10.1.1.64.2504

10.1.1.64.2504

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  Tracking Anonymous Peer-to-Peer VoIP Calls on the Internet ∗ Xinyuan Wang Shiping Chen Sushil Jajodia Department of Information and Center for Secure Information Center for Secure Information Software Engineering Systems Systems George Mason University George Mason University George Mason University Fairfax, VA 22030, USA Fairfax, VA 22030, USA Fairfax, VA 22030, USA [email protected] [email protected] [email protected] ABSTRACT Keywords Peer-to-peer VoIP calls are becoming increasingly popular VoIP, Anonymous VoIP Calls, VoIP Tracing, Peer-to-Peer due to their advantages in cost and convenience. When these Anonymous Communication calls are encrypted from end to end and anonymized by low latency anonymizing network, they are considered by many 1. INTRODUCTION people to be both secure and anonymous. VoIP is a technology that allows people to make phone In this paper, we present a watermark technique that calls through the public Internet rather than traditional could be used for effectively identifying and correlating en- Public Switched Telephone Network (PSTN). Because VoIP crypted, peer-to-peer VoIP calls even if they are anonymized offers significant cost savings with more flexible and ad- by low latency anonymizing networks. This result is in con- vanced features over Plain Old Telephone System (POTS), trast to many people’s perception. The key idea is to em- more and more voice calls are now carried at least par- bed a unique watermark into the encrypted VoIP flow by tially via VoIP. In fact, consulting firm Frost & Sullivan has slightly adjusting the timing of selected packets. Our analy- predicted that VoIP will account for approximately 75% of sis shows that it only takes several milliseconds time adjust- world voice services by 2007. ment to make normal VoIP flows highly unique and the em- For privacy reasons, people sometimes want their phone bedded watermark could be preserved across the low latency conversation to be anonymous and do not want other people anonymizing network if appropriate redundancy is applied. know that they have even talked over the phone. The use Our analytical results are backed up by the real-time exper- of VoIP has made it much easier to achieve anonymity in iments performed on leading peer-to-peer VoIP client and voice communications, especially when VoIP calls are made on a commercially deployed anonymizing network. Our re- between computers. This is because VoIP calls between peer sults demonstrate that (1) tracking anonymous peer-to-peer computers have no phone numbers associated with them, VoIP calls on the Internet is feasible and (2) low latency and they could easily be protected by end to end encryption anonymizing networks are susceptible to timing attacks. and routed through low latency anonymizing networks (e.g., Onion Routing [13], Tor [6], Freedom [3], and Tarzan [12]) to Categories and Subject Descriptors achieve anonymity. People intuitively think their computer C.2.0 [Computer-Communication Networks]: General— to computer VoIP calls could remain anonymous if they are Security and protection (e.g., firewalls); C.2.3 [Computer- encrypted end to end and routed through some low latency Communication Networks]: Network Operations—Net- anonymizing network. work monitoring On the other hand, law enforcement agencies (LEA) of- ten need to conduct lawful electronic surveillance in order to combat crime and terrorism. For example, the LEAs need General Terms techniques to determine who has called the surveillance tar- Security get and to whom the surveillance target has called. In a ∗ letter to FCC [8], several federal law enforcement agencies This work was partially supported by the Air Force Re- have considered the capability of tracking VoIP calls “of search Laboratory, Rome under the grant F30602-00-2-0512 and by the Army Research Office under the grants DAAD19- paramount importance to the law enforcement and the na- 03-1-0257 and W911NF-05-1-0374. tional security interests of the United States.” How to balance people’s needs for privacy and anonymity and the security requirements of the law enforcement agen- cies has been a subject of controversy. In this paper, we leave Permission to make digital or hard copies of all or part of this work for the controversy between anonymity and security aside and personal or classroom use is granted without fee provided that copies are instead focus on the technical feasibility of tracking anony- not made or distributed for profit or commercial advantage and that copies mous peer-to-peer VoIP calls on the Internet. Our goal is bear this notice and the full citation on the first page. To copy otherwise, to to investigate practical techniques for the effective track- republish, to post on servers or to redistribute to lists, requires prior specific ing of anonymous VoIP calls on the Internet and identify permission and/or a fee. CCS’05, November 7–11, 2005, Alexandra, Virginia, USA. the weakness of some of the currently deployed anonymous Copyright 2005 ACM 1-59593-226-7/05/0011 ...$5.00. communication systems.
