Attack-Resilient Time Synchronization for Wireless Sensor Networks

Transcription

1 ack-resilien Time Synchronizaion for Wireless Sensor Neworks Hui Song, Sencun Zhu, and Guohong Cao Deparmen of Compuer Science & Engineering The Pennsylvania Sae Universiy Universiy Park, P {hsong,szhu,gcao}@cse.psu.edu srac The exising ime synchronizaion schemes in sensor neworks were no designed wih securiy in mind, hus leaving hem vulnerale o securiy aacks. In his paper, we firs idenify various aacks ha are effecive o several represenaive ime synchronizaion schemes, and hen focus on a specific ype of aack called delay aack, which canno e addressed y crypographic echniques. Nex we propose wo approaches o deec and accommodae he delay aack. Our firs approach uses he generalized exreme sudenized deviae (GESD) algorihm o deec muliple ouliers inroduced y he compromised nodes; our second approach uses a hreshold derived using a ime ransformaion echnique o filer ou he ouliers. Finally we show he effeciveness of hese wo schemes hrough exensive simulaions. I. INTRODUCTION Many sensor nework applicaions require ime o e synchronized wihin he nework. Examples of such applicaions include moile ojec racking, daa aggregaion, TDM radio scheduling, message ordering, o name a few. Consider he applicaion of moile ojec racking [1], in which a sensor nework is deployed in an area of ineres o monior passing ojecs. When an ojec appears, he deecing nodes record he deecing locaion and he deecing ime. Laer, hese locaion and ime informaion are sen o he aggregaion node which esimaes he moving rajecory of he ojec. Wihou an accurae ime synchronizaion, he esimaed rajecory of he racked ojec could differ grealy from he acual one. Similarly, we can see he imporance of ime synchronizaion for he operaions of oher sensor nework applicaions. ll nework ime synchronizaion mehods rely on some sor of message exchanges eween nodes. Nondeerminism in he nework dynamics such as physical channel access ime or operaing sysem overhead (e.g., sysem calls), makes he synchronizaion ask challenging in sensor neworks. In he lieraure, many schemes have een proposed o address he ime synchronizaion prolem [2], [3], [4], [5], [6]. These schemes involve he exchange of muliple ime synchronizaion messages among muliple sensor nodes [2] or eween wo sensor nodes [3] o e synchronized. However, none of hem was designed wih securiy in mind, even hough securiy has een idenified as a major challenge for sensor neworks [7]. cually, even if an adversary is capale of desroying some or all sensor nodes, i may op for oher more severe aacks, since i is more dangerous o ake acions ased on some false sensor daa han wihou any daa. For example, if an adversary can aack he ime synchronizaion proocol so ha he esimaed direcion of a moile ojec is conrary o is acual direcion, a wrong or even risky acion may e aken and many sysem resources may e wased. Thus, when a sensor nework is deployed in an adversarial environmen such as a alefield, he ime synchronizaion proocol is an aracive arge o he adversaries. In his paper, we firs idenify several securiy aacks an adversary can launch agains a non-secure ime synchronizaion proocol. For insance, an aacker can replay old synchronizaion messages, drop, modify, or even forge exchanged iming messages. Since many of hese aacks can e addressed y employing appropriae crypographic echniques, we focus on a specific ype of aack called delay aack, which canno e addressed y he crypographic echniques. In he delay aack, a malicious aacker (or a compromised node) delieraely delays he ransmission of ime synchronizaion messages o magnify he offse eween he ime of a malicious node and he acual ime. ll he curren ime synchronizaion schemes [2], [3], [4], [5], [6] are vulnerale o his aack in one way or anoher. We propose wo approaches o deec and accommodae he delay aacks. Our firs approach uses he generalized exreme sudenized deviae (GESD) algorihm o deec he ouliers inroduced y malicious nodes. If here is no malicious node, he ime offses among he sensor nodes should follow he same (or similar) disriuion or paern. For heir aacks o e effecive, malicious nodes ypically repor heir ime offses much larger han hose from he enign nodes, leaving heir repored values suspicious. Our second approach uses a ime ransformaion echnique, which enales every node o derive an upper ound of he ime offse ha is accepale o i, herey filering ou he ouliers. We discuss he meris as well as he limiaions of each approach, and evaluae he effeciveness of hese wo schemes hrough exensive simulaions. The res of he paper is organized as follows. The nex secion descries he relaed work and discusses various aacks which are addressale using crypographic echniques. In Secion III, we idenify and discuss a new aack called delay aack. Secion IV presens he sysem model and assumpions. In Secion V, we presen he GESD-ased approach. Secion

