions that can arise in such a design and aim to develop methods and algorithms for detecting and searching for these contradictions in order to improve the quality of the design, as well as writing software that will implement these algorithms and methods. The program "diagrams.net" was chosen as a tool for creating object-oriented design, the main useful feature of which is the ability to present the created diagrams in the form of an XML file in the popular drawio format. The authors of the study propose a method for parsing the XML file of the diagram and presenting it as a set of objects, such as dependency arrows, classes, methods, etc. These objects must interact according to the established rules.The violation of these rules is a contradiction of the object-oriented design. As a result of the study, a method of finding contradictions was presented and implemented in the Java programming language.