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  We choose toinvestigate the popular Skype [28] peer-to- it could be used to determine if party A is communicating peer VoIP calls in the context of the anonymous VPN pro- (or has communicated) with party B via peer-to-peer VoIP vided by findnot.com [11]. Skype offers free computer to even if the VoIP traffic is (or has been) disguised by low computer VoIP calls based on KaZaa [16] peer-to-peer tech- latency anonymous communication systems. nology. Several properties of Skype have made it an attrac- The rest of the paper is organized as follows. Section 2 tive candidate for the investigation of tracking anonymous formulates the problem of tracking anonymous peer-to-peer VoIP calls on the Internet: VoIP calls, and describes the overall tracing model. Sec- tion 3 presents the active timing based tracking method and • It is free and widely used. Since August 2003, there analyzes its effectiveness. Section 4 describes our implemen- are over 100 million downloads of the Skype client. It tation of the high precision VoIP watermarking engine in is being actively used by millions of people all over the real-time Linux kernel. Section 5 evaluates the effectiveness world. Skype is now included in Kazaa v3.0. of our method empirically. Section 6 summarizes related works. Section 7 concludes the paper. • All the Skype traffic is encrypted from end to end by 256-bit AES encryption. 2. THE OVERALL MODEL OF TRACING • Skype can automatically traverse most firewalls and NAT (Network Address Translation) gateways with ANONYMOUS PEER-TO-PEER VOIP the help of intermediate peers. CALLS Given any two different Skype peers A and B, we are • Skype intelligently and dynamically routes the encrypted interested in determining if A is talking (or has talked) to calls through different peers to achieve low latency. B via Skype peer-to-peer VoIP. As shown in Figure 1, both This means that the route and the intermediate peer(s) Skype peers A and B have outgoing and incoming VoIP flows of one VoIP call could be changed during a call. to and from the Internet cloud. The Skype peers could be • It uses proprietary peer-to-peer signaling protocol to behind firewall and NAT, and peer A and/or B could be set up the VoIP calls. connected to some low latency anonymizing network. Here we view the Internet cloud and any low latency anonymizing Since most Skype calls are carried in UDP, we can not di- network as a black box, and we are interested only in the rectly use those anonymizing systems (such as Onion Rout- Skypy flows that enter or exit the black box. We assume ing [13], Tor [6] or anonymizer.com [1]), who do not support that (1) we can monitor the Skype flow from the black box anonymization of all UDP flows, to anonymize Skype VoIP to the Skype peer; (2) we can perturb the timing of the calls. We choose to use the anonymous communication ser- Skype flow from the Skype peer to the black box. vices by findnot.com [11] that support anonymization of all Here we do not intend to track all the peer-to-peer VoIP IP protocols through point to point tunnel protocol (PPTP). calls from anyone to anyone, nor do we assume the global The key challenge in tracking encrypted VoIP calls across monitoring and intercepting capability. Instead we focus on anonymous communication system is how to identify the finding out if some parties in which we are interested have correlation between the VoIP flows of the caller and the communicated via peer-to-peer VoIP calls anonymously, and callee. Since all the traffic of the peer-to-peer VoIP calls are we only need the capability to monitor and intercept IP flows encrypted, no signaling information is available for correla- to and from those interested parties. This model is consis- tion. To be able to track encrypted, anonymous VoIP calls tent with our understanding of the common practice of law- across the Internet, we use the timing characteristics of the ful electronic surveillance by the law enforcement agencies. anonymized VoIP flow. Unfortunately, the original inter- Because the Skype VoIP flows are encrypted from end to packet arrival characteristics of VoIP flows are not distinct end, no correlation could be found from the flow content. enough as the inter-packet timing arrival time of VoIP traf- Given that the Skype VoIP flow could pass some intermedi- fic is determined by the frame packetization interval used. ate Skype peers and some low latency anonymizing network, This means that passive comparison of the original inter- there is no correlation from the VoIP flow headers. Among packet timing characteristics of VoIP flows will not be able all the characteristics of the VoIP flows, the inter-packet to distinguish different VoIP calls. timing characteristics are likely to be preserved across inter- In order to uniquely identify the anonymous VoIP calls mediate Skype peers and low latency anonymizing network. through inter-packet timing characteristics, we use an ac- This invariant property of VoIP flows forms the very foun- tive approach to deliberately make the inter-packet timing dation for tracking anonymous, peer-to-peer VoIP calls on of VoIP calls more distinctive. The idea is to embed a unique the Internet. watermark into the inter-packet timing of the VoIP flows by A number of timing based correlation methods have been slightly adjusting the timing of selected packets. If the em- proposed, and they can be classified into two categories: bedded watermark is unique enough and robust enough, the passive and active. Passive timing based correlation ap- watermarked VoIP flows could be effectively identified. By proaches (e.g. [35], [34], [33] [7], [5]) correlate the encrypted utilizing redundancy techniques, we can make the embed- flows based on passive comparison of their timing charac- ded watermark robust against random timing perturbation teristics, and they have been shown to be effective when provided there are enough packets in the VoIP flow. the timing characteristics of each flow are unique enough. Our analytical and experimental results demonstrate that However, the inter-packet timing characteristics of all VoIP (1) tracking anonymous peer-to-peer VoIP calls on the In- flows are very similar to each other. The inter-packet ar- ternet is feasible and (2) low latency anonimizing systems rival time of VoIP flows is determined by the voice codec are susceptible to timing attack. Our VoIP tracking tech- and the corresponding packetization interval, and there are nique does not require the global monitoring capability, and only a few commonly used VoIP packetization intervals (i.e.
