分布式拒绝服务攻击及防范研究

拒绝服务攻击(Denial of Service,DoS)是网络上最常见的一种攻击方式,其攻击类型繁多、影响广泛,其中的分布式拒绝服务攻击(Distributed Denial of Service,DDoS)更是严重威胁网络安全,受到这种攻击的损失是无法计量的。系统地分析了分布式拒绝服务攻击的攻击原理和攻击类型,通过研究各个DDoS攻击程序提出相应的防御方法。     

防御DDoS攻击算法

目前,对商业服务器攻击方式主要有两种,包括拒绝服务（DoS）攻击和分布式拒绝服务（DDoS）攻击。这种攻击类型属于命中一运行类型。DoS／DDoS攻击因为不够灵敏而不能绕过防火墙等防御．即DoS／DDoS攻击向受害主机发送大量看似合法的网络包．从而造成网络阻塞或服务器资源耗尽而导致拒绝服务。虽然数据没有被损坏。但是服务器最终被摧毁．并且还会引发一系列其他的问题．对于一个电子商务服务器．其最重要的为服务器的停机时间。研究对分布式拒绝服务（DDoS）防御原则。     

Intrusion Detection Systems of ICMPv6-based DDoS attacks

Neural Computing and Applications - Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks are thorny and a grave problem of today’s Internet, resulting in economic damages...     

基于流量行为特征的DoS&DDoS攻击检测与异常流识别

针对现有方法仅分析粗粒度的网络流量特征参数,无法在保证检测实时性的前提下识别出拒绝服务(DoS)和分布式拒绝服务(DDoS)的攻击流这一问题,提出一种骨干网络DoS&DDoS攻击检测与异常流识别方法。首先,通过粗粒度的流量行为特征参数确定流量异常行为发生的时间点;然后,在每个流量异常行为发生的时间点对细粒度的流量行为特征参数进行分析,以找出异常行为对应的目的IP地址;最后,提取出与异常行为相关的流量进行综合分析,以判断异常行为是否为DoS攻击或者DDoS攻击。仿真实验的结果表明,基于流量行为特征的DoS&DDoS攻击检测与异常流识别方法能有效检测出骨干网络中的DoS攻击和DDoS攻击,并且在保证检测实时性的同时,准确地识别出与攻击相关的网络流量     

分布式拒绝服务（DDoS）与防护

分布式拒绝服务攻击是目前严重影响网络安全和威胁网站服务质量的一种攻击手段。文章中讨论了拒绝服务攻击和分布式拒绝服务攻击的产生方式和特点,并提出了相应的防护措施。     

Distributed Denial of Service Attacks: A Threat or Challenge

In today’s cyber world, the Internet has become a vital resource for providing a plethora of services. Unavailability of these services due to any reason leads to huge financial implications or even consequences on society. Distributed Denial of Service (DDoS) attacks have emerged as one of the most serious threats to the Internet whose aim is to completely deny the availability of different Internet based services to legitimate users. The attackers compromise a large number of Internet enabled devices and gain malicious control over them by exploiting their vulnerabilities. Simplicity of launching, traffic variety, IP spoofing, high volume traffic, involvement of numerous agent machines, and weak spots in Internet topology are important characteristics of DDoS attacks and makes its defense very challenging. This article provides a survey with the enhanced taxonomies of DDoS attacks and defense mechanisms. Additionally, we describe the timeline of DDoS attacks to date and attempt to discuss its impact according to various motivations. We highlighted the general issues, challenges, and current trends of DDoS attack technology. The aim of the article is to provide complete knowledge of DDoS attacks and defense mechanisms to the research community. This will, in turn, help to develop a powerful, effective, and efficient defense mechanism by filling the various research gaps addressed in already proposed defense mechanisms.     

An approach for detecting and preventing DDoS attacks in campus

Nowadays, Denial of Service (DoS) attacks have become a major security threat to networks and the Internet. Therefore, even a naive hacker can launch a large-scale DoS attack to the victim from providing Internet services. This article deals with the evaluation of the Snort IDS in terms of packet processing performance and detection. This work describes the aspect involved in building campus network security system and then evaluates the campus network security risks and threats, mainly analyses the attacks DoS and DDoS, and puts forward new approach for Snort campus network security solutions. The objective is to analyze the functional advantages of the solution, deployment and configuration of the open source based on Snort intrusion detection system. The evaluation metrics are defined using Snort namely comparison between basic rules with new ones, available bandwidth, CPU loading and memory usage.     