2 VI presens he hreshold-ased approach. The performance of hese wo approaches are evaluaed in Secion VII. Secion VIII concludes he paper. II. RELTED WORK. Time Synchronizaion in Hosile Environmens ll of he curren ime synchronizaion proocols [2], [3], [4], [5], [6] ecome vulnerale in hosile environmens. Taking he RBS scheme as an example, an aacker may launch differen kinds of aacks o reak he proocol. The firs aack is called masquerade aack. Suppose node sends ou a reference eacon o is wo neighors B and C. n aacker E can preend o e B and exchange wrong ime informaion wih C, disruping he ime synchronizaion process eween B and C. second aack is called replay aack. Using he same scenario in he firs aack, an aacker E can replay B s old iming packes, misleading C o e synchronized o a wrong ime. hird aack is called message manipulaion aack. In his aack, an aacker may drop, modify, or even forge he exchanged iming messages o inerrup he ime synchronizaion process. For he message dropping aack, he aacker can selecively drop he packes o prolong he converging ime of he synchronizaion process. This aack could e difficul o deec. For he message forging aack, he aacker can forge many reference eacon messages and flood he nework. On one hand, i reaks ime synchronizaion among he neighors. On he oher hand, i causes hose nodes o consume power o process hese unwaned and faked iming messages. If some of he nodes are power-deprived, some holes or even pariion may appear in he nework. We can cerainly employ some crypographic echniques o address he aforemenioned aacks. For example, providing auhenicaion of every exchanged message will preven an ouside aacker from impersonaing oher nodes or alering he conen of an exchanged message. dding a sequence numer o eacon messages or oher messages will preven message replay aacks. Message dropping may e noiced y some misehavior deecion schemes [8]. B. Faul-Tolerance Time Synchronizaion The ime synchronizaion prolem has een sudied for many years and mos of he previously proposed approaches fall ino he general field of faul-olerance ime synchronizaion [9], [1], [11], [12]. Our proposed schemes differ from hese schemes in several ways. Firs, in [1], [11], [12], i was assumed ha wo nonfauly clocks never differ y more han a predefined hreshold δ. However, how o define his hreshold is no discussed. In our second scheme, we use he ime ransformaion echnique o derive he hreshold. Our firs scheme do no have his assumpion a all. Second, he scheme of [9] requires an auhenicaion mechanism such as digial signaures o ensure ha no oher node can generae he same message or aler he message wihou deecion. Our schemes do no have his requiremen. In fac, our schemes are addressing a new aack, called delay aack, which can no e prevened or handled y crypographic echniques such as digial signaures, ecause we assume ha nodes may e compromised. III. THE DELY TTCK MODEL The ime synchronizaion schemes proposed for wireless sensor neworks are ased on wo models: he receiver-receiver model and he sender-receiver model. The reference roadcas synchronizaion scheme (RBS) [2] and is prooype proocol [13] fall ino he receiver-receiver model. In he following, we simply use he RBS scheme o represen he receiver-receiver model. Schemes of he sender-receiver model include TPSN [3], LTS [4], he iny-sync and mini-sync schemes [5], and he gloal ime synchronizaion proocol [6]. In he following, we will descrie he delay aack model in he conex of he RBS scheme [2], which is ased on he following idea: using a hird pary for ime synchronizaion. node, which is a regular node acing as a reference node, roadcass a reference eacon o is neighors. Each neighoring node records he arrival ime of he eacon ased on is own clock. Since hese receiving nodes are close o he reference node, we can assume he eacon arrives a oh receivers a he same ime. Therefore, he difference eween he recording imes of hese receiving nodes is he ime offse eween hem. By exchanging heir recorded receiving imes, hey can calculae he ime offse, adjus and synchronize heir clocks. s shown in Figure 1(a), nodes and B have he recorded imes a and, respecively, and he ime offse eween hem is δ = a. To synchronize wih node, node B may increase is clock y δ, or oh of hem se heir clocks o ( a + )/2. Nex we inroduce a new aack model agains he RBS scheme. Definiion 1 (Delay ack): In a delay aack, an aacker delieraely delays some of he ime messages, e.g., he eacon message in he RBS scheme, so as o fail he ime synchronizaion process. Figure 1() and (c) show wo ways o launch he delay aack in he RBS scheme. In Figure 1(), wo colluding nodes ac as he reference node for nodes and B. They send he reference eacon o nodes and B a differen imes. s a resul, nodes and B receive he eacon messages a differen imes, u hey assume hey receive he eacon a he same ime. Figure 1(c) shows ha a malicious node can launch he aove aacks alone if i has a direced anenna [14] so ha nodes and B only hear one eacon message. The delay aack can also e launched when a enign node is synchronizing wih a compromised node. The compromised node can add some delay o he eacon receiving ime and send i he good node. This will mislead he good node o synchronize o a wrong ime. The sender-receiver model proocols [3], [4], [5], [6] are also vulnerale o he delay aack. In he sender-receiver model, he sender and he receiver exchange ime synchronizaion packes, esimae he round-rip ransmission ime eween hem, and synchronize heir clocks afer finding he clock offse eween hem. Since only wo nodes are involved in he process, his model does no suffer from he aacks