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  Internet Cloud Skype Peer A Skype Peer B Skype VoIP flow Low Latency Intermediate Skype VoIP flow to be correlated Anonymizing Skype Peers to be correlated Network Figure 1: Anonymous Peer-to-Peer VoIP Calls Tracing Model 20ms or 30ms). Therefore, passively comparing the timing 3. ACTIVE TIMING BASED TRACKING OF characteristics of VoIP flows will not be able to distinguish VOIP FLOWS different VoIP flows. We present the new watermarking scheme which guar- Wang and Reeves [32] proposed the first active approach to correlate the encrypted flows. They suggested embedding antees the even time adjustment for embedding the water- mark in real time and has all the theoretical strengths of a unique watermark into the inter-packet timing domain of the interactive flow through deliberate timing adjustment of work [32]. Unlike the watermarking scheme proposed in previous work [32], our new watermarking scheme is prob- selected packets, and correlating based on the embedded wa- termark. Because the embedded watermark could make an abilistic in the sense that the watermark embedding suc- otherwise non-distinctive flow unique, their active method cess rate is not guaranteed 100%. In other words, the new watermarking scheme trades off the guaranteed 100% wa- has the potential to differentiate flows with very similar tim- termark embedding success rate with the guaranteed even ing characteristics. However, the method proposed in [32] can not be directly used to correlate VoIP flows due to the time adjustment for embedding the watermark. By exploit- following reasons: ing the inherent inter-packet timing characteristics of the VoIP flows, our new watermarking scheme achieves virtu- • The VoIP traffic has stringent real-time constraints, ally 100% watermark embedding success rate with guaran- and the total end to end delay should be less than teed even time adjustment for embedding the watermark. 150ms. 3.1 Basic Concept and Notion • The inter-packet arrival time of VoIP flows is very Given any packet flow P1 , . . . , Pn with time stamps t1 , short (i.e. 20ms or 30ms). This requires any time ad- . . ., tn respectively (ti < tj for 1 ≤ i < j ≤ n), we can inde- justment on VoIP packet to be very precise and small. pendently and probabilistically choose a number of packets through the following process: (1) sequentially look at each • The watermarking method proposed by Wang and Reeves of the first n−d (0 < d n) packets; and (2) independently is based on the quantization of averaged Inter-Packet determine if the current packet will be probabilistically cho- Delays (IPDs), and it requires packet buffering in or- 2r sen, with probability p = n−d (0 < r < n−d ). 2 der to achieve the even timing adjustment over differ- Here whether or not choosing the current packet is not ent packets. The required buffering would be too long affected by any previously chosen packets and it will not for the real-time VoIP flows. affect whether to choose any other packets. In other word, To correlate anonymous VoIP flows with similar inter- all the selected packets are selected independently from each packet timing characteristics, we use an active approach to other. Therefore, we can expect to have 2r distinct packets deliberately yet subtly make the inter-packet timing charac- independently and randomly selected from any packet flow teristics of the VoIP flows more unique. This is achieved by of n packets. We denote the 2r randomly selected packets embedding a unique watermark into the inter-packet timing as Pz1 , . . . , Pz2r (1 ≤ zk ≤ n − d for 1 ≤ k ≤ 2r), and create domain of the VoIP flow in real-time. 2r packet pairs: Pzk , Pzk +d (d ≥ 1, k = 1, . . . , 2r). To address the limitations of previous work [32], we use a The IPD (Inter-Packet Delay) between Pzk +d and Pzk is new watermarking scheme that is suited for tracking anony- defined as mous VoIP traffic in real-time. The key challenge in track- ipdzk ,d = tzk +d − tzk , (k = 1, . . . , 2r) (1) ing anonymous VoIP calls by the active approach is how to precisely adjust the packet timing without buffering and Because all Pzk (k = 1, . . . , 2r) are selected independently, guarantee the even time adjustment of those selected pack- ipdzk ,d is independent from each other. Since each Pzk is ets. randomly and independently selected through the same pro- cess, ipdzk ,d is identically distributed no matter what inter- packet timing distribution the packet flow P1 , . . . , Pn may have. Therefore, ipdzk ,d (k = 1, . . . , 2r) is independent and
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  Distribution of the10844 IPDs of Distribution of the 10423 IPDs of the Originating VoIP Flow 2000 the Terminating VoIP Flow 7000 1800 6000 Number of Occurances 1600 Number of Occurances 5000 1400 1200 4000 1000 3000 800 600 2000 400 1000 200 0 0 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 IPD (Inter-Packet Delay) in Millisecond IPD (Inter-Packet Delay) in Millisecond Figure 2: Distribution of IPDs of the originating and terminating Skype flows Distribution of the 10843 IPD Differences Distribution of the 10422 IPD Differences of the Originating VoIP Flow 1000 of the Terminating VoIP Flow 4500 4000 900 Number of Occurances 800 Number of Occurances 3500 700 3000 600 2500 500 2000 400 1500 300 1000 200 500 100 0 0 -10 -8 -6 -4 -2 0 2 4 6 8 10 -10 -8 -6 -4 -2 0 2 4 6 8 10 IPD (Inter-Packet Delay) Difference in Millisecond IPD (Inter-Packet Delay) Difference in Millisecond Figure 3: Distribution of IPD Differences of the originating and terminating Skype flows identically distributed (iid ). Skype peer, and the other trace is for the Skype flow that We then randomly divide the 2r IPDs into 2 distinct terminated at the other Skype peer. We call them the orig- groups of equal size. Let ipd1,k,d and ipd2,k,d (k = 1, . . . , r) inating flow and the terminating flow respectively. The left denote the IPDs in group 1 and group 2 respectively. Appar- and right chart of Figure 2 show the IPD histograms of the ently both ipd1,k,d and ipd2,k,d (k = 1, . . . , r) are iid. There- originating flow and the terminating flow respectively. They fore E(ipd1,k,d ) = E(ipd2,k,d ), and Var(ipd1,k,d ) = Var(ipd2,k,d ). all have 30ms average IPD, which indicates that the packe- Let tization interval of Skype VoIP call is 30ms. While the IPDs ipd1,k,d − ipd2,k,d of the originating Skype flow is more concentrated around Yk,d = (k = 1, . . . , r) (2) 30ms, the IPDs of the terminating Skype flow is less clus- 2 tered due to the network delay jitter. The left and right Then we have E(Yk,d ) = (E(ipd1,k,d ) − E(ipd2,k,d ))/2 = chart of Figure 3 show the histograms of Yk,d with d=1 (or 0. Because ipd1,k,d and ipd2,k,d are iid, Yk,d is also iid. We equivalently Yr,d with r=1 and d=1) of the Skype originat- 2 use σY,d to represent the variance. ing flow and the terminating flow respectively. They both We represent the average of r Yk,d ’s as confirm that the distribution of Yr,d of Skype VoIP flows is r indeed symmetric and centered around 0. 