通信类英文文献及翻译

姓名：峻霖班级：通信143班学号：2014101108
附录
一、英文原文：
Detecting Anomaly Traffic using Flow Data in the
real VoIP network
I. INTRODUCTION
Recently, many SIP[3]/RTP[4]-based VoIP applications and services have appeared and their penetration ratio is gradually increasing due to the free or cheap call charge and the easy subscription method. Thus, some of the subscribers to the PSTN service tend to change their home telephone services to VoIP products. For example, companies in Korea such as LG Dacom, Samsung Net- works, and KT have begun to deploy SIP/RTP-based VoIP services. It is reported that more than five million users have subscribed the commercial VoIP services and 50% of all the users are joined in 2009 in Korea [1]. According to IDC, it is expected that the number of VoIP users in US will increase to 27 millions in 2009 [2]. Hence, as the VoIP service becomes popular, it is not surprising that a lot of VoIP anomaly traffic has been already known [5]. So, Most commercial service such as VoIP services should provide essential security functions regarding privacy, authentication, integrity and
non-repudiation for preventing malicious traffic. Particu- larly, most of current SIP/RTP-based VoIP services supply the minimal security function related with authentication. Though secure transport-layer protocols such as Transport Layer Security (TLS) [6] or Secure RTP (SRTP) [7] have been standardized, they have not been fully implemented and deployed in current VoIP applications because of the overheads of implementation and performance. Thus, un-encrypted VoIP packets could be easily sniffed and forged, especially in wireless LANs. In spite of authentication,the authentication keys such as MD5 in the SIP header could be maliciously exploited, because SIP is a text-based protocol and unencrypted SIP packets are easily decoded. Therefore, VoIP services are very vulnerable to attacks exploiting SIP and RTP. We aim at proposing a VoIP anomaly traffic detection method using the flow-based traffic measurement archi-tecture. We consider three representative VoIP anomalies called CANCEL, BYE Denial of Service (DoS) and RTP flooding attacks in this paper, because we found that malicious users in wireless LAN could easily perform these attacks in the real VoIP network. For monitoring VoIP packets, we employ the IETF IP Flow Information eXport (IPFIX) [9] standard that is based on NetFlow v9. This traffic measurement method provides a flexible and extensible template structure for various protocols, which is useful for observing SIP/RTP flows [10]. In order to capture and export VoIP packets into IPFIX flows, we define two additional IPFIX templates for SIP and RTP flows. Furthermore, we
add four IPFIX fields to observe 802.11 packets which are necessary to detect VoIP source spoofing attacks in WLANs.
II. RELATED WORK
[8] proposed a flooding detection method by the Hellinger Distance (HD) concept. In [8], they have pre- sented INVITE, SYN and RTP flooding detection meth-ods. The HD is the difference value between a training data set and a testing data set. The training data set collected traffic over n sampling period of duration Δ t.The testing data set collected traffic next the training data set in the same period. If the HD is close to ‘1’, this testing data set is regarded as anomaly traffic. For using this method, they assumed that initial training data set did not have any anomaly traffic. Since this method was based on packet counts, it might not easily extended to detect other anomaly traffic except flooding. On the other hand, [11] has proposed a VoIP anomaly traffic detection method using Extended Finite State Machine (EFSM). [11] has suggested INVITE flooding, BYE DoS anomaly traffic and media spamming detection methods. However, the state machine required more memory because it had to maintain each flow. [13] has presented NetFlow-based VoIP anomaly detection methods for INVITE, REGIS-TER, RTP flooding, and REGISTER/INVITE scan. How-ever, the VoIP DoS attacks considered in this paper were not considered. In [14], an IDS approach to detect SIP anomalies was developed, but only simulation results are presented. For monitoring VoIP traffic, SIPFIX [10] has been proposed as an IPFIX extension. The key ideas of the SIPFIX are application-layer inspection and
