Title With Abstract - 2011

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S.NO TITLE -2010 ABSTRACT

DOMAIN PLAT

1. A MachineLearning Approachto TCP ThroughputPrediction

TCPthroug

hputpredictionisani

mportantcapabilityfor

networkswheremultiplep

Networking.net
http://www.ingenioustech.in/http://www.ingenioustech.in/mailto:[email protected]:[email protected]://www.ingenioustech.in/http://www.ingenioustech.in/http://www.ingenioustech.in/http://www.ingenioustech.in/http://www.ingenioustech.in/http://www.ingenioustech.in/http://www.ingenioustech.in/http://www.ingenioustech.in/mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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athsexist

betweendatasendersandreceivers.Inthis

paper,wedescribea

newlightweightmetho

dfo


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rTCPth

roughputprediction.OurpredictorusesSupp

ortVectorRegression

(SVR);predictionisbas

ed


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onboth

priorfiletransferhistoryandmeasurement

sofsimplepathproper

ties.Weevaluateour

pre


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dictorina

laboratorysettingwheregroundtruthcanb

emeasuredwithperfect

accuracy.Wereportthe

per


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formanc

eofourpredictorfororacularandpracticalme

asurementsofpathpro

pertiesoverawideran

ge


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oftrafficco

nditionsandtransfersizes.Forbulktransfe

rsinheavytrafficusingor

acularmeasurements,T

CP


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through

putispredictedwithin10%oftheactualvalue

87%ofthetime,represe

ntingnearlyathreefold

im


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provem

entinaccuracyoverpriorhistory-basedmetho

ds.Forpracticalmeasur

ementsofpathproper

ties


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,predict

ionscanbemadewithin10%oftheactualvalu

enearly50%ofthetim

e,approximatelya60

%i


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mprove

mentoverhistory-basedmethods,andwith

muchlowermeasureme

nttrafficoverhead.We

im


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plement

ourpredictorinatoolcalledPathPerf,testitinth

ewidearea,andshow

thatPathPerfpredicts

TC


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Pthroug

hputaccuratelyoverdiversewideareapaths.

2. Feedback-BasedScheduling for Load-

Balanced Two-Stage

Switches

Aframeworkfordesig

ningfeedback-based

sch

.net


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eduling

algorithmsisproposedforelegantlysolvin

gthenotoriouspacketm

issequencingproblem

ofa


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load-bal

ancedswitch.Unlikeexistingapproaches,w

eshowthattheeffortsm

adeinloadbalancing

an


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dkeepin

gpacketsinordercancomplementeachother.

Specifically,ateachmid

dle-stageportbetwe

en


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thetwo

switchfabricsofaload-balancedswitch,onl

yasingle-packetbuffe

rforeachvirtualoutp

utq


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ueuein

g(VOQ)isrequired.Althoughpacketsbelongi

ngtothesameflowpas

sthroughdifferentmid

dle-


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stageV

OQs,thedelaystheyexperienceatdifferent

middle-stageportswill

beidentical.Thisism

ad


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epossibl

ebyproperlyselectingandcoordinatingthe

twosequencesofswitc

hconfigurationstoforma

joint


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sequenc

ewithbothstaggeredsymmetrypropertyan

din-orderpacketdeliv

eryproperty.Basedo

nth


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estagg

eredsymmetryproperty,anefficientfeedbac

kmechanismisdesign

edtoallowtherightmid

dle-


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stagep

ortoccupancyvectortobedeliveredtotheri

ghtinputportattherig

httime.Asaresult,thep

erfo


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rmance

ofloadbalancingaswellastheswitchthrough

putissignificantlyimpr

oved.Wefurtherexte

nd


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thisfeed

backmechanismtosupportthemulticabinet

implementationofalo

ad-balancedswitch,w

her


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ethepro

pagationdelaybetweenswitchlinecardsa

ndswitchfabricsisno

nnegligible.Ascompar

ed


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totheexi

stingload-balancedswitcharchitecturesan

dschedulingalgorith

ms,oursolutionsimpos

ea


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modest

requirementonswitchhardware,butconsiste

ntlyyieldbetterdelay-

throughputperforma

nce.


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Lastbutn

otleast,someextensionsandrefinementsar

emadetoaddressthe

scalability,implement

atio


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n,andfa

irnessissuesofoursolutions.

3. Trust management inmobile ad hoc networks

using a scalable

maturity based model

Inthispaper,

weproposeahuman-

basedmodelwhichbuil

dsa

.net


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trustrela

tionshipbetweennodesinanadhocnetw

ork.Thetrustisbased

onpreviousindividual

ex


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periences

andontherecommendationsofothers.Wepr

esenttheRecommend

ationExchangeProtoc

ol(R


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EP)which

allowsnodestoexchangerecommendatio

nsabouttheirneighb

ors.Ourproposaldoesn

otre


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quirediss

eminatingthetrustinformationovertheent

irenetwork.Instead,n

odesonlyneedtokee

pa


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ndexch

angetrustinformationaboutnodeswithin

theradiorange.Witho

uttheneedforaglob

altr


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ustkno

wledge,ourproposalscaleswellforlargenetw

orkswhilestillreducingth

enumberofexchang

ed


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messages

andthereforetheenergyconsumption.Inad

dition,wemitigatethe

effectofcolludingattacks

com


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posedof

liarsinthenetwork.Akeyconceptweintroduce

istherelationshipmatur

ity,whichallowsnodes

toi


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mprove

theefficiencyoftheproposedmodelformobil

escenarios.Weshowth

ecorrectnessofourmod

elin


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asingle-

hopnetworkthroughsimulations.Wealsoe

xtendtheanalysistom

obilemultihopnetwor

ks,


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showing

thebenefitsofthematurityrelationshipconce

pt.Weevaluatethei

mpactofmaliciousnod

esth


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atsendfa

lserecommendationstodegradetheefficienc

yofthetrustmodel.At

last,weanalyzethep

erfo


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rmance

oftheREPprotocolandshowitsscalability.We

showthatourimpleme

ntationofREPcansigni

fica


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rityand

privacy

ofOSNs,and

humanmobilitymodelsbasedonsocialn

etworkOSNsonlinese

rvic


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esitefocu

sesofsocialnetworksorsocialrelationsamong

people,e.g.,whoshar

einterestsandactiviti

es.