1 Yr,d = Yk,d (3) r k = 1 3.2 Embedding and Decoding A Binary Bit Probabilistically Here Yr,d represents the average of a group of normalized Since the distribution of Yr,d is symmetric and centered IPD differences, and we call r the redundancy number. Ac- around 0, the probabilities of Yr,d to be positive and negative cording to the property of variance of independent random are equal. If we decrease or increase Yr,d by an amount 2 variables, we have Var(Yr,d ) = σY,d /r. Because E(Yk,d ) = a > 0, we can shift its distribution to the left or right by 0 (k = 1, . . . , r), E(Yr,d ) = 0. Because Yk,d is symmet- a so that Yr,d will be more likely to be negative or positive. ric (k = 1, . . . , r), Yr,d is also symmetric. Therefore, the This gives us a way to embed and decode a single binary bit distribution of Yr,d is symmetrically centered around 0. probabilistically. To illustrate the validity of concepts of Yk,d and Yr,d , we To embed a bit 0, we decrease Yr,d by a, so that Yr,d collected two traces of the packet flows of a real Skype call will have > 0.5 probability to be less than 0. To embed a from two communicating Skype peers that are 27 hops and bit 1, we increase Yr,d by a, so that Yr,d will have > 0.5 over a thousand miles away (when the Skype call is routed probability to be greater than 0. By definition in equation through the commercial findnot.com anonymizing network). (3), the decrease or increase of Yr,d can be easily achieved One trace is for the Skype flow that originated from one by decreasing or increasing each of the r Yk,d ’s by a. By
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  r = 4k r = k>1 Bit ‘0’ Bit ‘1’ r=1 -a a -a a Figure 4: Embedding Binary Bit by Shifting Figure 5: Probability Distribution of Yr,d With the Distribution of Yr,d by a to the Left or Right Different r definition in equation (2), the decrease of Yk,d by a can be Therefore achieved by decreasing each ipd1,k,d by a and increasing each ipd2,k,d by a; the increase of Yk,d by a can be achieved by √ √ √ rYr,d a r a r increasing each ipd1,k,d by a and decreasing each ipd2,k,d by Pr[Yr,d < a] = Pr[ < ] ≈ Φ( ) (6) σY,d σY,d σY,d a. After Yr,d has been decreased or increased by a, we can This means that the distribution of the probabilistic wa- decode the embedded binary bit by checking whether Yr,d is termark bit embedding success rate is approximately nor- less than or greater than 0. The decoding of the embedded mally distributed with zero mean and variance σ 2 /r. binary bit is 1 if the value of Yr,d is greater than 0, or 0 if Equation (6) gives us an accurate estimate of the proba- the value of Yr,d is less than or equal to 0. It is easy to see bilistic watermark bit embedding success rate. It indicates that probability of correct decoding is always greater than that no matter what distribution Yk,d may be, no matter that of wrong decoding. what variance Yk,d may have (as long as it exists), no matter However, as shown in Figure 4, there is always a non- how small the timing adjustment a > 0 (or the watermark zero probability such that the embedded bit (with adjust- embedding strength) might be, we can always make the wa- ment a > 0) will be decoded incorrectly (i.e. Yr,d > a or termark bit embedding success rate arbitrarily close to 100% Yr,d < −a). We define the probability that the embedded bit by increasing the redundancy number r. This result holds will be decoded correctly as the bit embedding success rate true regardless of the distribution of the inter-packet timing w.r.t. adjustment a, which can be quantitatively expressed of the packet flow. as Pr(Yr,d < a). Figure 5 illustrates how the distribution of Yr,d can be Here the adjustment a is a representation of the water- “squeezed” into range [−a, a] by increasing the redundancy mark embedding strength. The larger the a is, the higher number r. the bit embedding success rate will be. We now show that Because the routers, intermediate Skype peers and the even with arbitrarily small a > 0 (or equivalently arbitrarily anonymizing network along the Skype VoIP call could intro- weak watermark embedding strength), we can achieve arbi- duce different delays over VoIP packets, we need to consider trarily close to a 100% bit embedding success rate by having the negative impact of such delay jitters over the watermark a sufficiently large redundancy number r. decoding. 2 Central Limit Theorem If the random variables X1 , Let σd be the variance of all delays added to all packets, . . ., Xn form a random sample of size n from a given distri- Xk be the random variable that denotes the perturbation bution X with mean µ and finite variance σ 2 ,then for any over Yk,d by the delay jitter, and Yk,d be the random vari- fixed number x able that denotes the resulting value of Yk,d after it has been √ perturbed by the delay jitter. We have the following quanti- n(Xn − µ) tative tradeoff among the watermark bit detection rate, the lim Pr[ ≤ x] = Φ(x) (4) n→∞ σ defining characteristics of the delay jitter, and the defining x u2 characteristics of the original inter-packet timing of the VoIP where Φ(x) = −∞ √1 e− 2 du. 2π flow, whose derivation can be found in the Appendix: The theorem indicates that whenever a random sample of size n is taken from any distribution with mean µ and finite √ variance σ 2 , the sample mean Xn will be approximately nor- a r Pr[Yr,d < a] ≈ Φ( ) σ2 mally distributed with mean µ and variance √ /n, or equiv- 2 2 σY,d + σd + 2Cor(Yk,d , Xk )σY,d σd alently the distribution of random variable n(Xn − µ)/σ √ will be approximately a standard normal distribution. a r ≥ Φ( ) (7) Applying the Central Limit Theorem to random sample σY,d + σd 2 Y1,d , . . . , Yr,d , where Var(Yk,d )= σY,d , E(Yk,d ) = 0, we have Equation (7) gives us an accurate estimate of the water- √ √ mark bit detection rate in the presence of delay jitters. The r(Yr,d − E(Yk,d )) rYr,d correlation coefficient Cor(Yk,d , Xk ), whose value range is Pr[ < x] = Pr[ < x] ≈ Φ(x) (5) Var(Yr,d ) σY,d [-1, 1], models any correlation between the network delay