3 reference node R eacon eacon a M B ck malicious node Compromised Reference node R acker +e B Compromised Reference node R (a) The RBS scheme () Collusion-ased delay aack (c) Direcional anenna-ased delay aack Fig. 1. The RBS scheme and he delay aack +e B inroduced y a malicious reference node. However, a node can e deceived if he node i is synchronizing wih is malicious. Therefore, hese schemes are also sujec o he aforemenioned delay aacks. IV. SYSTEM MODEL ND SSUMPTIONS. Node, Nework, and Securiy ssumpions We consider a sensor nework composing of resourceconsrained sensor nodes such as he curren generaion of Berkeley Mica moes [15]. Every sensor node is equipped wih an oscillaor assised clock and powered y an exernal aery. The clock of a sensor sars o ick only afer i is powered on. Since i is unlikely o power on all he sensor nodes a he same ime, here may e large ime offses among sensor nodes iniially. We assume ha he sensor nodes deployed in a securiy criical environmen is manufacured o susain possile reak-in aacks a leas for a shor ime inerval (say several seconds) when capured y an adversary [16]; oherwise, he adversary could easily compromise all he sensor nodes and hen ake over he nework. To his end, we assume ha here exiss a lower ound on he ime inerval T min ha is necessary for an adversary o compromise a sensor node. We assume ha he firs ime synchronizaion will e execued and finished wihin he ime inerval T min. s a resul, we can assume ha all he sensor nodes are loosely synchronized. Because of inrinsic clock drifs of sensor nodes, he ime offses among sensor nodes could ecome very large (e.g., in he order of seconds or even larger) unless ime synchronizaion is performed once in a while. Hence, we assume ha ime synchronizaion is performed periodically. Each node is assigned a unique id efore deploymen and i can auhenicae he messages sen/received wih appropriae shared keys esalished hrough a key managemen proocol [16], [17], [18]. This ensures ha no node can impersonae ohers during he exchange of iming messages and a malicious node can ac as a reference a mos once. Noe ha he presence of jam-and-replay aackers can incur exra delay o any well-ehaving node s ransmission in is neighorhood. s a resul, a well-ehaving node may e misidenified as compromised. In his paper, however, we assume ha we can uilize jamming aack deecion schemes, such as [19], o deec and remove he jam-and-replay aackers. B. Models for Secure Time Synchronizaion R3 R2 R4 R1 delay aack i a... i B Ri Rn delay aack Ri+1 (a) Two-node model Fig Rn 1 R3 2 R2 3 R4 dela2 2 dela dela4 4 dela1 4 R1 R5 n dela5 n dela(n) dela(i)... n 1 dela(n 1) i Rn dela(i+1) Ri n 1 Rn 1... Ri+1 () Neighoring-node model Two models for secure ime synchronizaion The general idea of defending agains delay aacks is as follows. fer collecing a se of ime offses from muliple involved nodes, we idenify he malicious ime offses ha are due o delay aacks. The idenified malicious ime offses will e excluded and he res of he ime offses are used o esimae he acual ime offse. Nex, we presen wo models for collecing he ime offses: he wo-node model and he neighoring-node model, which are descried in he conex of he RBS scheme. The wo-node model: In his model, one node needs o synchronize wih anoher node. For example, in Figure 2(a), node B is he cluser head and is a node wihin he cluser. ll nodes in he cluser are required o synchronize wih B. Due o securiy concerns, node only russ he cluser head u no oher nodes in he cluser. However, i has o use oher nodes as reference nodes when using RBS. To deal wih securiy aacks on ime synchronizaion, node uses muliple reference nodes o oain a se of ime offses. For example, i can reques R 1,R 2,... R n o serve as reference nodes. Le i a, i represen he wo eacon receiving imes oained y using a reference node R i and δ i = ( i a i ) e he ime offse eween and B. Node B oains n ime offses {δ 1,δ 2,...,δ n }. Based on he colleced ime offses, we can deec and exclude he malicious ime offses and esimae he acual ime offse eween and B more accuraely. The neighoring-node model: In some applicaions, a node may e required o synchronize wih is neighors o cooperae wih each oher. In his case, he wo-node model is no i

