STUDY OF THE STRUCTURE OF THE SYSTEM FOR DETECTING AND PREVENTING RANSOMWARE ATTACKS BASED ON ENDPOINT DETECTION AND RESPONSE

Danyil Zhuravchak, V. Dudykevych, Anastasiia Tolkachova
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Abstract

The paper discusses the challenges and limitations of current ransomware detection and prevention systems, as well as potential future developments in the field. One key challenge is the constantly evolving nature of ransomware attacks, which requires systems to be regularly updated and adapted to stay effective. Another challenge is the need for systems to be able to distinguish between legitimate and malicious software, as well as different types of ransomware. To address these challenges, the paper proposes a number of functional and non-functional requirements for ransomware detection and counteraction systems. These include the ability to detect and respond to attacks in real time or close to it, the ability to analyze and classify different types of ransomware, and the ability to integrate with other security systems and tools. Additionally, non-functional requirements such as scalability, performance, and security should also be considered.The paper also presents a detailed analysis of the different types of ransomware detection and counteraction systems currently available, including intrusion detection systems (IDS), endpoint detection and response (EDR), and modern antiviruses. It also provides a comparison of their strengths and weaknesses, and a classification of existing solutions according to their similarity. Finally, the paper presents an evaluation algorithm for assessing the quality of products for detecting and countering ransomware. The algorithm is based on a set of functional and non-functional requirements and is designed to provide a comprehensive and objective assessment of the capabilities of different systems. The algorithm is validated through a series of tests and experiments, which demonstrate its effectiveness in identifying the best solutions for detecting and countering ransomware. Overall, this paper provides valuable insights and practical guidance for organizations looking to improve their defenses against ransomware attacks.
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研究了基于端点检测与响应的勒索软件攻击检测与防范系统的结构
本文讨论了当前勒索软件检测和预防系统的挑战和局限性,以及该领域未来的潜在发展。一个关键的挑战是勒索软件攻击的不断发展的性质,这需要系统定期更新和适应,以保持有效。另一个挑战是系统需要能够区分合法和恶意软件,以及不同类型的勒索软件。为了解决这些挑战,本文提出了勒索软件检测和对抗系统的一些功能和非功能需求。这些包括实时或接近实时的检测和响应攻击的能力,分析和分类不同类型勒索软件的能力,以及与其他安全系统和工具集成的能力。此外,还应该考虑可伸缩性、性能和安全性等非功能需求。本文还详细分析了目前可用的不同类型的勒索软件检测和对抗系统,包括入侵检测系统(IDS),端点检测和响应(EDR)以及现代反病毒软件。它还提供了它们的优点和缺点的比较,并根据它们的相似性对现有解决方案进行分类。最后,本文提出了一种用于检测和对抗勒索软件的产品质量评估算法。该算法基于一组功能性和非功能性需求,旨在对不同系统的能力提供全面和客观的评估。通过一系列的测试和实验,验证了该算法在识别检测和打击勒索软件的最佳解决方案方面的有效性。总的来说,这篇论文为希望提高对勒索软件攻击的防御能力的组织提供了有价值的见解和实践指导。
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