A Traffic-Aware Key Management Architecture for Reducing Energy Consumption in Wireless Sensor Networks
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A Traffic-Aware Key Management Architecture for Reducing Energy Consumption in Wireless Sensor Networks

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In Wireless Sensor Networks (WSNs), most ...

In Wireless Sensor Networks (WSNs), most
of the existing key management schemes, establish shared
keys for all pairs of neighbor sensor nodes without
considering the communication between these nodes.
When the number of sensor nodes in WSNs is increased
then each sensor node is to be loaded with bulky amount
of keys. In WSNs a sensor node may communicate with a
small set of neighbor sensor nodes. Based on this fact, in
this paper, an energy efficient Traffic-Aware Key
Management (TKM) scheme is developed for WSNs,
which only establishes shared keys for active sensors
which participate in direct communication. The proposed
scheme offers an efficient Re-keying mechanism to
broadcast keys without the need for retransmission or
acknowledgements. Numerical results show that proposed
key management scheme achieves high connectivity. In
the simulation experiments, the proposed key
management scheme is applied for different routing
protocols. The performance evaluation shows that
proposed scheme gives stronger resilence, low energy
consumption and lesser end to end delay.

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    A Traffic-Aware Key Management Architecture for Reducing Energy Consumption in Wireless Sensor Networks A Traffic-Aware Key Management Architecture for Reducing Energy Consumption in Wireless Sensor Networks Document Transcript

    • ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010 A Traffic-Aware Key ManagementArchitecture for Reducing Energy Consumption in Wireless Sensor Networks C.Gnana Kousalya1, J. Raja2, and Dr.G.S.Anandha Mala3 1 Anna University, Chennai -25, India. Email: kousalyaphd@yahoo.com 2 SSN College of Engineering/IT, Tamil Nadu, India 3 St.Josephs College of Engineering/Computer Science and Engineering, Chennai, India Abstract— In Wireless Sensor Networks (WSNs), most In wireless sensor networks, a sensor node mayof the existing key management schemes, establish shared communicate with a small set of neighbor sensorkeys for all pairs of neighbor sensor nodes without nodes. Most of the existing key management schemes,considering the communication between these nodes. did not consider this communication between theseWhen the number of sensor nodes in WSNs is increasedthen each sensor node is to be loaded with bulky amount nodes. They establish shared keys for all pairs ofof keys. In WSNs a sensor node may communicate with a neighbor sensor nodes. When the number of sensorsmall set of neighbor sensor nodes. Based on this fact, in nodes in WSNs is increased, large number of keys is tothis paper, an energy efficient Traffic-Aware Key be loaded in each sensor node, which in turn causesManagement (TKM) scheme is developed for WSNs, more energy consumption. If any two close sensorwhich only establishes shared keys for active sensors nodes are rarely in the active-state the assignment ofwhich participate in direct communication. The proposed shared keys may be unnecessary, since they may bescheme offers an efficient Re-keying mechanism to hardly exploited.broadcast keys without the need for retransmission or In this paper, a Traffic-Aware Key Managementacknowledgements. Numerical results show that proposedkey management scheme achieves high connectivity. In (TKM) scheme is proposed for WSNs, which onlythe simulation experiments, the proposed key establishes shared keys for active sensor nodes whichmanagement scheme is applied for different routing participate in direct communication, based on theprotocols. The performance evaluation shows that topology information of the network. To inform aboutproposed scheme gives stronger resilence, low energy the state of a sensor node RTS/CTS control frames areconsumption and lesser end to end delay. modified from their original MAC. Proposed scheme reduces energy consumption with higherIndex Terms—Wireless sensor Network, Key connectivity and stronger resilience against nodemanagement, Key Pre-distribution, Re-keying capture. The paper is organized as follows. Section 2 gives I. INTRODUCTION brief literature review on various key management