4 enough since some neighors may have een compromised and synchronizing wih a malicious node is more vulnerale o aacks. Our soluion is illusraed in Figure 2(). Suppose has n neighors: R 1, R 2,..., R n. We run he RBS scheme eween and each of is neighors and each ime we use a differen node as reference o oain a ime offse. fer collecing n ime offses, we can deec he ouliers, exclude hem, and make a good esimaion on he acual ime offses. In addiion o he aove wo models, oher models are possile. These models have one hing in common: hey collec a se of ime offses, which may include malicious ime offses. The focus of his paper is o answer he following quesion: Given a se of ime offses, how o idenify he ouliers and how o achieve an aack-resilien esimaion? In his paper, we propose soluions in he conex of RBS, alhough he soluions can also e applied o he sender-receiver ased model. V. THE GESD-BSED DELY TTCK DETECTION Inuiively, wihou delay aacks, he ime offses among nodes follow a similar disriuion. The exisence of delay aacks makes he malicious ime offses much differen from he ohers; oherwise, he aack is no effecive and can e oleraed y he ime synchronizaion schemes. In saisics, hese malicious ime offses are referred o as ouliers, which is defined as an oservaion which deviaes so much from oher oservaions as o arouse suspicious ha i was generaed y a differen mechanism [2]. Numerous schemes have een proposed o deec ouliers [21] (see [21] for a survey). mong hem, he generalized exreme sudenized deviae many-oulier procedure (GESD) [22] is proved o perform well under differen condiions [21]. In he following, we inroduce GESD and discuss how o apply i o our prolem. fer he ouliers have een idenified y GESD, we discuss how o exclude he ouliers and oain a more accurae esimaion of he ime offse.. The GESD Many-Oulier Deecion Procedure Before inroducing GESD, le us firs look a he exreme sudenized deviae (ESD) es which is also called he Gru s es. The ESD es is good a deecing one oulier in a random normal sample. Definiion 2 (ESD Tes): Given a daa se Γ = {x 1,x 2,...,x n }, The mean of Γ is denoed as x and he sandard deviaion of Γ is denoed as s. Le T i = x i x /s, where i = 1,...,n. T i is also called he corresponding T -value of x i. Le x j e he oservaion ha leads o he larges x i x /s, where i = 1,...,n. Then x j is an oulier when T j exceeds a aled criical value λ. In principle, if T j does no exceed he criical value λ, we need no single ou x j. ssuming his es finds an oulier, we hen look for furher ouliers y removing oservaion x j and repeaing he process on he remaining n 1 oservaions. However, he ESD es can only deec one oulier. GESD is a modified version of he ESD es, which can find muliple ouliers. Two criical parameers for GESD are r and λ i, where r is he esimaed numer of ouliers in he daa se and λ i is he wo-sided 1 α percen criical value go from Formula (1). λ i = n i 1,p (n i) (n i n i 1,p )(n i + 1) (1) In Formula (1), i = 1,...,r. v,p is he 1 p percenage poin from he disriuion wih v degrees of freedom, and p = 1 [α/2(n i+1)]. Given α,n and r, he criical values λ i, where i = 1,...,r, can e calculaed eforehand. B. Using GESD for Delay ack Deecion The GESD-ased approach is formally defined as follows. Definiion 3 (GESD-ased delay aack deecion): Given he ime offse se Γ = {δ 1,δ 2,...,δ n }, all he ime offses δ i ha are idenified as ouliers y GESD are claimed o e under delay aack. In GESD, r is he numer of esimaed ouliers in he daa se, which is he esimaed numer of malicious ime offses in our seings. The choice of r plays an imporan role in GESD. If r is se o a small numer and here are more han r malicious ime offses among he n ime offses, some of hem canno e deeced using GESD. On he oher hand, if r is oo large, i wases ime on checking he nodes ha are in fac enign (good) ones. In his paper, since he numer of ime offses is small (e.g., 2), we se r o e half of he oal numer of ime offses. We also assume ha he numer of malicious ime offses is less han half of he oal numer of ime offses. Wihou his assumpion, GESD may no work since i may find he malicious ime offses o e enign and he enign ones o e malicious. Definiion 4 (Esimae r): Le he median of he ime offse se Γ e x and s e he sandard deviaion. r is defined as he numer of ime offses x j such ha x j x /s > 2, where i = 1,...,n. When he numer of malicious nodes is small, i.e, less han 5% of he oal, we can uilize he median of he ime offses o se r. s shown in Definiion 4, r is he numer of ime offses ha are wo sandard deviaions away from he median. In mos cases, he daa and ime offses are normally disriued, and 95% of he values are a mos wo sandard deviaions away from he mean. In our case, we replace he mean wih he median since he median serves eer when here exiss malicious daa ses. Figure 3 shows how o use GESD o idenify ouliers. The algorihm acceps hree parameers: he esimaed numer of ouliers r, he ime offse daa se Γ, and he criical value λ compued y Formula (1). λ can e pre-compued and sored in he sensors. In he following, we use λ n o denoe he criical values for a daa se wih n elemens. Two array srucures C and T, are used o save he candidae oulier informaion. C is used o keep he ouliers and T is used o save he T value (Definiion 2) corresponding o he candidae ouliers. The T