SDP analysis for carrying media session information. Yet, this paper presents only the possibility of applying SIPFIX to DoS anomaly traffic detection and prevention. We described the preliminary idea of detecting VoIP anomaly traffic in [15]. This paper elaborates BYE DoS anomaly traffic and RTP flooding anomaly traffic detec-tion method based on IPFIX. Based on [15], we have considered SIP and RTP anomaly traffic generated in wireless LAN. In this case, it is possible to generate the similiar anomaly traffic with normal VoIP traffic, because attackers can easily extract normal user information from unencrypted VoIP packets. In this paper, we have extended the idea with additional SIP detection methods using information of wireless LAN packets. Furthermore, we have shown the real experiment results at the commercial VoIP network.
III. THE VOIP ANOMALY TRAFFIC DETECTION METHOD
A. CANCEL DoS Anomaly Traffic Detection
As the SIP INVITE message is not usually encrypted, attackers could extract fields necessary to reproduce the forged SIP CANCEL message by sniffing SIP INVITE packets, especially in wireless LANs. Thus, we cannot tell the difference between the normal SIP CANCEL message and the replicated one, because the faked CANCEL packet includes the normal fields inferred from the SIP INVITE message. The attacker will perform the SIP CANCEL DoS attack at the same wireless LAN, because the purpose of the SIP CANCEL attack is to prevent the normal call estab-lishment when a victim is waiting for calls. Therefore, as soon
as the attacker catches a call invitation message for a victim, it will send a SIP CANCEL message, which makes the call establishment failed. We have generated faked SIP CANCEL message using sniffed a SIP INVITE message.Fields in SIP header of this CANCEL message is the same as normal SIP CANCEL message, because the attacker can obtain the SIP header field from unencrypted normal SIP message in wireless LAN environment. Therefore it is impossible to detect the CANCEL DoS anomaly traffic using SIP headers, we use the different values of the wireless LAN frame. That is, the sequence number in the 802.11 frame will tell the difference between a victim host and an attacker. We look into source MAC address and sequence number in the 802.11 MAC frame including a SIP CANCEL message as shown in Algorithm 1. We compare the source MAC address of SIP CANCEL packets with that of the previously saved SIP INVITE flow. If the source MAC address of a SIP CANCEL flow is changed, it will be highly probable that the CANCEL packet is generated by a unknown user. However, the source MAC address could be spoofed. Regarding 802.11 source spoofing detection, we employ the method in [12] that uses sequence numbers of 802.11 frames. We calculate the gap between n-th and (n-1)-th 802.11 frames. As the sequence number field in a 802.11 MAC header uses 12 bits, it varies from 0 to 4095. When we find that the sequence number gap between a single SIP flow is greater than the threshold value of N that will be set from the experiments, we determine that the SIP host address as been spoofed for the anomaly traffic.
B. BYE DoS Anomaly Traffic Detection
In commercial VoIP applications, SIP BYE messages use the same authentication field is included in the SIP IN-VITE message for security and accounting purposes. How-ever, attackers can reproduce BYE DoS packets through sniffing normal SIP INVITE packets in wireless LANs.The faked SIP BYE message is same with the normal SIP BYE. Therefore, it is difficult to detect the BYE DoS anomaly traffic using only SIP header information.After sniffing SIP INVITE message, the attacker at the same or different subnets could terminate the normal in- progress call, because it could succeed in generating a BYE message to the SIP proxy server. In the SIP BYE attack, it is difficult to distinguish from the normal call termination procedure. That is, we apply the timestamp of RTP traffic for detecting the SIP BYE attack. Generally, after normal call termination, the bi-directional RTP flow is terminated in a bref space of time. However, if the call termination procedure is anomaly, we can observe that a directional RTP media flow is still ongoing, whereas an attacked directional RTP flow is broken. Therefore, in order to detect the SIP BYE attack, we decide that we watch a directional RTP flow for a long time threshold of N sec after SIP BYE message. The threshold of N is also set from the experiments.Algorithm 2 explains the procedure to detect BYE DoS anomal traffic using captured timestamp of the RTP packet. We maintain SIP session information between clients with INVITE and OK messages including the same Call-ID and 4-tuple (source/destination IP Address and port number) of the BYE