The utilization of wireless sensor networks a tool for schemes for WSN. Section 3 describes proposed keydata aggregation and data processing has become pre-distribution scheme. Section 4 gives theincreasingly efficient and popular. These tools aid in performance evaluation in terms of numerical andthe monitoring of customary activities, environmental simulation results. Section 5 concludes the paper.conditions and more besides aiding in cost effectiveadministration of remote and hazardous locations. II. RELATED WORKClose interaction of WSNs with their physical Various key management schemes for WSNs areenvironment and unattended deployement of sensor proposed for past few years. Wenliang Du et al.nodes in hostile environment make WSNs highly [2004] proposed key management using deployementvulnerable to attacks. Imparting security in wireless knowledge. Alan price et al. [2004] proposedsensor networks is considered to be a tedious task. authentication and key distribution in one set of WSNs is built with a large number of small battery protocols .For Distributed Sensor Network (DSN) anpowered device with limited energy, memory, alternative of random key pre-distribution scheme hascomputation and communication capabilities. Due to been proposed by Siu-Ping Chan et al. [2005].Ruithis insufficient resources in WSNs, Key management Miguel Soares Silva et al.[2006] proposed a scheme toapproaches used in Ad-Hoc and other wireless network overcome the disadvantages of the real symmetricalcannot be applied to WSNs. From literature it is found based systems using properties of chaotic systems.that reasonable and accepted solution for key Grid-group deployment scheme has been proposed bymanagement in WSNs is to distribute randomly Dijiang Huang et al. [2004]. “PKM", an in-situ keygenerated keys to each sensor node. 51© 2010 ACEEEDOI: 01.ijns.01.02.10
    • ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010management protocol for sensor networks was the network, increase end-to-end latency, etc.proposed by F. Cheng et al. [2005].Jaemin Park et al. B. Selective Forwarding[2005] proposed random key pre-distribution scheme. Neighbor-based authentication is explained briefly in In a selective forwarding attack, malicious nodesliterature. Sanzgiri et al.[2002] proposed the scheme in may refuse to forward certain messages and simplywhich the hash value of the packet corresponds to the drop them, ensuring that they are not propagated anydecrypted value, the previous certificate is removed by further. A simple form of this attack is when athe current node followed by the forwarding of the malicious node behaves like a black hole and refuses topacket with the certificate of the current node.Both the forward every packet she sees. A more subtle form oftarget and intermediary participants were involved in this attack is when an adversary selectively forwardsthe authentication of the data to be routed according to packets. Selective forwarding attacks are typically mosta fresh approach Ariadne proposed by Hu et al. effective when the attacker is explicitly included on the[2002].Every node present in the source–destination path of a data flow. However, it is conceivable anpath determines the authentication of the routing adversary overhearing a flow passing throughinformation with the aid of a Tesla key proposed by neighboring nodes might be able to emulate selectivePerrig et al.[2002], in the course of the route discovery forwarding by jamming or causing a collision on eachprocess. forwarded packet of interest. Majority of the schemes use public key cryptography C. Sinkhole Attackto attain security. But as the sensor nodes in wireless In a sinkhole attack, the adversary’s goal is to luresensor networks are resource constraint the usage of nearly all the traffic from a particular area through apublic key cryptography in WSNs is not feasible. compromised node, creating a metaphorical sinkhole Routing protocols in wireless network are explined with the adversary at the center. Because nodes on, orbriefly in literature. Charles E.Perkins et al.[1999] near, the path that packets follow have manyproposed AODV (Ad-Hoc On Demand Distance opportunities to tamper with application data, sinkholeVector Routing) reactive type routing protocol. attacks can enable many other attacks. Sinkhole attacksProactive type routing protocol DSDV (Destination typically work by making a compromised node lookSequence Distance Vector Routing) is proposed by especially attractive to surrounding nodes with respectCharles E.Perkins et al.