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  Transparent VoIP Watermark Engine Internet Cloud PPTP Tunnel Skype Peer A Skype Peer B Watermarked Low Latency Intermediate Watermarked Original Skype Skype VoIP flow Anonymizing Skype Peers Skype VoIP flow VoIP flow Network Figure 6: Experimental Setup for the Real-Time Tracking of Anonymous, Peer to Peer Skype VoIP Calls across the Internet jitter and the packet timing of the original packet flow. In To achieve the guaranteed high precision, we choose to case the delay jitter is independent from the packet timing build our packet delay capability upon the Real Time Appli- of the packet flow, Cor(Yk,d , Xk ) will be 0. cation Interface (RTAI) [23] of Linux. The following features The important result here is that no matter what variance of RTAI have made it an attractive platform for implement- Yk,d may have (as long as it exists), no matter how large a ing the high precision packet delay capability: variance the network jitter may have, no matter how small the timing adjustment a > 0 (or the watermark embedding • The hard real-time scheduling functions introduced by strength) might be, we can always make the watermark bit The RTAI coexist with all the original Linux kernel detection rate arbitrarily close to 100% by increasing the services. This makes it possible to leverage existing redundancy number r. This result holds true regardless of Linux kernel services, especially the IP stack compo- the distribution of the network delay jitter. nents, from within the real-time task. • The RTAI guarantees the execution time of real-time 4. TRANSPARENT WATERMARKING OF tasks regardless of the current load of non real-time VOIP FLOWS IN REAL TIME tasks. In order to be able to watermark any VoIP flows transpar- • The RTAI supports high precision software timer with ently, it is desirable to have a VoIP gateway which forwards the resolution of microseconds. the VoIP flows and watermarks any specified bypassing VoIP flows with specified watermarks. To embed the watermark We built our transparent and real-time VoIP watermark- into the inter-packet timing of a VoIP flow, we need a capa- ing engine upon RTAI 3.1 in Linux kernel 2.6.8.1, and we bility to delay specified packet of specified flow for specified implemented the VoIP watermarking engine as a RTAI ker- duration. We choose to implement such a capability in the nel module. To facilitate the management of the kernel VoIP kernel of the Linux operating system. watermarking engine from user space, we also extended the One key challenge in implementing the transparent and netfilter/iptable mechanism in Linux kernel. real-time VoIP watermarking engine is how to precisely de- By integrating the RTAI hard real-time scheduling and lay an outgoing packet in real-time. The inter-packet arrival the Linux kernel functionality, our real-time VoIP water- time of normal VoIP flows is either 20ms or 30ms. This marking engine achieves the guaranteed delay precision of means that the delay of any VoIP packet must be less than 100 microseconds over any specified packets of any specified 20ms. In order to hide the watermark embedding into the flows despite the workload of the Linux kernel. “background noise” introduced by the normal network delay jitter, the delay of any VoIP packet should be no more than a few milliseconds. To achieve packet delay of such a pre- 5. EXPERIMENTS cision, the operating system must provide a hard real-time In this section, we empirically validate our active water- scheduling capability. mark based tracking of anonymous, peer-to-peer VoIP calls However, the standard Linux kernel lacks the hard real- on the Internet. In specific, we conduct our experiments time scheduling capability and it does not support time- with real-time Skype peer-to-peer VoIP calls over the com- critical tasks. Because the standard Linux is a time-sharing mercially deployed anonymizing system of findnot.com. Fig- OS, the execution of any process depends on not only the ure 6 shows the setup of our experiments. The Skype peer priority of the process but also the current load in the OS, A is connected to some entry point of the anonymizing net- and there is no guarantee that a time-critical task will be work of findnot.com via PPTP (Point to Point Tunnel Pro- processed and completed on time. In addition, the resolu- tocol) and all the Internet traffic of Skype peer A is routed tion of the software timer in the Linux kernel is by default through and anonymized by the anonymizing network of 10ms, which is too coarse for our needs. findnot.com. As a result, Skype peer B never sees the real
• 7.
  IP address ofSkype peer A, and Skype peer A could appear the Hamming distance between any two of them is at least to be some host of thousands miles away. In our experimen- 9. We then made 100 Skype calls of 2 minutes long and tal setup, the two communicating Skype peers are at least watermarked each of them with different watermark. We 27 hops away with about 60ms end to end latency. collected the originating and terminating watermarked VoIP We place our high precision VoIP watermarking engine flows from Skype peer B and A respectively, and decoded between Skype peer B and the Internet and let it transpar- the 24-bit watermarks from them. We call any bit in the ently watermark the VoIP flow from Skype peer B to peer decoded 24-bit watermark that is different from the cor- A. We intercept the VoIP flow from the anonymizing net- responding embedded bit as an error bit. Figure 9 shows work of findnot.com to Skype peer A, and try to detect the the number of error bits of the 100 Skype VoIP calls and watermark from the intercepted VoIP flow. the watermark detection true positive rates given different While Skype VoIP call can use both TCP and UDP, we numbers of allowed error bits. It indicates that very few have found that it almost always use UPD. In our experi- of the 100 watermarked originating flows has 1 or 2 error ments, all the Skype calls happen to be UPD, and none of bits, and a number