Improving the resilience of content distribution networks to large scale distributed denial of service attacks

Distributed Denial of Service (DDoS) attacks remain a daunting challenge for Internet service providers. Previous work on countering these attacks has focused primarily on attacks at a single server location and the associated network infrastructure. Increasingly, however, high-volume sites are served via content distribution networks (CDNs). In this paper, we propose two mechanisms to withstand and deter DDoS attacks on CDN-hosted Web sites and the CDN infrastructure. First, we present a novel CDN request routing algorithm which allows CDN proxies to effectively distinguish attacks from the requests from actual users. The proposed scheme, based on the keyed hash function, can significantly improve the resilience of CDNs to DDoS attacks. In particular, the resilience of a CDN, consisting of n proxies, becomes O(n²) with the proposed approach, when compared to a site hosted by a single server. We present performance numbers from a controlled test environment to show that the proposed approach is effective. Second, we introduce novel site allocation algorithms based on the well-established theory on binary codes. The proposed allocation algorithm guarantees an upper bound on the level of service outage of a CDN-hosted site even when a DoS attack on another site on the same CDN has been successful. Together, our schemes significantly improve the resilience of the Web sites hosted by CDNs, and complement other work on countering DoS.     

防御DDoS攻击的智能过滤模型

拒绝服务攻击(DoS)和分布式拒绝服务攻击(DDoS)已经成为网络最大的安全威胁之一,如何防御DDoS攻击已经引起了人们的广泛关注,然而关于在DDoS攻击发生时减轻攻击危害的这方面工作却很少。阐述了一种基于IP返回追踪的数据包智能过滤模型,能够在DDoS攻击正在发生时尽可能响应合法用户的请求,提高合法通信的吞吐量。     

Characterizing DDoS attacks and flash events: Review,research gaps and future directions

A Distributed Denial of Service (DDoS) attack is an austere menace to network security. Nowadays in a technological era, DDoS attacks pose a severe threat to widely used Internet-based services and applications. Disruption of these services even for a fraction of time lead to huge financial losses. A Flash event (FE) is similar to a DDoS attack wherein a large number of legitimate users starts accessing a particular service concurrently leading to the denial of service. Both of these events cause overloading of network resources such as bandwidth, CPU, Memory to legitimate users and result in limited accessibility. Nowadays most of the DDoS attacks use the logical semantics of HTTP protocol to launch a similar kind of attack traffic as that of legitimate traffic which makes the distinction between the two very challenging. Many researchers have tried to discriminate these two types of traffic, but none of them has been able to provide any effective solution yet. This paper systematically reviews 40 such prominent research papers from 2002 to till date for providing insight into the problem of discriminating DDoS and FEs. This article dowries and deliberates the list of traffic feature rationales and detection metrics used by the fellow researchers at both macro and micro level. Such a pragmatic list of rationales would surely be helpful to provide more robust and efficient solutions. The paper also highlights open issues, research challenges and future directions in this area.     

基于小波神经网络的DDoS攻击检测及防范

DDoS攻击的检测及防范是目前计算机安全研究领域中的难点和热点。文章在系统地分析比较国内外DDoS攻击检测及防范理论和方法的基础上,根据DDoS攻击时引起网络数据流异常波动的特点,运用小波神经网络理论和方法,建立了DDoS检测和防范模型,并据此设计了相应的软件产品。仿真结果显示,该方法能有效地检测和防范DDoS攻击。     

DDoS攻击和防御机制分类研究

随着Internet的迅速发展,网络安全问题日益突出,其中分布式拒绝服务（DDoS）攻击对Internet构成巨大威胁。在分析DDoS攻击机理的基础上,对攻击和防御机制进行分类,以便有效地分析、认识分布式拒绝服务攻击行为。     

校园网DDoS攻击防御平台建设方案研究

分布式拒绝服务攻击(DDoS)已经成为互联网最大的威胁之一。分析了校园网现状,建立了业务模型,提出了流量清洗设备的功能要求,设计了一种校园网DDoS攻击防御平台的设计方案。并分析了DDOS攻击清洗方案的流量牵引技术、触发技术、流量清洗技术与流量回注技术。     

