CSR: SGER: Dynamic Data Driven Defense Mechanisms for Cybersecurity

该SGER项目的目标是采用新颖而激进的方法来调查与关键基础设施保护相关的基本问题，并确保即使在系统受到攻击时也能向最终用户可靠地提供合法流量。本研究项目的宗旨是使用动态数据驱动应用系统（DDDAS）的概念来最好地满足这些目标，因为它为开发高性能协作环境的动态数据驱动入侵检测系统提供了基础。拟议的探索性研究集中在四个基本研究方向：用于入侵检测和响应的动态协作防御基础设施，包括对等网络，基于资源高效算法，动态协作地防御入侵和拒绝服务攻击，数据驱动的IDS -入侵评估信息库（IAIB）：我们建议开发一个信息库（评估树库），将用于协助检测和防御过程。在DDDAS的框架下，探讨了分布式入侵检测系统中入侵隔离、破坏遏制和自适应恢复机制的可行性和设计要求。网络安全日益受到人们的关注，而静态的安全解决方法受到限制。该项目带来了传统上不相交的技术方面，并整合了来自各个学科的跨学科工作，包括概率算法，人工智能技术，数据库，网络和协作系统，并推动了DDDAS概念。所提出的方法和系统软件功能可以对如何以自适应方式构建系统中的安全性的基本问题产生影响。 该项目包括教育和外联计划。其他更广泛的影响包括在项目的规定范围内推进最先进的技术是重要的，该项目有可能为未来和新的方法设定方向。

The objective of this SGER project is to pursue novel and radical approaches to investigate fundamental issues related to critical infrastructure protection and enable reliable delivery of legitimate traffic to end-users, even when the system is under attack. It is the tenet of this research project that these goals are best met using the concept of Dynamic Data-Driven Application Systems (DDDAS), as it provides the foundation for the development of a dynamic, data-driven intrusion detection systems for high-performance collaborative environments.The proposed exploratory research focuses on four fundamental research thrusts: Dynamic, collaborative defense infrastructure for intrusion detection and response, comprising of a network of peers, dynamically and collaboratively defend against intrusions and denial of service attacks based on resource efficient algorithms for probabilistic inspection of packets for detection and algorithms for collaborative sentinel deployment to guarantees optimal network coverage for scalable response to attacks.Data Driving the IDS -Intrusion Assessment Information Base (IAIB): We propose development of an information base (repository of assessment trees) that will be used to assist the detection and defense process. And Algorithms and Framework for Collaborative IDS for Disruption Detection, Containment & Recovery, explored within the paradigm of DDDAS, allowing exploration of the feasibility and design requirements of distributed mechanisms for intrusion isolation, damage containment and adaptive recovery.Network security is of increasing concern, and static methods to address security are limiting. The project brings technical aspects traditionally disjoint, and integrates interdisciplinary work from various disciplines including probabilistic algorithms, AI techniques, data bases, networks and collaborative systems, and driven the DDDAS concept. The proposed methods and systems software capabilities can have impact on fundamental issues how to architect security in systems in an adaptive way. The project includes education and outreach plans. Additional broader impacts include advancing the state of the art in the stated scope of the project is important, and the project has the potential to set directions for future and novel methods.