5 lgorihm 1: Inpu: r, Γ, λ le j = 1, C and T e wo arrays 1 egin loop 2 calculae x and s over se Γ; find x kj which maximizes x i x, x i Γ; 3 le T[j] = { x kj x /s}, C[j] = x kj ; remove x kj from Γ; 4 increase j; decrease r; 5 if (r < 1) reak 6 end loop 7 le oulier se Ω =, j = r; 8 egin loop 9 if (T[j] > λ n [j]) {Ω = {C[k]}, k = 1,..., j; reurn Ω} 1 else {decrease j; if (j < 1) reurn } 11 end loop Fig. 3. Idenifying ouliers wih GESD values of he candidae ouliers are laer used o compare wih he criical values o decide wheher he candidaes are ouliers or no. C. Delay ack ccommodaion The goal of securing ime synchronizaion is o synchronize he ime in he presence of delay aacks. This can e achieved y firs idenifying he ouliers (malicious ime offses) and hen excluding hem when esimaing he rue ime offses eween nodes. We use he mean of he enign ime offses o approximae he rue ime offses. The following definiion can e used o approximae he ime offse esimaion ˆδ. Definiion 5 (Esimae ˆδ): Le Γ e he ime offse daa se and Ω e he oulier se. Then he enign ime offse se is Γ Ω. ˆδ is defined as he mean of he se Γ Ω. Le he size of Γ e n and he size of Ω e k. ˆδ is calculaed as follows. n k ˆδ = i=1 x i n k,where x i Γ Ω. VI. THRESHOLD-BSED DELY TTCK DETECTION One drawack of he GESD approach is ha i needs o have enough reference nodes o deec he malicious nodes effecively. This has een verified y he simulaion resuls shown in Secion VII-B. In his secion, we propose a hreshold-ased approach o deec he delay aacks ased on he following oservaions. Wihou delay aacks, he ime offse eween wo nodes should e ounded y a hreshold value if he maximum clock drif raes can e ounded. Wih he hreshold value, we can idenify hose ime offses ha are larger han he hreshold as malicious ones. Differen from GESD, he hreshold-ased approach does no need ha many reference nodes. Moreover, he hreshold-ased approach only needs o calculae he hreshold once, and hus has less overhead. In he following, we firs presen he ime ransformaion echnique, which was firs proposed in [23]. Then, ased on he ime ransformaion echnique, we presen a mehod o deermine he hreshold. fer deermining he hreshold, we discuss how o use i o defend agains delay aacks.. The Time Transformaion Technique Before presening he ime ransformaion echnique, le us firs look a he hardware oscillaor assised clock in Berkeley Mica moes [15], which implemens an approximaion C(T) of he acual ime T. C(T) = k T T ω(η)d η + C(T ) is a funcion of he real ime T, which derives from he angular frequency ω(t) of he hardware oscillaor. In his formula, k is a proporional coefficien and T is he iniial clock value. For a perfec hardware clock, dc d T is equal o one. However, all hardware clocks are no perfec since hey are sujec o clock drif. We can only assume ha he clock drif rae of he sensor clock does no exceed a maximum value of ρ. Thus, we have he following inequaliy: 1 ρ dc d T 1 + ρ. The idea of ime ransformaion is o ransform he real ime difference T ino he sensor clock difference C and vice versa. These ransformaions are difficul ecause of he unpredicailiy of he sensor clock, u here exiss some lower and upper ounds on he esimaes. Based on he previous inequaliy, we can ge: 1 ρ C T 1 + ρ. This inequaliy can e ransformed ino (1 ρ) T C (1 + ρ) T and C 1+ρ T C 1 ρ, which means ha he clock difference C can e approximaed y he inerval [(1 ρ) T,(1 + ρ) T ]. On he oher hand, he real ime difference T ha corresponds o he sensor clock difference C can e approximaed y he inerval [ C 1+ρ, C 1 ρ ]. Node Node B eacon eacon a T Fig M 3 ck 4 2 T1 T2 Time ransformaion Time in node Time in node B True Time In order o ransform a ime difference C1 corresponding o one node N 1 wih ρ 1, o a ime corresponding o anoher node N 2 wih ρ 2, C1 is firs esimaed y he real ime inerval [ C 1 1+ρ 1, C 1 1 ρ 1 ], which in urn is esimaed y he sensor clock ime inerval [ 1 ρ2 1+ρ 1 C1, 1+ρ2 1 ρ 1 C1 ], relaive o he local ime of node N 2. s shown in Figure 4, nodes and B use RBS o do ime synchronizaion. The maximum clock drif raes of and B are denoed as ρ a and ρ, respecively. Suppose and B receive he reference eacon a ime a and, in erms of heir own local clocks, respecively. fer receiving he reference eacon, a ime 1, sends a message M o B, elling B ha i received he eacon a ime a. Message M is received y B a ime 3, and hen B sends ack an ck a ime 4 o confirm ha i has received M. In he ck, B piggyacks, 3, and 4. fer receiving he ck, can use he ime ransform echnique o ransform he eacon receiving ime o a ime inerval [ L, R ] relaive o s clock. L and R are calculaed using Formula 2.