Transport-aware IP routers: a built-in protection mechanism to counter DDoS attacks

The lack-of service differentiation and resource isolation by current IP routers exposes their vulnerability to Distributed Denial of Service (DDoS) attacks (Garber, 2000), causing a serious threat to the availability of Internet services. Based on the concept of layer-4 service differentiation and resource isolation, where the transport-layer information is inferred from the IP headers and used for packet classification and resource management, we present a transport-aware IP (tIP) router architecture that provides fine-grained service differentiation and resource isolation among different classes of traffic aggregates. The tIP router architecture consists of a fine-grained Quality-of-Service (QoS) classifier and an adaptive weight-based resource manager. A two-stage packet-classification mechanism is devised to decouple the fine-grained QoS lookup from the usual routing lookup at core routers. The fine-grained service differentiation and resource isolation provided inside the tIP router is a powerful built-in protection mechanism to counter DDoS attacks, reducing the vulnerability of Internet to DDoS attacks. Moreover, the tIP architecture is stateless and compatible with the Differentiated Service (DiffServ) infrastructure. Thanks to its scalable QoS support for TCP control segments, the tIP router supports bidirectional differentiated services for TCP sessions.     

云环境下基于SOAP的Web服务应用层DoS攻击检测系统

针对云计算环境中的Web服务应用层容易遭受攻击的问题,提出一种用于Web服务应用层的基于SOAP的检测XML和HTTP层分布式拒绝服务(DDoS)攻击的防御系统。首先,从属于特定简单对象访问协议(SOAP)正常操作中提取数据集的特征值,构建相应的高斯请求模型;然后,对Web服务的网络服务描述语言(WSDL)中的一些属性进行设置,实现对攻击的初步过滤;再后,对服务请求的HTTP头部和XML内容进行检查,并与模型数据比较,进一步实现攻击检测。实验结果表明,该系统能够有效的预防多种DDoS攻击,且消耗较少的响应时间。     

Defending against Distributed Denial of Service Attacks: Issues and Challenges

ABSTRACT

Distributed Denial of Service (DDoS) attacks on user machines, organizations, and infrastructures of the Internet have become highly publicized incidents and call for immediate solution. It is a complex and difficult problem characterized by an explicit attempt of the attackers to prevent access to resources by legitimate users for which they have authorization. Several schemes have been proposed on how to defend against these attacks, yet the problem still lacks a complete solution. The main purpose of this paper is therefore twofold. First is to present a comprehensive study of a wide range of DDoS attacks and defense methods proposed to combat them. This provides better understanding of the problem, current solution space, and future research scope to defend against DDoS attacks. Second is to propose an integrated solution for completely defending against flooding DDoS attacks at the Internet Service Provider (ISP) level.     

基于蚁群优化的DDoS防御技术研究

分布式拒绝服务(DDoS)是目前攻击范围最广、破坏性最大的网络攻击之一。为此,提出一种基于数字蚂蚁的网络信息系统安全防御模型。利用蚁群优化算法计算网络中节点的资源相关性,构建一个防御DDoS攻击的数字蚂蚁联盟模型,通过确定DDoS攻击方式、标记数据报和限制流量3个步骤,实现一种具有群体智能和协同性的防御机制。     

网络攻击追踪技术性能分析

DoS攻击(拒绝服务攻击)和DDoS攻击(分布式拒绝服务攻击)IP追踪目前成为当今网络安全领域中最难解决的问题,IP追踪系统目的是在数据包源地址非真时识别出IP数据包源地址.对一些解决该问题最有前景的追踪技术进行了比较,以寻找更有效方法,并提出了一个新的IP追踪系统,该系统能够只用一个数据包就可以实现追踪而不需要受害者数据包.     

基于生存性的DoS攻击防御方案

拒绝服务攻击(DoS)是Internet中常见的一种攻击形式,提出一种基于覆盖网络的防御DoS攻击的方案。通过覆盖网络中的冗余资源和自恢复功能确保系统在遭到DoS攻击时仍能提供一定性能的服务,并可自动从攻击中恢复正常。