packet. We set a time threshold value by adding Nsec to the timestamp value of the BYE message. The reason why we use the captured timestamp is that a few RTP packets are observed under 0.5 second. If RTP traffic is observed after the time threshold, this will be considered as a BYE DoS attack, because the VoIP session will be terminated with normal BYE messages. C. RTP Anomaly Traffic Detection Algorithm 3 describes an RTP flooding detection method that uses SSRC and sequence numbers of the RTP header. During a single RTP session, typically, the same SSRC value is maintained. If SSRC is changed, it is highly probable that anomaly has occurred. In addition, if there is a big sequence number gap between RTP packets, we determine that anomaly RTP traffic has happened. As inspecting every sequence number for a packet is difficult, we calculate the sequence number gap using the first, last, maximum and minimum sequence numbers. In the RTP header, the sequence number field uses 16 bits from 0 to 65535. When we observe a wide sequence number gap in our algorithm, we consider it as an RTP flooding attack.
IV. PERFORMANCE EVALUATION
A. Experiment Environment
In order to detect VoIP anomaly traffic, we established an experimental environment as figure 1. In this envi-ronment, we employed two VoIP phones with wireless LANs, one attacker, a wireless access router and an IPFIX flow collector. For the realistic performance evaluation, we directly used one of the working VoIP networks deployed in Korea where an 11-digit telephone number (070-XXXX-XXXX) has been assigned to a SIP phone.With wireless SIP phones supporting 802.11, we could make calls to/from the PSTN or cellular phones. In the wireless access router, we used two wireless LAN cards- one is to support the AP service, and the other is to monitor 802.11 packets. Moreover, in order to observe VoIP packets in the wireless access router, we modified nProbe [16], that is an open IPFIX flow generator, to create and export IPFIX flows related with SIP, RTP, and 802.11 information. As the IPFIX collector, we have modified libipfix so that it could provide the IPFIX flow decoding function for SIP, RTP, and 802.11 templates. We used MySQL for the flow DB.
B. Experimental Results
In order to evaluate our proposed algorithms, we gen-erated 1,946 VoIP calls with two commercial SIP phones and a VoIP anomaly traffic generator. Table I shows our experimental results with precision, recall, and F-score that is the harmonic mean of precision and recall. In CANCEL DoS anomaly traffic detection, our algorithm represented a few false negative cases, which was related with the gap threshold of the sequence number in 802.11 MAC header. The average of the F-score value for detecting the SIP CANCEL anomaly is 97.69%.For BYE anomaly tests, we generated 755 BYE mes-sages including 118 BYE DoS anomalies in the exper-iment. The proposed BYE DoS anomaly traffic detec-tion algorithm found 112 anomalies with the F-score of 96.13%. If an RTP flow is terminated before the threshold, we regard the anomaly flow as a normal one. In this algorithm, we extract RTP session information from INVITE and OK or session description messages using the same Call-ID of BYE message. It is possible not to capture those packet, resulting in a few false-negative cases. The RTP flooding anomaly traffic detection experiment for 810 RTP sessions resulted in the F score of 98%.The reason of false-positive cases was related with the sequence number in RTP header. If the sequence number of anomaly traffic is overlapped with the range of the normal traffic, our algorithm will consider it as normal traffic.
V. CONCLUSIONS
We have proposed a flow-based anomaly traffic detec-tion method against SIP and RTP-based anomaly traffic in this paper. We presented VoIP anomaly traffic detection methods with flow data on the wireless access router. We used the IETF IPFIX standard to monitor SIP/RTP flows passing through wireless access routers, because its template architecture is easily extensible to several protocols. For this purpose, we defined two new IPFIX templates for SIP and RTP traffic and four new IPFIX fields for 802.11 traffic. Using these IPFIX flow templates,we proposed CANCEL/BYE DoS and RTP flooding traffic detection algorithms. From experimental results on the working VoIP network in Korea, we showed that our method is able to detect three representative VoIP attacks on SIP phones. In CANCEL/BYE DoS anomaly traffic
detection method, we employed threshold values about time and sequence number gap for classfication of normal and abnormal VoIP packets. This paper has not been mentioned the test result about suitable threshold values. For the future work, we will show the experimental result about evaluation of the threshold values for our detection method.
二、英文翻译：
交通流数据检测异常在真实的世界中使用的VoIP网络
一 .介绍
最近,多SIP[3],[4]基于服务器的VoIP应用和服务出现了,并逐渐增加他们的穿透比及由于自由和廉价的通话费且极易订阅的法。