6 L = 2 ( 4 ) 1+ρa 1 ρ (( 2 1 ) ( 4 3 ) 1 ρa 1+ρ ) R = 2 ( 4 ) 1 ρa 1+ρ (2) B. Deermining he hreshold ξ The hreshold ξ is he upper ound of he ime offses eween wo nodes. We deermine ξ ased on he idea of ime ransformaion shown aove. Differen from he original paper, where he ime inerval is used o order messages, we uilize he ime inerval o quanify he ime offse upper ound eween wo nodes. In addiion, unlike [23] where he ime ransformaion happens along muliple hops, we only need o do he ime ransformaion wihin a single hop. s a resul, he inerval we ge has less error accumulaion han ha in [23]. sraighforward soluion is o use ( R L ) as ξ. However, ( R L ) is a igh ound. If we use i o decide wheher a ime offse is malicious or no, i may idenify enign ime offses as malicious ones. Thus, o effecively deec malicious ime offses, ξ should e a looser upper ound. Since L and R are he wo oundaries of ime a node, max( a L, R a ) should e he upper ound of he ime offses eween and B. Based on his oservaion, he ime offse upper ound, ξ a, eween and B can e deermined y Formula (3), which is a looser upper ound compared o ( R L ). This can e explained as follows. If he clock drif raes of he wo nodes are equal, a should fall inside [ L, R ]; oherwise, a may fall ouside of [ L, R ], leading o a looser upper ound ased on Formula (3). Since he clock drif raes of wo nodes are usually no equal, Formula (3) gives a looser upper ound compared o ( R L ). R a if a < L ξ a = MX{ R a, a L } if a [ L, R ] (3) a L if a > R The ime offse upper ound eween wo neighoring nodes shown in Formula (3) is calculaed only in he firs ime synchronizaion, which happens shorly afer he deploymen of he sensor nework. Thus, he ime offse caused y he clock drif is small in Formula (3). The clock drif ime increases as ime goes y. If he ime synchronizaion inerval is long, he clock drif ime will e long and should e aken ino consideraion when deermining he ime offse upper ound. Formula (4) gives he ime offse upper ound eween nodes and B considering clock drif ime. a = ξ a + ρ a ρ T (4) In Formula (4), T is he ime synchronizaion inerval and a is he upper ound of he ime offse eween nodes and B when hey are synchronized using one reference node. To increase he accuracy of he esimaion, we use n reference nodes o oain a se of ξ a. The hreshold ξ is defined as he maximum among hem, as showed in Formula (5). { ξ = MX ξ a i } + ρ a ρ T, where 1 i n. (5) Wih hreshold ξ, we can deec malicious ime offses among a se of ime offses. The hreshold-ased approach is formally defined in Definiion 6. Definiion 6 (Threshold-ased delay aack deecion): Given he ime offse daa se Γ = {δ 1,δ 2,...,δ n }, all he ime offses igger han ξ are claimed o e under delay aack and are idenified as malicious ime offses. C. Delay ack ccommodaion fer he malicious ime offses have een deeced using he hreshold, we can use he same sraegy as ha in Secion V-C o exclude hem and oain a good esimaion on he rue ime offse eween wo nodes.. Simulaion seup VII. PERFORMNCE EVLUTIONS We evaluae he performance of he wo approaches using he RBS scheme y simulaion. In he simulaion, each node has a maximum clock drif rae a microsecond level (1 6 second) [23]. The deviaions of clock drif raes among nodes are also a microsecond level. To synchronize wo nodes, a numer of reference nodes are generaed varying from 1 o 2. Each reference node roadcass a reference eacon o he wo nodes, which record he eacon receiving imes according o heir clocks. The arrival imes of he reference eacons follow Poisson disriuion, and he eacon processing ime follows normal disriuion. Since he ypical message size is 36 yes in TinyOS [24], he eacon processing ime is aou 12 milliseconds which is he ime required o process a 36-ye packe. fer he eacon has een processed, one node sends he eacon receiving ime o he oher, which calculaes he ime offse eween hem. fer hese wo nodes ge a se of ime offses, we randomly pick some of hem as malicious ime offses and assume hey are under delay aacks. We add a delay aack ime which follows normal disriuion. Based on a se of ime offses, he proposed schemes are evaluaed wih differen levels of delay aack ime and differen numer of malicious ime