Ontology-based Approach to Enhance Security in Network Architecture and in System Design

我们每天收集的数据的大小和我们构建的软件系统的范围是许多数字转型背后的驱动力。发现强大的区别特征，无论是在数据集内还是在系统家族中，都是非常有用的。它使我们能够更好地设计可靠和安全的系统。目前，我们在分析数据方面的能力相当有限，目的是保护日益复杂的系统，并更好地塑造已开发的系统，以满足安全和隐私需求。我们需要更好的技术来从流经我们不同系统的海量数据中获得新的知识，并利用这些知识更好地保护它们免受安全威胁。这一研究计划的长期目标是进一步探索在资源网络中管理知识生成的基本原理。我们的工作范围是在灵活和自主的安全系统领域。作为基础工作的应用，我们打算探索更好的防御机制，构思安全网络系统的设计和体系结构，并建立设计安全的软件系统。 我们的研究项目探索了发现领域内解释的数据集中包含的特征的新方法。我们将探索一种适用于有组织的数据集的新型本体框架。我们将构建与安全相关的本体。我们的目标是使用我们的本体框架和开发的安全相关本体来提取安全相关知识。在安全环境中，通过解释流经网络的数据或有关安全情况的数据，我们生成可概括为基于数据的知识的信息。从分析数据中获得的知识将被用于即时修改网络体系结构或加强安全机制。为了提高部署在软件系统和网络上的防御机制的性能和可用性，我们将探索本体模块化技术，使多个代理能够在一个安全任务上进行协作。我们将阐明一种用于指定本体论的高级语言。我们还将提出推理机制和工具，以支持我们的网络系统解决方案的可扩展性。

The size of the data that we collect daily and the scope of the software systems that we build are the driving forces behind many digital transformations. The discovery of powerful distinguishing features, whether within data sets or within families of systems, is extremely useful. It allows us to better design dependable and secure systems. Currently, our capacity is quite limited in analyzing data for the purpose of securing increasingly complex systems and better molding the developed systems to meet security and privacy needs. We need better techniques for gaining new knowledge from the huge volume of data flowing through our diverse systems and to use this knowledge to better shield them from security threats. The long-term goal of this research program falls under further exploring the fundamentals governing knowledge generation within networks of resources. The scope of our work is within the area of agile and autonomous security systems. As application of our foundational work, we intend to explore better defense mechanisms, conceive designs and architectures for secure networked systems, and build software systems that are secure by design. Our research program explores novel ways to discover characteristics contained in data sets interpreted within a domain. We will be exploring a novel ontology framework that is suitable for organized data-sets. We will build security-related ontologies. We aim at using our ontology framework and the developed security related ontologies to extract security-related knowledge. Within a security context, by interpreting the data flowing through the network or the data about the security situation, we generate information that can be generalized into data-grounded knowledge. The gained knowledge from the analyzed data will be used to on-the-fly amend the architecture of the network or strengthen the security mechanisms. To increase the performance and the usability of the defense-mechanisms deployed on software systems and networks, we will explore ontology modularisation techniques to enable several agents to cooperate on a security task. We will articulate a high level language for specifying ontologies. We will also propose reasoning mechanisms and tools that support the scalability of our solutions for networked systems.