因此,一些用户服务倾向于改变他们PSTN家里服务VoIP产品。

例如,公司在国LG、三星等Dacom网-作品、KT已经开始部署SIP / RTP-based VoIP服务。

据报道,超过5百万的用户已订阅《商业VoIP服务和50%的所有的用户都参加了2009年在国[1]。

据IDC,预期该用户的数量将增加在我们的VoIP 2009年到27百万[2]。

因此,随着VoIP 服务变得很受欢迎,这是一点也不意外,很多人对VoIP异常交通已经知道[5]。

所以,大多数商业服务如VoIP服务应该提供必要的安全功能对于隐私、认证、完整性和不可否认对于防止恶意的交通。

Particu - larly,大多数的电流SIP / RTP-based VoIP服务提供最小安全功能相关的认证。

虽然安全transport-layer 一类协议传输层安全(TLS)[6]或安全服务器(SRTP)[7]已经被修正,它们并没有被完全实施和部署在当前的VoIP应用的实施,因为过顶球和性能。

因此,un-encrypted VoIP包可以轻易地嗅和伪造的,特别是在无线局域网。

尽管的认证, 认证键,如MD5在SIP头可以狠的剥削,因为SIP是基于文本的协议和未加密的SIP包都很容易地被解码。

因此,VoIP服务很容易被攻击开发SIP和服务器。

我们的目标是在提出一个VoIP异常交通检测法archi-tecture使用流转交通测量。

我们认为有代表性的VoIP异常称为取消,再见拒绝服务(DoS)和快速的洪水袭击在本文中,因为我们发现恶意的用户在无线局域网可以很容易地履行这些袭击的真正的VoIP网络。