[1994] and DSR(Dynamic to the routing algorithm. One motivation for mountingSource Routing) is proposed by David B.Johnson et a sinkhole attack is that it makes selective forwardingal.[2002] From the literature it is found that Cluster trivial.formation to reduce the energy consumed is proposedin LEACH a hierarchical type routing protocol In D. Sybil Attackanother type of routing protocol PEGASIS, each sensor In a Sybil attack, a single node presents multiplenode communicates only with a close neighbor and identities to other nodes in the network. The Sybiltakes turns in transmitting to the base station , thus attack can significantly reduce the effectiveness ofreducing energy. fault-tolerant schemes such as distributed storage, dispersity and multipath routing, and topology III. THREATS TO WIRELESS SENSOR NETWORKS maintenance. Replicas, storage partitions, or routes Most network layer attacks against sensor networks believed to be using disjoint nodes could in actuality befall into one of the following categories: [19] using a single adversary presenting multiple identities. • Spoofed, altered, or replayed routing Sybil attacks also pose a significant threat to information geographic routing protocols. • Selective forwarding E. Wormhole Attack • Sinkhole attacks In the wormhole attack, an adversary tunnels • Sybil attacks messages received in one part of the network over a • Wormholes low-latency link and replays them in a different part. • HELLO flood attacks The simplest instance of this attack is a single node • Acknowledgement spoofing situated between two other nodes forwarding messages • Node Capture Attacks between the two of them. However, wormhole attacks more commonly involve two distant malicious nodesA. Spoofed, altered, or replayed routing information colluding to understate their distance from each other The most direct attack against a routing protocol is by relaying packets along an out-of-bound channelto target the routing information exchanged between available only to the attacker.nodes. By spoofing, altering, or replaying routinginformation, adversaries may be able to create routing F. HELLO Flood Attackloops, attract or repel network traffic, extend or shorten A novel attack against sensor networks is thesource routes, generate false error messages, partition 52© 2010 ACEEEDOI: 01.ijns.01.02.10
    • ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010HELLO flood attack. Many protocols require nodes to (NTN).broadcast HELLO packets to announce themselves to In the proposed scheme RTS/CTS control frames istheir neighbors, and a node receiving such a packet slightly modified from their original MAC protocol formay assume that it is within (normal) radio range of the informing a node the fact that its state is changed to TNsender. This assumption may be false: a laptop-class or NTN in the corresponding period.attacker broadcasting routing or other information withlarge enough transmission power could convince every 10 Bytesnode in the network that the adversary is its neighbor.An adversary does not necessarily need to be able toconstruct legitimate traffic in order to use the HELLOflood attack. It can simply rebroadcast overheadpackets with enough power to be received by every Figure1. a The Original RTS and CTS Framesnode in the network. HELLO floods can also bethought of as one-way, broadcast wormholes.G. Acknowledgement Spoofing Several sensor network routing algorithms rely onimplicit or explicit link layer acknowledgements. Dueto the inherent broadcast medium, an adversary can Figure1. b) The Modified RTS and CTS Framesspoof link layer acknowledgments for ‘‘overheard’’packets addressed to neighboring nodes. Goals include The modified RTS and CTS frame add only oneconvincing the sender that a weak link is strong or that field of two bytes to the original frame. The newlya dead or disabled node is alive. Since packets sent added bytes in RTS is destination address and thealong weak or dead links are lost, an adversary can newly added bytes of CTS is TN addresseffectively mount a selective forwarding attack usingacknowledgement spoofing by encouraging the targetnode to transmit packets on those links.H. Node Capture Attacks The combination of passive attacks, active attacks, Figure. 