offses. ll resuls are oained y seing he synchronizaion inerval o 5, seconds. The resuls are averaged over 1 runs. Mos of he simulaion parameers are lised in Tale I. Three merics are used o evaluae he effeciveness of he proposed schemes: he successful deecion rae, he false posiive rae, and he accuracy improving rae. In a nework wih delay aacks, he successful deecion rae ells he percenage of malicious ime offses ha can e successful deeced. The false posiive rae shows he percenage of ime offses ha are repored as ouliers u are acually no. The accuracy improving rae shows he accuracy improvemen on he esimaed ime offse afer he deeced ouliers have een

7 Numer of reference nodes 1 o 2 Numer of malicious nodes 1 o 5 Beacon processing ime mean 12 milliseconds Beacon arrival inerval mean 2 milliseconds Clock drif rae mean.5 millisecond Clock drif rae deviaion.1 millisecond Delay aack ime 1-1 milliseconds Synchronizaion inerval 5, seconds TBLE I SIMULTION PRMETERS excluded. Le ˆδ e he esimaed ime offse when he ouliers have een excluded and δ ad e he esimaed ime offse when he ouliers have no een excluded. The accuracy improving rae is defined in Formula (6). ccuracy improving rae = δ ad ˆδ 1% (6) ˆδ B. Simulaion Resuls of he GESD-ased pproach Success Rae (in %) NUM_REF= No. of malicious nodes (delay= 1 ms) (a) Fig. 5. Success Rae (in %) NUM_REF= No. of malicious nodes (delay= 1 ms) () The successful deecion rae of GESD 1) The Successful Deecion Rae: Figure 5 shows he successful deecion raes as he numer of malicious nodes and he numer of ime offses (NUM REF) change, considering differen delay aack imes (delay). We did no show he successful deecion rae when here are five malicious nodes and NUM REF is 1, ecause GESD does no work when he numer of malicious ime offses is equal or larger han ha of he enign nodes. Based on Figure 5, we can make he following oservaions. Firs, when he delay aack is 1ms, he successful deecion rae is low in mos cases. Since he ime synchronizaion inerval is 5, seconds, he clock drif ime eween wo nodes can e as large as 1ms. I is difficul o deec he delay aacks when he delay aack ime is no significanly larger han he clock drif ime, resuling in low successful deecion rae. Second, Figure 5(a) also shows ha he successful deecion rae increases as he numer of ime offses increase in general. Given a numer of malicious ime offses, we will have more enign ime offses wih a larger se of ime offses; and he more enign nodes we have, he higher he successful deecion rae is. Thus, when here are muliple ouliers, GESD is more effecive if more ime offses are availale. Third, as long as he delay aack ime is much larger han he clock drif during he synchronizaion inerval, he successful deecion rae increases dramaically. For example, as shown in Figure 5 (), he successful deecion rae reaches 1% when he delay aack is a 1ms level. s he delay aack ime is larger han he clock drif ime, he malicious ime offses can e easily idenified. lhough no shown in he figure, GESD keeps he 1% successful deecion rae when he he delay aack ime is larger han 1ms. 2) The False Posiive Rae: The simulaion resuls show ha he false posiive rae of GESD is almos zero in our sysem seings. This is ecause a enign ime offse will no e idenified as oulier when here exiss malicious nodes. Thus, GESD works well in erms of false posiive rae. ccuracy improving rae NUM_REF= No. of malicious nodes (delay= 1 ms) (a) Fig. 6. ccuracy improving rae NUM_REF= No. of malicious nodes (delay= 1 ms) () The accuracy improving rae of GESD 3) The ccuracy Improving Rae: Figure 6 shows he accuracy improving raes wih differen level of delay aacks. From he figure, we can see ha he accuracy improving rae is low when he delay aacks are a he level of 1ms. This is ecause he delay aack ime is relaively small compared o he clock drif ime during he 5,-second inerval. Thus, excluding he malicious ime offses canno have oo much improvemen. However, as he delay aack ime increases, excluding he malicious ime offses can significanly improve he accuracy improvemen rae. For example, when he delay aack ime is 1ms, he accuracy improving rae can e increased y as much as 16 imes (see Figure 6()). C. Simulaion Resuls