VoIP包监测,利用IETF出口(IPFIX IP流信息)[9]标准的基础上,对NetFlow 9节。

这一交通测量法的研究提供了一个灵活的、可扩展的模板结构为各种各样的协议,有利于对观察SIP /服务器流[10]。

摘要为获取和出口VoIP包成IPFIX流中,我们定义两个额外的IPFIX模板为SIP和快速流动。

此外,我们加上四个IPFIX领域观察802.11包所必需的欺骗攻击的检测在WLANs VoIP来源。

二.相关工作
[8]提出了一种检测法Hellinger洪水的距离(简称HD)的概念。

文献[8]中,
他们有售前介绍邀请,洪水:SYN和快速检测种法。

高清是之间的差异值的训练数据集和测试的数据集。

收集的训练数据集的交通量持续时间Δn采样期t。

收集的测试数据集的训练数据集下的流量可以在同一时间。

如果高清接近' 1 ',该测试数据集被视为异常交通。

为使用这个法,他们假定初始训练数据集上没有任异常交通。

因为这种法是基于分组数,它可能不会很容易地扩展来侦测其他异常交通除了洪水泛滥。

另一面,[11]提出了一项VoIP异常交通检测法,利用扩展有限状态机(EFSM)。

[11]建议邀请洪水,再见DoS异常交通和媒体垃圾检测的法。

然而,状态机的需要更多的存空间,因为它已经保持每个流程。

[13]已经呈现出NetFlow-based VoIP异常检测法,REGIS-TER邀请,琳琅驱,而注册/邀请扫描。

How-ever VoIP DoS攻击,本文认为不被考虑。

在[14],一个入侵检测系统(IDS)的法来检测,研制了SIP的异常,但是只有仿真的结果。

VoIP交通、SIPFIX监测[10]作为IPFIX提出了延长。

SIPFIX的主要思路的分析是应用层检验和SDP装载媒体会话的信息。

然而,本文提出只有中应用的可能性,SIPFIX DoS异常交通检测器和预防。

我们描述了初步的构思的交通状况检测VoIP异常[15]。

阐述了交通,再见DoS异常交通detec-tion洪水异常快速IPFIX法的基础上。

基于[15],我们一直认为SIP和服务器异常交通产生在无线局域网。

在这种情况下,就有可能产生类似的异常交通与正常VoIP交通,因为攻击者就很容易从普通用户信息提取未加密的VoIP的数据包。

在本文中,我们已经将这个想法与额外的SIP检测法的使用信息的无线局域网的数据包。

此外,我们已经表现出真正的实验结果在商业VoIP网络。

三.交通检测器的VOIP异常法
a.取消DoS异常交通检测器
为SIP邀请信息通常是不加密的,攻击者可以提取领域繁殖伪造的必要信息通过嗅闻啜啜取消邀请包,特别是在无线局域网。

