勒索软件分析：高级网络威胁情报的知识提取和分类

English | 2024 | ISBN: 9781003528999 | 113 pages | True PDF,EPUB | 9.2 MB

This book presents the development of a classification scheme to organize and represent ransomware threat knowledge through the implementation of an innovative methodology centered around the semantic annotation of domain-specific source documentation. By combining principles from computer science, document management, and semantic data processing, the research establishes an innovative framework to organize ransomware data extracted from specialized source texts in a systematic classification system.

Through detailed chapters, the book explores the process of applying semantic annotation to a specialized corpus comprising CVE prose descriptions linked to known ransomware threats. This approach not only organizes but also deeply analyzes these descriptions, uncovering patterns and vulnerabilities within ransomware operations. The book presents a pioneering methodology that integrates CVE descriptions with ATT&CK frameworks, significantly refining the granularity of threat intelligence.

The insights gained from a pattern-based analysis of vulnerability-related documentation are structured into a hierarchical model within an ontology framework, enhancing the capability for predictive operations. This model prepares cybersecurity professionals to anticipate and mitigate risks associated with new vulnerabilities as they are cataloged in the CVE list, by identifying recurrent characteristics tied to specific ransomware and related vulnerabilities.

With real-world examples, this book empowers its readers to implement these methodologies in their environments, leading to improved prediction and prevention strategies in the face of growing ransomware challenges.

中文| 2024 | ISBN:9781003528999 | 113页| True PDF，EPUB | 9.2 MB本书介绍了一种分类方案的开发，该方案通过实施以特定领域源文档的语义注释为中心的创新方法来组织和表示勒索软件威胁知识。通过结合计算机科学、文档管理和语义数据处理的原理，该研究建立了一个创新的框架，将从专业源文本中提取的勒索软件数据组织在一个系统的分类系统中。 通过详细的章节，本书探讨了将语义注释应用于包含与已知勒索软件威胁相关的CVE散文描述的专业语料库的过程。这种方法不仅组织而且深入分析这些描述，揭示勒索软件操作中的模式和漏洞。该书提出了一种开创性的方法，将CVE描述与ATT&CK框架相结合，显著提高了威胁情报的粒度。 从基于模式的漏洞相关文档分析中获得的见解被结构化为本体框架内的分层模型，增强了预测操作的能力。该模型通过识别与特定勒索软件和相关漏洞相关的重复特征，使网络安全专业人员能够预测和减轻与CVE列表中新漏洞相关的风险。 通过现实世界的例子，本书使读者能够在他们的环境中实施这些方法，从而在面对日益增长的勒索软件挑战时改进预测和预防策略。

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