of he Threshold-ased pproach Success Rae (in %) NUM_REF= No. of malicious nodes (delay= 1 ms) Fig. 7. (a) Success Rae (in %) NUM_REF= No. of malicious nodes (delay= 1 ms) () The successful deecion rae of he hreshold-ased approach 1) The Successful Deecion Rae: Figure 7 shows he successful deecion raes wih differen level of delay aacks when he synchronizaion inerval is 5,-second. s shown in Figure 7(a), when he delay aack ime is 1ms, he hreshold-ased scheme can achieve higher successful deecion rae (nearly 1% in all he cases) compared o GESD (Figure 5(a)). This shows ha he hreshold-ased approach is effecive even when he delay aack ime is small compared

8 o he clock drif rae. In he hreshold-ased approach, he hreshold reflecs oh he maximum ime offse ha wo nodes can have when here is no delay aack and he ime offse caused y clock drif during he synchronizaion inerval. Thus, even hough delay aack ime is no large compared o he clock drif ime, i can sill e deeced a a high rae. Similar o GESD, he hreshold-ased approach achieves a 1% successful deecion rae when he delay aack ime is 1ms. Figure 7 also shows ha he successful deecion rae does no change oo much as he numer of malicious ime offses increases. Differen from GESD, he hreshold is no affeced y he numer of malicious ime offses. In summary, he hreshold-ased approach can achieve a eer successful deecion rae han GESD. The hresholdased scheme performs well even when he delay aack ime is small compared o he clock drif ime and i is rous agains muliple delay aacks. 2) The False Posiive Rae: Simulaion resuls show ha he false posiive rae of he hreshold-ased approach is always zero in differen seings. This is ecause he hreshold is deermined in such a way ha no enign ime offses will e idenified as malicious. From he false posiive rae poin of view, oh he GESD approach and he hreshold-ased approach perform well. ccuracy improving rae NUM_REF= No. of malicious nodes (delay= 1 ms) Fig. 8. (a) ccuracy improving rae NUM_REF= No. of malicious nodes (delay= 1 ms) () The accuracy improving rae of he hreshold-ased approach 3) The ccuracy Improving Rae: Figure 8 shows he accuracy improving raes wih differen level of delay aacks. Compared o Figure 6, Figure 8 shows ha he accuracy improving rae achieved in he hreshold-ased approach is higher han ha of GESD. This can e explained y he fac ha he hreshold-ased approach can achieve a much higher successful deecion rae han GESD. s he delay aack ime increases, he improvemen on he accuracy also increases as shown in Figure 8(a) and (). In erms of he accuracy improving rae, he hreshold-ased approach performs eer han GESD, which is consisen wih he resuls of he successful deecion rae. VIII. CONCLUSIONS In his paper, we idenified various aacks ha are effecive o several represenaive ime synchronizaion schemes, and focused on dealing wih he delay aack. We proposed wo soluions o deec and accommodae he delay aacks. Our firs approach uses he generalized exreme sudenized deviae (GESD) algorihm o deec muliple ouliers inroduced y he compromised nodes and our second approach uses a hreshold derived using a ime ransformaion echnique o filer ou he ouliers. Exensive simulaion resuls show ha oh schemes are effecive in defending agains delay aacks. However, he GESD approach needs more reference nodes o effecively deec he malicious nodes. The hreshold ased approach relaxes his assumpion and ouperforms GESD in erms of successful deecion rae, false posiive rae, and accuracy improving rae. In he fuure, we will evaluae he overhead of collecing muliple ime offses in our schemes. We will also look ino schemes o reduce he overhead and make our scheme more efficien and pracical. CKNOWLEDGMENT This work was suppored in par y rmy Research Office (W911NF ) and he Naional Science Foundaion (CCR-9277, CNS , and CNS-51946). REFERENCES [1] W. Zhang and G. Cao, Opimizing Tree Reconfiguraion for Moile Targe Tracking in Sensor Neworks, IEEE INFOCOM, 24. [2] J. Elson, L. Girod, and D. Esrin, Fine-grained nework ime synchronizaion using reference roadcass, SIGOPS Oper. Sys. Rev., vol. 36, no. SI, pp , 22. [3] S. Ganeriwal, R. Kumar, and M. B. 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