Scalable Programmable Appliance-based Network Intrusion Detection Architecture

网络入侵检测系统(IDS)是安全专业人员用来检测和响应安全漏洞的几种工具之一。通常，通过窃听网络并将每个网络消息的副本转移到传感器来实现入侵检测。通常，传感器是一台运行软件的通用计算机，可以检查它收到的每个数据包。这种入侵检测方法很容易实现，因为它依赖于现成的硬件和软件。然而，通用操作系统带来的开销以及大多数PC和工作站体系结构有限的I/O吞吐量将这种入侵检测系统限制在低带宽和中带宽网络。另一方面，专用入侵检测系统平台可以优化为处理高带宽流量，但缺乏灵活性和定制硬件和软件的高昂成本使这种方法在实践中不可行。最近，存在并行和分布式入侵检测体系结构，通过在多台通用机器上分发网络数据包来操作高带宽流量。这种方法结合了现成硬件和软件的灵活性以及并行处理的高性能。目前还没有对这种方法的可扩展性进行系统的研究，也没有对合适的分组分发策略进行分析。由于这种集群体系结构本质上是一套完整的计算机系统，占用机架或机架空间，消耗电力，需要耗时的管理和配置，因此在空间和电力成本方面可能会付出潜在的代价。本项目的目标是开发一种可扩展的基于并行设备的网络入侵检测系统体系结构，能够可靠地监控高带宽网段，同时具有基于通用入侵检测系统的成本效益和灵活性。通过在一系列低成本传感器之间以不影响入侵检测质量的方式分配网络流量，同时最大化可用并发性并最大限度地减少传感器之间所需的通信，可以实现高性能。利用现成的单板计算机实现了一种廉价而紧凑的设计，与同等数量的完整工作站或PC相比，它需要更少的电力。并行入侵检测平台体系结构的关键组件是在传感器之间分发网络数据包的方法。因此，系统设计将以对网络流量特性的系统分析为指导，这将为高级模型和模拟提供输入。为了验证和评估由此产生的体系结构的性能和可伸缩性，将主要基于低成本的现成硬件和软件实施一个原型系统。通过使用现成的组件解决入侵检测系统的问题，可以快速开发出协助安全漏洞的产品。这可能会对一个重要的网络话题产生巨大的直接影响。

Network Intrusion Detection Systems (IDS) are one of several tools used by security professionals to detect and respond to security breaches. Typically an IDS is implemented by tapping a network and diverting a copy of every network message to a sensor. Usually, the sensor is a general-purpose computer running software that examines every packet that it receives. This approach to IDS is easy to implement as it relies on off-the-shelf hardware and software. However, the overhead incurred by the general-purpose operating system and the limited I/O throughput of most PC and workstation architectures restrict such IDS to low and medium bandwidth networks. Special-purpose IDS platforms, on the other hand, can be optimized to handle high-bandwidth traffic, but the lack of flexibility and the high cost of custom hardware and software make this approach not viable in practice.Recently, parallel and distributed IDS architectures exist that operate on high bandwidth traffic by distributing network packets over a number of general-purpose machines. This approach combines the flexibility of off-the-shelf hardware and software with the high performance of parallel processing. A systematic study of the scalability of this approach as well as an analysis of suitable packet distribution strategies has not been done. Because such clustered architectures pay a potential penalty in terms of space and power required as they are essentially a set of complete computer systems that occupy shelf or rack space, consume power, and require time consuming management and configuration they have space and power costs that are high.The goal of this project is to develop a scalable parallel appliance-based architecture for network intrusion detection systems that is able to reliably monitor high-bandwidth network segments, yet is cost-efficient and retains the flexibility of general-purpose based IDS. High performance is achieved by distributing network traffic among an array of low-cost sensors in a way that does not impact the quality of intrusion detection, while maximizing the available concurrency and minimizing required communication among sensors. Utilizing off-the-shelf single-board computers leads to an inexpensive and compact design that requires less power than a comparable number of complete workstations or PCs.The key component of a parallel intrusion detection platform architecture is the approach by which network packets are distributed across the sensors. As a result, the system design will by guided by a systematic analysis of network traffic characteristics which will provide input into high-level models and simulations. To verify and evaluate the performance and scalability of the resulting architecture, a prototype system will be implemented based primarily on low-cost off-the-shelf hardware and software. By addressing IDS issues using off the shelf components, a product to assist in security breaches may be quickly developed. This could have large, immediate impact on an important network topic.