of watermarked terminating flows has 1 them has noticeable packet loss. to 6 error bits. If we require the exact match between the embedded watermark and the detected watermark, then we 5.1 Watermarking Parameter Selection have 59% true positive rate. If the number of allowed error Equation (7) gives us the quantitative tradeoff between bits is increased to 4, the true positive rate becomes 99%. the watermark bit detection rate, watermark embedding pa- With number of allowed error bits being 6 or greater, we rameters and the defining characteristics of the network de- have 100% true positive rate. lay jitters. To make the embedded watermark more robust against 5.3 False Positive Experiments the network delay jitters and have high watermark bit de- No matter what watermark we choose, it is always possi- tection rate, it is desirable to have larger watermark embed- ble that an unwatermarked VoIP flow happens to have the ding delay a and bigger redundancy number r. However, a chosen watermark naturally. We call this case as a false bigger watermark embedding delay means bigger distortion positive in correlating the VoIP flows. of the original inter-packet timing of the VoIP flow, which We have shown that the true positive rate is generally could potentially be used by the adversary to determine if a higher if the number of allowed error bits is bigger. However, VoIP flow has been watermarked or not. Ideally, the delay a bigger number of allowed error bits tends to increase the introduced by the watermark embedding should be indistin- false positive rate. Therefore, it is important to choose an guishable from the normal network delay. appropriate number of allowed error bits that will yield both To understand the normal network delay jitter as well as high true positive rate and low false positive rate at the the hiding space for embedding our transparent watermark same time. To find the appropriate number of allowed error into the inter-packet timing of VoIP flows, we made a Skype bits, we need to know the false positive rates under different call of 6 minutes long without watermarking, and collected numbers of allowed error bits. the traces of the VoIP flows from both Skype peer A and Assuming the 24-bit watermark decoded from a random B. We calculated the network delay jitter by comparing the flow is uniformly distributed, then the expected false posi- timestamps of 10424 corresponding packets between the two tive rate with h ≥ 0 allowed error bits will be VoIP flows. Figure 7 shows the distribution of the normal- ized network delay jitters. It indicates that there are about h 24 1 50% chances that the network delay jitter will be equal to or ( )24 (8) i 2 bigger than 3ms. Therefore, it would be hard to distinguish i=0 any watermarked VoIP flow from unwatermarked ones if we Because each of the 100 Skype calls is watermarked with embed the watermark with 3ms delay. different watermark, any of the 100 watermarked Skype With watermark embedding delay a=3ms, we tried dif- flows has 99 uncorrelated watermarked Skype flows. Ideally, ferent redundancy numbers r to embed a 24-bit watermark the number of different bits between the 24-bit watermarks into the Skype VoIP calls over the same anonymizing net- decoded from different watermarked flows should be high. work of findnot.com. Figure 8 shows the average number Figure 10 shows the expected and measured numbers of of the error bits of the decoded watermarks of 10 Skype different bits between the 24-watermarks decoded from the calls with a range of redundancy numbers. It clearly shows 9900 pairs of uncorrelated VoIP flows as well as the expected that the number of error bits can be effectively decreased and measured watermark detection false positive rates un- by increasing the redundancy number r. With redundancy der various numbers of allowed error bits. It indicates that number r=25, the average number of error bits of the de- the measured values are very close to expected value. This coded 24-bit watermark is only 1.4. validates our assumption that the 24-bit watermark decoded In all of the following experiments, we use 24-bit water- from a random flow is uniformly distributed. marks with embedding delay a=3ms and redundancy num- Out of the 9900 pairs of uncorrelated flows, no one has less ber r=25. With this set of watermarking parameters, the than 6 different bits between the two watermarks decoded. watermarking of VoIP flow only requires 1200 packets to There are 10 pairs of uncorrelated flows that have 6 different be delayed by 3ms. Given the 30ms packetization interval bits. Therefore, if we choose 5 as the number of allowed of Skype VoIP calls, the transparent watermarking can be error bits, we would have 99% true positive rate and 0% applied to any VoIP calls that are as short as 90 seconds. false positive rate. If we use 6 as the number of allowed error bits, we would get 100% true positive rate and 0.1% 5.2 True Positive Experiments false positive rate. We randomly generated 100 24-bit watermarks such that
• 8.
  Average Number ofError bits of 24-Bit Watermark Distribution of the 10424 Network Delay Jitters 1600 8.0 7.0 Error Bit Number 1400 Number of Occurances 6.0 1200 5.0 1000 4.0 800 3.0 600 2.0 400 1.0 200 0.0 0 5 10 15 20 25 -20 -16 -12 -8 -4 0 4 8 12 16 20 Network Delay Jitter in Millisecond Redundancy Number Figure 7: Distribution of the Network Delay Jit- Figure 8: Average Number of Bit Errors vs the ters of Skype VoIP Call Redundancy Number r Correlation True Positive Rate of 100 VoIP Calls Number of Error Bits of 100 VoIP Calls 7 Originating Flow Terminating Flow 100 90 True Positive Rate % 6 80 Number of Error Bits 5 70 60 4 50 3 40 30 2 20 1 10 0 0 0 1 2 3 4 5 6 7 0 10 20 30 40 50 60 70 80 90 100 VoIP Call Number Number of Allowed Error Bits of 24-Bit Watermark Figure 9: The Numbers of Error Bits and Correlation True Positive Rates of 100 Skype VoIP Calls Distribution of Numbers of Different Bits of 9900 Pairs False Positive Rates of 9900 Pairs of of Uncorrelated VoIP Calls Uncorrelated VoIP Calls Originating Flow Terminating Flow Expected Value Originating Flow Terminating Flow Expected Value 1600 100 Number of Occurrances 1400 90 False Positive Rate % 80 1200 70 1000 60 800 50 600 40 30 400 20 200 10 0 0 0 2 4 6 8 10 12 14 16 18 20 22 24 0 2 4 6 8 10 12 14 16 18 20 22 24 Number of Error Bits Number of Allowed Error Bits Figure 10: The Numbers of Error Bits and Correlation False Positive Rates of 9900 Pairs of Uncorrelated Skype VoIP Flows
