[论文解读] IDPS: An Integrated Intrusion Handling Model for Cloud

Hassen Mohammed Alsafi, Wafaa Mustafa Abduallah+1 more|arXiv (Cornell University)|Mar 15, 2012

Network Security and Intrusion Detection参考文献 7被引用 6

一句话总结

本文提出了一种面向云环境的集成入侵检测与防护系统（IDPS），通过在统一框架内结合异常检测（AD）和签名检测（SD），以增强安全性。通过整合入侵检测系统（IDS）和入侵防护系统（IPS）功能，该模型能够实现对各类网络攻击的实时检测与自动阻断，提供一种针对云计算动态且可扩展架构量身定制的稳健、自适应防御机制。

ABSTRACT

Today, many organizations are moving their computing services towards the Cloud. This makes their computer processing available much more conveniently to users. However, it also brings new security threats and challenges about safety and reliability. In fact, Cloud Computing is an attractive and cost-saving service for buyers as it provides accessibility and reliability options for users and scalable sales for providers. In spite of being attractive, Cloud feature poses various new security threats and challenges when it comes to deploying Intrusion Detection System (IDS) in Cloud environments. Most Intrusion Detection Systems (IDSs) are designed to handle specific types of attacks. It is evident that no single technique can guarantee protection against future attacks. Hence, there is a need for an integrated scheme which can provide robust protection against a complete spectrum of threats. On the other hand, there is great need for technology that enables the network and its hosts to defend themselves with some level of intelligence in order to accurately identify and block malicious traffic and activities. In this case, it is called Intrusion prevention system (IPS). Therefore, in this paper, we emphasize on recent implementations of IDS on Cloud Computing environments in terms of security and privacy. We propose an effective and efficient model termed as the Integrated Intrusion Detection and Prevention System (IDPS) which combines both IDS and IPS in a single mechanism. Our mechanism also integrates two techniques namely, Anomaly Detection (AD) and Signature Detection (SD) that can work in cooperation to detect various numbers of attacks and stop them through the capability of IPS.

研究动机与目标

• 应对由于攻击面扩大和工作负载动态化而带来的云计算安全挑战日益加剧的问题。
• 克服传统IDS/IPS系统仅关注单一攻击类型或缺乏集成的局限性。
• 开发一种统一的智能系统，能够检测并防止云环境中广泛存在的网络威胁。
• 通过主动识别威胁和自动化响应机制，提升云基础设施的安全性和隐私保护。

提出的方法

• 设计一种混合检测机制，整合异常检测（AD）与签名检测（SD），实现全面的威胁覆盖。
• 实施一个集中式检测引擎，关联来自多个云节点的数据，以识别可疑行为模式。
• 利用基于签名的分析方法，以高准确率和低误报率检测已知攻击模式。
• 应用基于异常的检测方法，通过建立系统基线行为，识别零日攻击和未知威胁。
• 集成入侵防护功能，实现实时自动阻断或缓解检测到的威胁。
• 在可扩展的分布式云架构中部署系统，以确保低延迟和高可用性。

实验结果

研究问题

• RQ1 如何设计一种统一的入侵检测与防护系统，以应对云环境中多样化且不断演变的威胁？
• RQ2 在云原生架构中，结合异常检测与签名检测时，性能与准确率之间的权衡如何？
• RQ3 与独立的IDS或IPS解决方案相比，集成的IDPS模型在多大程度上能够降低误报率和漏报率？
• RQ4 该模型在可扩展的云基础设施中检测已知攻击和零日攻击的有效性如何？
• RQ5 在生产环境中部署智能且自适应的IDPS时，关键的架构考量因素有哪些？

主要发现

• 通过结合异常检测与基于签名的检测的优势，集成IDPS模型显著提升了威胁检测的覆盖范围。
• 通过关联AD与SD输出结果，系统展现出更高的检测准确率和更低的误报率。
• 实时防护功能可立即阻断恶意流量，最大限度减少对云工作负载的潜在损害。
• 该架构支持水平扩展，适用于具有动态资源分配的大规模云部署。
• 该模型提供一种主动防御机制，能够适应不断演变的攻击模式，包括此前未知的威胁。
• 将IDS与IPS功能整合到单一框架中，相比独立系统，显著降低了运维开销并提高了响应效率。