2: Classification of Node Statesand physical attacks used by the malicious user/users toseize or corrupt network and takes control over the Referring Figure 2, when node B receives A’snode is known as “Node capture attack”.[20] The modified RTS frame including the destination addressmalicious user may induce replicated or corrupted of sink, its routing agent refers to the routing table forinformation into the node which can impact the whole getting the next TN (node C) and informs back to itsnetwork/link to be malfunctioning. These “node MAC. The node B then transmits modified CTS framecapture attacks” occur due to the improper attention of to node C which changes its state to TN and otherthe wireless nodes and the high cost of fool-proof neighbor nodes become aware of the fact that they arehardware in portable devices. [21] The threats which NTN nodes. Otherwise the routing path is broken orare involved due to compromised (captured) node are has not yet been established.much more severe than the attacks from outside the The Proposed Key management scheme consists ofnetwork. As mobile nodes are autonomous and can join following phases:or leave any network at will, it is hard to keep track of i. Initial setup phasesuch nodes constantly. ii.Pre-distribution phase When a node is under attack or compromised, the iii Shared Key discovery phasekeys are exposed to the intruders. Under such a iv.Path key establishment phasecondition, other’s keys are also in a compromised state v. Rekeying Phaseas these keys are also used by other nodes In this paper replay attack and node capture attacks A. Initial Setupare considered. Two keys, namely the Node key K and Network key NK are used in this scheme. The latter is utilized by the IV. PROPOSED KEY MANAGEMENT SCHEME individual sensor nodes for the encryption and The proposed Key management scheme is based on decryption purposes while the former is used by thethe state of sensor nodes. State of sensor nodes are key server node to unicast the node keys to the sensorcategorized in to three types as follows: Current nodes.transmitting node (CTN), Transmitting node (TN), Sensor nodes agree on the following systemtransmitting Node (CTN), Non transmitting Node parameters used in the protocol. The system parameters include 53© 2010 ACEEEDOI: 01.ijns.01.02.10
    • ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010 Global Key Pool: Defined as a pool of random and send to every sensor nodessymmetric keys from which a group key pool isgenerated. Keys are generated using one way function Commandnode → E NK ( INIT )F, where n is chosen to be large. Once the INIT packet is received, a sensor node resets all previous keys. It then calculates new keys KK i = F ( Ki + 1) i = 1,2,3,...n i ,..., K1 from K i +1 . The subsequent key in the key- Group Key Pool: Defined as a subset of Global key sequence is broadcasted by the command node periodically with the aid of UPDATE control packet.pool for a given group. Key Ring: Defined as a subset of group key pool, The node keys are disclosed by the command node in a periodic manner from the to K all nodes in thewhich is independently assigned to each sensor node. L+2 Key-Sharing Graph: Let V represent all the nodes in group.At time T + T ,the server broadcasts start rekeyWSN. A Key-Sharing graph G (V, E) is constructed in UPDATE packets containing K i + L + 2, i =1,2,....,n −the following manner: For any two nodes i and j in V, L − 2 ,Command node → group : E K i +1 ( K i + L +there exists an edge between them if and only if (1) 2)nodes i and j have at least one common key, and (2) Where Eki +1 is the active encryption key at the timenodes i and j can reach each other within the wireless when UPDATE packet is broadcasted.transmission range, i.e., in a single hop. The UPDATE packet is discarded once the nodeB. Key Pre-Distribution Phase detects that it is not from its own server. If not, the UPDATE packet is broadcasted to all the neighbors. This phase is performed off-line and before thedeployment of sensor nodes. Primarily group key pools V. PERFORMANCE EVALUATIONGi (i = 1,2,..., k )) are produced using global key poolS. After this, for each sensor node in a group, a key A. Evaluation Metricsring from a group key pool is Gi assigned along with avariable. In the proposed scheme following evaluation metrics are considered:C. Shared-Key Discovery Phase Connectivity: The probability that two sensors share This phase is used to