• 9.
  6. RELATED WORKS applied to any peer-to-peer VoIP calls that are at least 90 There have been substantial research works on how to seconds long. trace attack packets with spoofed source address. Notably, Savage et al. [24] proposed IP traceback approach based on 8. REFERENCES probabilistic packet marking (PPM), and Snoeren et al. [30] [1] Anonymizer. URL. http://www.anonymizer.com proposed logging based IP traceback approach. While both [2] M. Arango, A. Dugan, I. Elliott, C. Huitema and S. approaches have been shown to be effective in tracing the Pickett. RFC 2705: Media Gateway Control Protocol real source of large number of packets with spoofed source (MGCP) Version 1.0. IETF, October 1999. address, they can not be used directly to trace VoIP flows. [3] A. Back, I. Goldberg, and A. Shostack. Freedom 2.1 Nevertheless, Savage’s work demonstrated the potentials of Security Issues and Analysis. Zero-Knowledge active approach in tracing IP packets. Systems, Inc. white paper, May 2001 There are a number of works [34, 35, 33, 7, 32, 5] on how to [4] S. A. Baset and H. Schulzrinne. An Analysis of the trace encrypted attack traffic through stepping stones based Skype Peer-to-Peer Internet Telephony Protocol. on the inter-packet timing characteristics. Except Wang and Columbia Technical Report CUCS-039-04, December Reeves’ work [32], all other timing based approaches are 2004 passive. As the timing characteristics of VoIP flows are not [5] A. Blum, D. Song, and S. Venkataraman. Detection of distinct enough, passive examination of existing inter-packet Interactive Stepping Stones: Algorithms and timing of VoIP flows won’t be able to distinguish different Confidence Bounds. In Proceedings of the 7th VoIP flows. Our proposed work differs from work [32] in International Symposium on Recent Advances in that it does not require packet buffering to achieve the even Intrusion Detection (RAID 2004). Springer, October time adjustment for embedding the watermark. 2004. A number of low-latency anonymizing systems have been [6] R. Dingledine, N. Mathewson and and P. Syverson. proposed to provide various levels of anonymity. Notably, Tor: The Second Generation Onion Router. In Onion Routing [13] and its second generation Tor [6] aim to Proceedings of the 13th USENIX Security Symposium, provide anonymous transport of TCP flows over the Inter- August 2000. net. ISDN mixes [21] proposed a technique to anonymize [7] D. L. Donoho, A. G. Flesia, U. Shankar, V. Paxson, J. the phone calls over the traditional PSTN. Tarzan [12] is Coit and S. Staniford. Multiscale Stepping Stone an anonymizing network layer based on peer-to-peer model. Detection: Detecting Pairs of Jittered Interactive Unlike most other anonymizing systems, Tarzan introduces Streams by Exploiting Maximum Tolerable Delay. In cover traffic in addition to encrypting and relaying the nor- Proceedings of the 5th International Symposium on mal traffic. Recent Advances in Intrusion Detection (RAID 2002): Felton and Schneider [10] identified a web caching exploit- LNCS-2516, pages 17–35. Springer, October 2002. ing technique that would allow malicious web site to infer [8] FBI. Letter to FCC whether its visitors have visited some other web pages, even if the browsing is protected by anonymizing services. Mur- http://www.askcalea.com/docs/20040128.jper.letter.pdf doch et al. [20] have recently investigated timing based at- [9] Federal Communications Commission. Notice of tack on Tor with the assumption that the attacker controls a Proposed Rulemaking (NPRM) and Declaratory corrupt Tor node. Levine et al. [18] investigated passive tim- Ruling RM-10865, ET Docket No. 04–295, FCC ing based attack on low-latency anonymizing systems with 04–187. In Federal Register at 69 Fed. Reg. 56956, the assumption that the attacker controls both the first and August, 2004. the last mix in the anonymizing network. However, none of [10] E. W. Felton and M. A. Schneider. Timing Attacks on these timing based approaches can be directly used to track Web Privacy. In Proceedings of the 7th ACM VoIP calls. Conference on Computer and Communications Security (CCS 2000), pages 25–32. ACM, November 2000. 7. CONCLUSIONS [11] Findnot. URL. http://www.findnot.com Tracking encrypted, peer-to-peer VoIP calls has been widely [12] M. J. Freedman and R. Morris. Tarzan: A viewed as impossible, especially when the VoIP calls are Peer-to-Peer Anonymizing Network Layer. In anonymized by the low latency anonymizing system. The Proceedings of the 9th ACM Conference on Computer key contribution of our work is that it demonstrates (1) and Communications Security (CCS 2002), pages tracking anonymous, peer-to-peer VoIP calls on the Inter- 193–206. ACM, November 2003. net is feasible; and (2) low latency anonymizing system is [13] D. Goldschlag, M. Reed and P. Syverson. Onion susceptible to timing based attack. Routing for Anonymous and Private Internet Our technique for tracking anonymous, peer-to-peer VoIP Connections In Communications of ACM, volume calls is based on subtle and deliberate manipulation of the 42(2), Febrary 1999. inter-packet timing of selected packets of the VoIP flow. Our [14] M. T. Goodrich. Efficient Packet Marking for experiments of the real-time peer-to-peer VoIP calls over a Large-scale IP Traceback. In Proceedings of the 9th commercially deployed anonymizing system show that the ACM Conference on Computer and Communications encrypted and anonymized VoIP flow could be made highly Security (CCS 2002), pages 117–126. ACM, October unique with only 3ms timing adjustment on selected packets. 2002. This level of timing adjustment is well within the range of [15] ITU-T Recommendation H.323v.4 Packet-based normal network delay jitters. Our results also show that Multimedia Communications Systems. November our watermark based tracking technique can be effectively 2000.
