кібербезпека

Predicting cyberspace intrusions using machine learning algoritms

The article presents possible strategies and approaches to address the growing cybersecurity threat landscape, new trends and innovations, such as artificial intelligence and machine learning for cyber threat detection and automation. The paper presents well-known machine learning classifiers for data classification. The dataset has been taken from a report by the Center for Strategic and International Studies. The presented model accuracy assessment study has been significant variation among algorithms based on different network intrusion detection systems.

Adaptation of Information Security in the Agile World

The article investigates the integration of information security into Agile software development processes, focusing on the adaptation of DevSecOps methods. The goal was to enhance the implementation of security practices by reducing vulnerability detection time, simplifying the integration of security into the development cycle, and improving team collaboration. The analysis revealed that automation of security testing reduces vulnerability detection time by 40%, while cross-functional teams improve collaboration by 30%.

Review of Modern Automated Software Security Testing Tools

Nowadays, with the rapid development of modern technologies in software engineering, active digitalization, and the migration of many services online, ensuring the security of these services in terms of integrity, confidentiality, and availability of information has become more important than ever. The level of application security directly depends on investments made in security during software development.

Research of Compliance With Cyber Essentials Requirements for Company’s Certification

This paper examines the Cyber Essentials requirements for ensuring basic security controls, which need to be implemented to protect against the most common cyber threats. Cyber Essentials is a foundational cybersecurity certification scheme developed by the UK government, which has been in operation since 2014 and under which more than 100,000 organizations have been certified.

Overview of the Fundamental Model of Security Orchestration, Automation, and Response in the Context of Cybersecurity of Virtual Networks

The aim of this study is a comprehensive analysis of the fundamental SOAR (Security Orchestration, Automation, and Response) model in the context of cybersecurity for virtual networks. The paper presents a synthesis of the core concepts of orchestration, automation, and response, which are critical elements of modern approaches to risk management and information system protection.

HYBRID MODEL OF NETWORK ANOMALIES DETECTION USING MACHINE LEARNING

The increasing complexity of cyber threats requires the development of effective methods for detecting and classifying attacks in network traffic. This study analyzes the effectiveness of three popular machine learning algorithms: Random Forest, which is used for anomaly detection, Support Vector Machines (SVM), which performs cyber threat classification, and autoencoders, which are used for data preprocessing and deep traffic analysis.

Role, Problems, and Methods of Software Security Testing Automation

In the modern world, where information security becomes a key element of any organization's operations, software security testing automation is more important than ever. The success of an application directly depends on its stability, reliability, and security, which makes the proper implementation of control mechanisms critical. The increase in cyber threats and the growing complexity of software systems make this topic even more relevant.

Docker Container Image Scanning Methods

With the development of containerized environments, the issue of security is becoming critical for application deployments. This article provides a comparative analysis of static and dynamic methods for scanning Docker container images. Static analysis is used to identify potential vulnerabilities before container deployment, while dynamic analysis is performed in an isolated environment at runtime, ensuring product reliability.

Neuro-symbolic models for ensuring cybersecurity in critical cyber-physical systems

This paper presents the results of a comprehensive study on the application of the neuro-symbolic approach for detecting and preventing cyber threats in railway systems, a critical component of cyber-physical infrastructures. The increasing complexity and integration of physical systems with digital technologies have made such infrastructures vulnerable to cyberattacks, where breaches can result in severe consequences, including system failures, financial losses, and threats to public safety and the environment.

Encrypting the File System on a Single-Board Computers Platform and Using Linux Unified Key Setup With Physical Access Keys

The object of the research is the security of the file system of a single-board platform. As part of the research reported in this paper, a method has been proposed to protect the file system using encryption. Implementing a Linux Unified Key Setup paired with a password or Universal Serial Bus key has been demonstrated. The advantages of Linux Unified Key Setup for this task and the possibilities for system configuration and encryption method depending on the use case and hardware configuration has been outlined.