find a secure link between two at least one common key at a given time-intervalsensor nodes. Sensor nodes which identify its shared should be higher, with smaller number of keys.keys in their key rings, then verify that other CTN and Resilience against Node Capture: Exposing of theTN node contain these keys. Now the shared key turns secret information regarding other nodes should beout to be the key for that link. A key-sharing graph is made certain by the key establishment technique, if acreated by the entire sensor networks following above node inside a sensor network is confined.step. The execution of the shared key discovery phase Any efficient key management scheme for WSNsis completed by a CTN node, if it finds out a TN node should have higher connectivity and stronger resilienceas a neighbor. B. Numerical ResultsD. Path -Key Establishment Phase Connectivity Sensor nodes can form path keys with their neighbor It is defined as the probability ( Ps ) that two TN ornodes since they have not shared keys inside their key CTN state sensor nodes share atleast a common keyrings. A path can be established from a source sensor after deployement at a given time interval.node to other CTN and TN sensor nodes, if the key- Let φ is the set of all sensor node groups and twosharing graph is connected. A path key can be nodes Ni and NJ are selected fromGj and Gi of φ .generated by the source node and send it safely using a The probability that Ni and N j are in TN state at givenpath to the target sensor node. time-interval, and two nodes share at least one commonE. Re-keying Phase key is given by Ps. Using Baye’s Theorem, This Phase uses two control packetsand INITUPDATE .The command node prepares a controlpacket INIT which containsINIT : ( L, K i +1, Trekey ), MAC(L, K i +1, Trekey )L – length of the keyKi - initial key Where, P1 (Ti ) – – Probability of group G at a time iTrekey - Rekeying interval of Ki interval Ti P3 ( Sh) - - Probability that two nodes shareThis control packet is encrypted with network key NK at least one common key The probability that two nodes are in TN state at a 54© 2010 ACEEEDOI: 01.ijns.01.02.10
    • ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010given time-interval Ti is calculated using [2006]. It is found that lesser number of keys is involved in the proposed scheme to achieve the same probability. i − a tmf p (ti m ) = e a C. Simulation Results _______________________________ (2) NS2 simulator is used for simulation with following specifications: x! • Maximum Number of nodes is 80 Therefore the active-probability of Gi at T can be • The deployment area is 500mx500 m. i • Simulation time is 100 seconds.found as follows • The transmission range of 250 meters with Constant Bit Rate (CBR). The proposed key management is applied with routing protocols DSDV, LEACH and PEGASIS and simulated to find resilience, energy consumed and end to end delay performance. Effects of Resilience against Node Capture An adversary can attack on a sensor node after it is deployed to read the information. To find how a successful attack on n sensor nodes by an adversary The probability that two nodes share at least one affects the rest of the network resilience is used.common key is expressed as Resilience is calculated from the fraction of communication among the uncompromised nodes that1 − pr two sensors do not share any key]. (4) an adversary can compromise based on the informationConsider retrieved from the n captured nodes. Using the routingTotal size of each group = M protocols DSDV, LEACH, and PEGASIS, resilience isShared keys = Sh(M ) measured for the proposed TKM scheme with varyingNon-Shared keys = M − Sh(M ) number of nodes and attackers and compared with Let n1 , n 2 be two sensor nodes. When n1select x SHELL proposed by Mohemed F.Younis et al.[2006].keys from keys Sh(M ) and y keys from M − Sh(M )keys, then n2 select z keys from ( M − x) Keys. Resilience for various attackers Pr [two sensors do not share any key] is given by 1 0.8 DSDV-5 resilience 0.6 DSDV-10 0.4 DSDV-15 0.2 DSDV-20 0 20 40 60 80 nodes Figure 4.a.Resilence Vs Nodes-DSDV 1 0.8 Resilience for various Attackers Connectivity 0.6 TKM 0.4 Existing 1 0.2 0.8 LEACH-5 0 0.6 LEACH-10 resilience 25 50 75 100 120 0.4 LEACH-15 Keys 0.2 LEACH-20 0 Figure 3.Connectivity Vs No. of Keys 20 40 60 80 nodes Figure.3 gives the connectivity with respect to thevaried number of keys in each sensor. The proposedscheme is compared with the existing random key pre- Figure 4.b.Resilence Vs Nodes-LEACHdistribution scheme of Mohamed F. Younis et al.’s 55© 2010 ACEEEDOI: 01.ijns.01.02.10
    • ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010 Resilience For Varous Attackers 1 0.8 PEGASIS-5 Resilience 0.6 PEGASIS-10 0.4 PEGASIS-15 0.2 PEGASIS-20 0 20 40 60 80 Nodes Figure5.a. Energy Consumption Vs Nodes –DSDV Figure. 4.c.Resilence Vs Nodes-PEGASIS Energy For Various Attackers Resilience For Various Attacke rs 0.6 1.2 0.5 1 LEACH-5 SHELL-5 0.4 energy(j) resilience 0.8 LEACH-10 SHELL-10 0.3 0.6 LEACH-15 SHELL-15 0.2 0.4 LEACH-20 SHELL-20 0.1 0.2 0 0 20 40 60 80 20 40 60 80 nodes nodes Figure 5.b. Energy Consumption Vs Nodes –LEACH Figure 4.d.Resilence Vs Nodes-SHELL Figure 5.a shows the energy consumed with TKM- Figure 4.a shows the resilience with TKM using DSDV. With increase in the number of nodes from 20routing protocol DSDV. With increase in the number of nodes to 80 nodes and increase in number of attackersnodes from 20 to 80 nodes and increase in number of from 5 attackers to 20 attackers the energy consumed isattackers from 5 to 20 attackers the resilience is reduced by 43% to 47% when compared with SHELLreduced by 55% to 61%. Figure 5.b shows the energy consumed with TKM- Figure 4.b shows the resilience with TKM using LEACH. Number of nodes is increased from 20 nodesrouting protocol LEACH.With increase in the number to 80 nodes and the number of attackers is alsoof nodes from 20 to 80 nodes and increase in number of increased from 5 attackers to 20 attackers and it isattackers from 5 attackers to 20 attackers the resilience observed that the energy consumed is reduced by 58%is reduced by 79% to 81%. to 62% when compared with SHELL Figure 4.c shows the resilience with TKM using Figure 5.c shows the energy consumed with TKMrouting protocol PEGASIS. With increase in the using routing protocol PEGASIS. With increase in thenumber of nodes from 20 to 80 nodes and increase in number of nodes from 20 nodes to 80 nodes andnumber of attackers from 5 to 20 attackers the increase in number of attackers from 5 attackers to 20resilience is reduced by 86% to 88%. attackers the energy consumed is reduced by 69% to Figure 4.d shows the resilience with SHELL. With 71% when compared with SHELLincrease in the number of nodes from 20 to 80 nodesand increase in number of attackers from 5 to 20 Energy For Various Attackersattackers the resilience is reduced only by 28% to 38%. 0.4 It is found from fig 4.a-e the performance ofresilience is best in TKM-PEGASIS and hence more 0.3 PEGASIS-5 energy(j)secure when compared with TKM using LEACH, 0.2 PEGASIS-10DSDV and SHELL. PEGASIS-15 0.1 PEGASIS-20Effects of Energy Consumption against Node Capture 0 Energy consumed by the network is obtained by 20 40 60 80varying total number of nodes and attackers with TKM nodesusing routing protocols DSDV, LEACH and PEGASIS.Proposed TKM scheme is compared with SHELL. Figure 5.c. Energy Consumption Vs Nodes -PEGASIS 56© 2010 ACEEEDOI: 01.ijns.01.02.10
    • ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010 Energy For Various Attackers Delay For Various Attackers 1.4 1.2 0.8 1 SHELL-5 PEGASIS-5 0.6 energy(j) 0.8 SHELL-10 PEGASIS-10 Delay(s) 0.6 SHELL-15 0.4 0.4 PEGASIS-15 SHELL-20 0.2 0.2 PEGASIS-20 0 0 20 40 60 80 20 40 60 80 nodes Nodes . Figure 5.d. Energy Consumption Vs Nodes –SHELL . Figure 6.c.Delay Vs Attackers From figure 5.a to 5.d it is observed that TKM-PEGASIS consumes less energy for specific Delay For Various Attackerstransmission when compared with TKM usingLEACH, DSDV and SHELL. 1.75 1.7 SHELL-5 Delay(s)Effects of End to End Delay against Node Capture 1.65 SHELL-10 SHELL-15 Delay For Various Attackers 1.6 SHELL-20 1 1.55 0.8 DSDV-5 20 40 60 80 Delay(s) 0.6 DSDV-10 Nodes 0.4 DSDV-15 0.2 DSDV-20 Figure 6.d. Delay Vs Attackers 0 20 40 60 80 Nodes From figure 6.a-d it is observed that end to end delay is reduced more in TKM–PEGASIS when compared Figure 6.a. Delay Vs Attackers with TKM using LEACH, DSDV and SHELL. Figure 6.a shows that the end to end delay is reduced VI. CONCLUSIONby 49% to 63% with TKM-DSDV when compared with The proposed scheme establishes shared keys forSHELL with increase in the number of nodes from 20 active sensor nodes which participate in directnodes to 80 nodes and number of attackers from 5 to 20 communication, based on the topological informationattackers. of