因此,我们不能辨别其正常SIP 取消短信与复制的一个,因为管理领域包括正常取消包推断出SIP邀请的讯息。

攻击者将会执行的园区取消DoS攻击,因为相同的无线局域网的目的是为了防止SIP取消攻击时的正常叫estab-lishment受害者正等待着。

因此,尽快打邀请袭击者渔获的信息,为一个受害者,就会发送一个SIP取消消息,这使得叫建立失败了。

我们产生了伪造的SIP取消消息使用嗅一口邀请的讯息。

工业园区头球的领域都是一样的,取消信息正常SIP取消留言,因为攻击者无法获得SIP标题域SIP 消息未加密的正常从无线局域网的环境。

因此无法检测交通使用DoS异常取消标题,我们使用了SIP的值不同的无线局域网帧。

也就是说,序号在画框会在802.11分辨一个受害者的主人和一个攻击者。

我们看着源MAC地址和序列号的MAC框架包括一小口802.11取消信息显示在算法1。

我们比较了源MAC
地址的SIP取消包与先前储存的SIP邀请流动。

如果源MAC地址的一小口取消流量发生变化时,它会有很高的可能取消包所产生的未知的用户。

然而,源MAC 地址可以欺骗时。

关于802.11源掺假检测,利用法在[12],使用序列号802.11的帧。

我们之间的差距,最后对计算-th(n-1 802.11的帧。

)作为序号在现场的使用12位802.11 MAC头球,它不同于从0到4095。

当我们发现序号在一个单一的SIP流量差距大于阈值,将定氮的实验结果,我们确定SIP主机地址被欺骗时为异常交通。

b.再见DoS异常交通检测器
VoIP应用在商业,SIP再见消息使用相同的认证领域包括在SIP IN-VITE的信息,为安全、会计的目的。

How-ever,攻击者可以复制再见DoS信息包通过嗅正常SIP邀请包的无线局域网。

信息管理SIP再见也用正常的SIP再见。

因此,很难侦测再见DoS异常交通只利用SIP的标题信息。

信息后,闻了闻SIP邀请攻击者在相同或不同的子网,可以终止在正常围之,因为它可以进步中获得成功,生成了再见消息给SIP代理服务器。

在SIP再见攻击,难以区分,从普通的终止程序。

也就是说,我们申请时间戳的快速交通侦测SIP再见的攻击。

一般来说,普通后,由双向快速流终止结束时仍很快就空间的时间。

然而,如果这个调用终止程序是异常时,我们能观察到的媒体流向快速仍在进行,但是攻击流量定向琳琅坏了。

因此,为了检测SIP再见的进攻,我们决定,我们观看了一场向快速流在很长一段时间后的最低门槛,N秒SIP再见消息。

入口处的N也将从实验。

算法的程序来检测2解释说再见DoS anomal交通用被俘的时间戳的快速包。

我们保持SIP会话之间信息的客户提供包括邀请和好的信息和4-tuple相同的Call-ID(源/目的IP地址和端口)再见包。

我们约个时间通过增加Nsec阈值的时间戳的价值信息。

再见我们为什么使用捕获的时间戳是那几个服务器包下观察0.5秒。

如果服务器后交通观测时间阈值,这将被视为一种再见DoS攻击,因为VoIP会议将终止与正常再见消息。

服务器异常交通检测算法之3描述了一种快速检测法,使用SSRC洪水和顺序编号的服务器的标题。

会议期间,通常一个单一的服务器,同样的SSRC 价值得以维持。

如果SSRC也发生了变化,极有可能就是异常发生时。

另外,如果有一个很大的序列号差距包,我们确定服务器异常交通发生。

服务器检查每一个序列作为一个包是困难的,我们计算序列号的差距,最后使用第一,最大和最小顺序编号。

在服务器页眉、序号在现场使用16位从0到65535之间。

当我们看到一个宽的序列号差距在我们的法,我们觉得这是一种快速的洪水袭击。

四. 绩效评估
a. 试验环境
为了检测VoIP异常交通,我们建立了一个实验环境为图1。

在这个环境,我们
聘用了两VoIP与无线局域网,一个袭击者,无线接入路由器和IPFIX流收藏家。

对现实的绩效评估,我们直接采用VoIP网络的工作之一11-digit部署在国当在一个(070-XXXX-XXXX)已被分配到一个SIP。

SIP支持802.11无线,我们可以打到/从PSTN或手机。

在无线接入路由器,我们使用了两种无线局域网卡-一个是为了支持美联社服务,另一个是监听802.11的数据包。

此外,为了观察VoIP包的无线接入路由器,我们修改nProbe[16],那是一个开放的IPFIX流发生器、创造和出口IPFIX流动相关的喝了一口,琳琅,802.11的信息。

随着IPFIX收藏家,我们更改了,它会libipfix流动提供了IPFIX解码功能为喝了一口,琳琅,802.11模板。

我们使用MySQL的流量分贝。

b.实验结果
为了评估我们提出的演算法,我们gen-erated 1,946 VoIP和两个商业SIP 和VoIP异常交通的发电机。

实验结果显示我们的桌子上我和精确,召回,这是F-score谐波均值的精度和召回率的两倍。

在DoS异常交通检测器取消,我们的算法代表了一些假负面的案例,这是关系到阈值的差距序列号在802.11 MAC的标题。

F-score值的平均值为检测97.69%.For SIP取消异常是产生异常的测试中,我们再见再见再见mes-sages包括118靶向exper-iment DoS异常之处。

提出的交通detec-tion再见DoS异常算法与F-score 112异常发现的96.13%。

如果一个快速流是前终止阈值,我们把异常流量作为一个正常的人。

该算法提取信息从服务器会话的邀请和好的或者会议简介讯息使用相同的Call-ID再见消息。

它是可能的,不是来捕捉那些包,导致一些最后的病例。

洪水异常交通检测器的服务器会话810对试验结果的分析导致了服务器的F值可达到98%以上。

假阳性病例的原因与服务器的序列号在页眉。

如果序列数目的异常交通搭接的正常围,我们的演算法将考虑交通是正常的交通。

五.结论
我们提出了一detec-tion流转异常交通法和SIP和RTP-based异常交通进行了论述。

我们提出了异常检测法与VoIP交通流数据的无线接入路由器。

我们使用了IETF标准监控IPFIX SIP /服务器通过无线接入路由器流动,因为模板的建筑是很容易扩展到几个协议。

为了这个目的,我们定义了两个新的IPFIX模板为SIP和快速交通和四个新IPFIX田野为802.11的交通。

使用这些IPFIX流程模版,我们提出取消/再见DoS及快速交通检测算法的洪水。

从实验的结果VoIP网络在国的工作表明,我们的法,我们可以探测到三个代表VoIP袭击SIP。

在取消/再见DoS异常交通检测法,本研究使用的阈值关于时间和序列号的差异极大的正常及异常的ip数据包。

本文还没有提到关于适当的阈值,对测试结果的价值。

对将来的工作,我们将显示实验结果对评价为我们的检测法的阈值。