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  [16] Kazaa. URL.http://www.kazaa.com/ [32] X. Wang and D. Reeves. Robust Correlation of [17] T. Kohno, A. Broido and K. Claffy. Remote Physical Encrypted Attack Traffic Through Stepping Stones by Device Fingerprinting. In Proceedings of the 2005 Manipulation of Interpacket Delays. In Proceedings of IEEE Symposium on Security and Privacy, IEEE, the 10th ACM Conference on Computer and 2005. Communications Security (CCS 2003), pages 20–29. [18] B. Levine, M. Reiter, C. Wang, and M. Wright. ACM, October 2003. Timing Attacks in Low-Latency Mix Systems. In [33] X. Wang, D. Reeves, and S. Wu. Inter-packet Delay Proceedings of Financial Cryptography: 8th Based Correlation for Tracing Encrypted Connections International Conference (FC 2004): LNCS-3110, Through Stepping Stones. In Proceedings of the 7th 2004. European Symposium on Research in Computer [19] J. Li, M. Sung, J. Xu and L. Li. Large Scale IP Security (ESORICS 2002), LNCS-2502, pages Traceback in High-Speed Internet: Practical 244–263. Springer-Verlag, October 2002. Techniques and Theoretical Foundation. In [34] K. Yoda and H. Etoh. Finding a Connection Chain for Proceedings of the 2004 IEEE Symposium on Security Tracing Intruders. In Proceedings of the 6th European and Privacy, IEEE, 2004. Symposium on Research in Computer Security [20] S. J. Murdoch and G. Danezis. Low-Cost Traffic (ESORICS 2000), LNCS-1895, pages 191–205. Analysis of Tor. In Proceedings of the 2005 IEEE Springer-Verlag, October 2002. Symposium on Security and Privacy, IEEE, 2005. [35] Y. Zhang and V. Paxson. Detecting Stepping Stones. [21] A. Pfitzmann, B. Pfitzmann and M. Waidner. In Proceedings of the 9th USENIX Security ISDN-MIXes” Untraceable Communication with Symposium, pages 171–184. USENIX, 2000. Small Bandwidth Overhead. In Proceedings of GI/ITG Conference: Communication in Distributed Systems, Mannheim, Informatik-Fachberichte 267, pages APPENDIX 451–463, Springer-Verlag, 1991. Let Di (i = 1, . . . , n) represent the random delays added [22] J. Rosenberg, H. Schulzrinne, G. Camarillo, A. R. to packet Pi by the adversary, let D > 0 be the maximum 2 Johnston, J. Peterson, R. Sparks, M. Handley, and E. delay the adversary could add to any packet, and let σd Schooler. RFC 3261: SIP: Session Initiation Protocol. be the variance of all delays added to all packets. Here IETF, June 2002. we make no assumption about the distribution of random [23] RTAI. URL. http://www.rtai.org delay the adversary could add to each packet except that the [24] S. Savage, D. Wetherall, A. Karlin, and T. Anderson. delay is bounded. For example, Di and Dj (i = j) could be Practical Network Support for IP Traceback. In correlated to each other and/or have different distributions. Proceedings of ACM SIGCOMM 2000, pages 295–306. This models all the possible bounded random delays the ACM, September 2000. adversary could add to a packet flow. [25] H. Schulzrinne. Internet Telephony. In Practical Given the assumption that the adversary does not know Handbook of Internet Computing, CRC, 2004 how and which packets are selected by the information hider, the selection of information embedding packet Pzk (k = [26] H. Schulzrinne and J. Rosenberg. A Comparison of 1, . . . , 2r) is independent from any random delay Di the ad- SIP and H.323 for Internet Telephony. In Proceedings versary could add. Therefore, the impact of the random de- of International Workshop on Network and Operating lays by the adversary over randomly selected Pzk is equiva- System Support for Digital Audio and Video lent to randomly choosing one from the random variable list: (NOSSDAV 1998), pages 83–86, Cambridge, England, D1 , . . . , Dn . Let bk (k = 1, . . . , 2r) represent the impact of July 1998. the random delays by the adversary over the k-th randomly [27] H. Schulzrinne and J. Rosenberg. Signaling for selected packet Pzk . Apparently the distribution of bk is a Internet Telephony. In Proceedings of The 6th IEEE compound one that depends on the probability that each Di International Conference on Network Protocols would be selected. Since each Pzk is randomly selected ac- (ICNP’98), October 1998. cording to the same probability distribution over P1 , . . . , Pn , [28] Skype - the Global Internet Telephony Company. each bk has the same compound distribution. Furthermore, URL. http://www.skype.org because each Pzk is selected independently, bk is also inde- [29] S. Snapp, J. Brentano, G. V. Dias, T. L. Goan, L. T. pendent from each other. In other words, the impact of any Heberlein, C. Ho, K. N. Levitt, B. Mukherjee, S. E. random delays by the adversary over those independently Smaha1, T. Grance, D. M. Teal, and D. Mansur. and randomly selected information bearing packets is inde- DIDS (Distributed Intrusion Detection System) - pendent and identically distributed (iid ), and it is essentially Motivation, Architecture, and Early Prototype. In an iid random sample from the random delays the adversary Proceedings of the 14th National Computer Security added to all packets. Conference, pages 167–176, 1991. Let x1,k and x2,k be the random variables that denote [30] A. Snoeren, C. Patridge, L. A. Sanchez, C. E. Jones, the random impact over ipd1,k,d and ipd2,k,d respectively. F. Tchakountio, S. T. Kent, and W. T. Strayer. Apparently both x1,k and x2,k are iid. It is also easy to Hash-based IP Traceback. In Proceedings of ACM see that x1,k , x2,k ∈ [−D, D], E(x1,k ) = E(x2,k ) = 0, and SIGCOMM 2001, pages 3–14. ACM, September 2001. 2 Var(x1,k ) = Var(x2,k ) = 2σd . Let Xk = (x1,k − x2,k )/2, 2 [31] S. Staniford-Chen and L. Heberlein. Holding Intruders then Xk is iid, E(Xk ) = 0, and Var(Xk ) = σd . Accountable on the Internet. In Proceedings of the Let Yk,d be the random variable that denotes the resulting 1995 IEEE Symposium on Security and Privacy, pages value of Yk,d after it is perturbed by x1,k and x2,k , then we 39–49. IEEE, 1995. have
• 11.
  By applying theCentral Limit Theorem to random sample 2 Y1,d , . . . , Yr,d , where E(Yk,d ) = 0, and Var(Yk,d ) = σY,d + Yk,d = [(ipd1,k,d + x1,k ) − (ipd2,k,d + x2,k )]/2 2 σd + 2Cor(Yk,d , Xk )σY,d σd , we have = (ipd1,k,d − ipd2,k,d )/2 + (x1,k − x2,k )/2 = Yk,d + Xk (A-1) √ √ r(Yr,d − E(Yk,d )) rYr,d Pr[ < x] = Pr[ < x] Therefore, E(Yk,d ) = 0. Since Yk,d is iid and Xk is iid, Var(Yk,d ) Var(Yk,d ) Yk,d is also iid. = Φ(x) (A-4) Var(Yk,d ) = Var(Yk,d ) + Var(Xk ) + 2Cov(Yk,d , Xk ) Therefore 2 2 √ √ = σY,d + σd + 2Cor(Yk,d , Xk )σY,d σd rYr,d a r 2 2 Pr[Yr,d < a] = Pr[ < ] ≤ σY,d + σd + 2σY,d σd (A-2) Var(Yk,d ) Var(Yk,d ) = (σY,d + σd )2 √ a r ≈ Φ( ) (A-5) Let Yr,d be the random variable that denotes the resulting Var(Yk,d ) value of Yr,d after it is perturbed by x1,k and x2,k , then we √ have a r = Φ( ) 2 2 1 r σY,d + σd + 2Cor(Yk,d , Xk )σY,d σd Yr,d = Yr,d (A-3) √ r a r k = 1 ≥ Φ( ) σY,d + σd According to the property of variance of independent ran- dom variables, Var(Yr,d ) = Var(Yk,d )/r. It is also easy to see that E(Yr,d ) = 0.