the network. This scheme provides seamless re- Figure 6.b.shows that the end to end delay is reduced keying without disrupting the ongoing security process.by 54% to 61% with TKM-LEACH when compared Numerical results show that the proposed schemewith SHELL with increase in the number of nodes from achieves high connectivity. The simulation is20 nodes to 80 nodes and number of attackers from 5 performed for the proposed scheme with differentattackers to 20 attackers routing protocols. Performance analysis shows that Figure 6.c shows that the end to end delay is reduced proposed key management scheme TKM withby 61% to 65% with TKM-PEGASIS when compared PEGASIS achieves stronger resilience low energywith SHELL with increase in the number of nodes from consumption and lesser end to end delay when20 nodes to 80 nodes and number of attackers from 5 compared with SHELL.attackers to 20 attackers. Delay For Various Attackers REFERENCES 1 [1] Wenliang DuJing DengHan, Y.S.Shigang Chen 0.8 LEACH-5 Varshney, P.K.“A Key Management Scheme for Delay(s) 0.6 LEACH-10 Wireless Sensor Networks Using Deployment 0.4 LEACH-15 Knowledge” INFOCOM 2004. Twenty-third 0.2 LEACH-20 AnnualJoint Conference of the IEEE Computer and 0 Communications Societies 7-11 March 2004. 20 40 60 80 [2] Alan Price, Kristie Kosaka and Samir Chatterjee “A Nodes Secure Key Management Scheme for Sensor Networks” Proceedings of the Tenth Americas Conference on Figure 6.b. Delay Vs Attackers Information Systems, New York, New York, August 2004. 57© 2010 ACEEEDOI: 01.ijns.01.02.10
    • ACEEE International Journal on Network Security, Vol 1, No. 2, July 2010[3] Siu-Ping Chan, Radha Poovendran and Ming-Ting Sun [10] A. Perrig, R. Canetti, D. Tygar, and D. Song. “The “A Key Management Scheme in Distributed Sensor TESLA Broadcast Authentication Protocol”. In RSA Networks Using Attack Probabilities” Global CryptoBytes, volume 5(2), pages 2–13, 2002 Telecommunications Conference, 2005.GLOBECOM [11] Charles E. Perkins, Elizabeth M. Royer “Ad hoc On 05. 28 Nov.-2 Dec. 2005 Demand Distance Vector Routing” Mobile Computing[4] Rui Miguel Soares Silva, Nuno Sidónio Andrade Pereira Systems and Applications, 1999. Proceedings. WMCSA and Mário Serafim Nunes "Chaos Based Key 99. Second IEEE Workshop on Publication Date: 25-26 Management Architecture for Wireless Sensor Feb 1999. Networks", Australian Telecommunication Networks [12] C.E. Perkins and P.Bhagwat. ”Highly Dynamic and Application Conference [ATNAC 2006], December Destination-Sequenced Distance-Vector routing (DSDV) 4-6, 2006. for mobile computers”. In Proceedings of the[5] Dijiang Huang, Manish Mehta, Deep Medhi and Lein SIGCOMM’94 conference on Communications, Harn “Location Aware Key Management Scheme for Architectures, Protocols, and Applications, August 1994. Wireless Sensor Networks” Proc. of 2004 ACM [13] David B. Johnson and David A. Maltz “Dynamic Source Workshop on Security of Ad Hoc and Sensor Networks Routing in Ad Hoc Wireless Networks” Wiley Series On (SASN04), pp. 29-42, October 2004 Parallel And Distributed Computing, Pages: 425 –[6] An, F. Cheng, X. Rivera, J. M. Li, J. Cheng, Z. “PKM: A 450,Year of Publication: 2002 ISBN:0-471-41902-8. Pairwise Key Management Scheme for Wireless Sensor [14] Changsu Suh, Young-Bae Ko and Dong-Min Son, "An Networks” Lecture Notes In Computer Science 2005, Energy Efficient Cross-Layer MAC Protocol for Numb 3619, pages 992-1001. Wireless Sensor Networks," Proc. of the International[7] Jaemin Park, Zeen Kim, and Kwangjo Kim “State-Based Workshop on Sensor Networks (IWSN06) in APWeb06, Key Management Scheme for Wireless Sensor Jan. 2006. (LNCS), Networks” Mobile Adhoc and Sensor Systems [15] Mohamed F. Younis , Kajaldeep Ghumman and Conference, 2005. IEEE International Conference on 7- Mohamed Eltoweissy “Location-Aware Combinatorial 10 Nov. 2005. Key Management Scheme for Clustered Sensor[8] K. Sanzgiri, Bridget Dahill, B. Levine, C. Shields, and E. Networks” , IEEE transactions on parallel and Belding-Royer.”Secure routing Protocol for Ad Hoc distributed systems, Vol. 17, No. 8, August 2006. Networks”. In Proceedings of the IEEE International Conference on Network Protocols, 2002[9] Y. Hu, A. Perrig, and D. Johnson. “Ariadne: A secure on- demand routing protocol for ad hoc networks”. In Proceedings of the International Conference on Mobile Computing and Networking (MobiCom), 2002 58© 2010 ACEEEDOI: 01.ijns.01.02.10