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Asocialn

etworkserviceessentiallyconsistsofarepresentat

ionofeachuser(oftena

profile),his/hersociallinks

,a


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ndavar

ietyofadditionalservices.Mostsocialnetwor

kservicesarewebbase

dandprovidemeans

for


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userstoin

teractovertheinternet,suchase-mailandinsta

ntmessaging.Although

onlinecommunityservic

esar


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esometi

mesconsideredasasocialnetworkonlinecomm

unityservicesaregroup-

centered.Socialnetworki

ng


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sitesallow

userstoshareideas,activities,events,and

interestswithintheirindi

vidualnetworks.

5. SYNCHRONIZATIONOF LOCAL DESKTOP

TO INTERNET USINGFILE TRANSFER

Filesync


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PROTOCOLhroniza

tionincomputingisthe

processofmakingsurethat

filesintwoormorelocati

onsareupdatedthro

ugh


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certain

rules.Inone-wayfilesy

nchronization,alsocalled

mirroring,updatedfiles

arecopiedfroma'so

urce'


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locatio

ntooneormore'target

'locations,butnofiles

arecopiedbacktotheso

urcelocation.Intwo-w

ayfil


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esynchr

onization,updatedfil

esarecopiedinbothdire

ctions,usuallywiththep

urposeofkeepingthe

two


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locatio

nsidenticaltoeachother

.Inthisarticle,theterm

synchronizationreferse

xclusivelytotwo-wa

yfile


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synchro

nization.

6. Intrusion Detectionfor Grid and CloudComputing

Providing

securityinadistributed

systemrequiresmoreth

anuserauthenticationwith


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passwor

dsordigitalcertificatesandconfidentialityindat

atransmission.TheGr

idandCloudComput

ing


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Intrusion

DetectionSystemintegratesknowledgean

dbehavioranalysisto

detectintrusions.

7. Adaptive PhysicalCarrier Sense in

Topology-ControlledWireless Networks

Tra

nsm


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ssnetwor

ks.Transmitpowercontrolhasbeenextens

ivelystudiedinthecont

extoftopologycontrol.

Ho


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wever,

theeffectofcarriersensethresholdontopology

controlhasnotbeenpr

operlyinvestigatedin

spit


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eofitscruc

ialrole.Ourkeymotivationisthattheperforma

nceofatopology-contro

llednetworkmaybeco

me


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worsetha

nthatofanetworkwithoutanytopologycont

rolunlesscarriersenseth

resholdisproperlychose

n.In


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ordertore

medythisdeficiencyofconventionaltopolo

gycontrol,wepresenta

frameworkonhowto

inco


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rporatep

hysicalcarriersenseintotopologycontrol.Weid

entifythatjointcontrolof

transmitpowerandca

rrier


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sensethre

sholdcanbeefficientlydividedintotopology

controlandcarriersense

adaptation.Wedevise

adi


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stribute

dcarriersenseupdatealgorithm(DCUA),by

whicheachnodedrives

itscarriersensethresholdto

war


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dadesir

ableoperatingpointinafullydistributedma

nner.Wederiveasuffi

cientconditionforthe

con


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vergenc

eofDCUA.Todemonstratetheutilityofintegr

atingphysicalcarriersens

eintotopologycontrol,

we


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equipa

localizedtopologycontrolalgorithm,LMS

T,withthecapabilityofD

CUA.Simulationstudies

sho


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wthatLM

ST-DCUAsignificantlyoutperformsLMST

andthestandard

8. On the Quality ofService of Crash-

Recovery Failure

Detectors

We model the probabilistic behavior of a system

comprising a failure detector and a monitoredcrash-recovery target. We extend failuredetectors to take account of failure recovery inthe target system. This involves extending QoSmeasures to include the recovery detectionspeed and proportion of failures detected. Wealso extend estimating the parameters of thefailure detector to achieve a required QoS toconfiguring the crash-recovery failure detector.We investigate the impact of the dependabilityof the monitored process on the QoS of ourfailure detector. Our analysis indicates thatvariation in the MTTF and MTTR of the

monitored process can have a significantimpact on the QoS of our failure detector. Our

Dependable

andSecurity

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analysis is supported by simulations thatvalidate our theoretical results.

9. Layered Approachusing conditional

random field

Intrusion detection faces challenges anintrusion detection system must constantly

detect malicious activities in a network andmust perform efficiently to cope with the largeamount of network traffic. These two issues ofAccuracy and Efficiency using ConditionalRandom Fields and Layered Approach. We showthat high attack detection accuracy can beachieved by using Conditional Random Fieldsand high efficiency by implementing theLayered Approach. Experimental results on thebenchmark KDD 99 intrusion data set showthat our proposed system based on LayeredConditional Random Fields outperforms otherwell-known methods such as the decision trees

and the naive Bayes. The improvement inattack detection accuracy is very high,particularly, for the U2R attacks (34.8 percentimprovement) and the R2L attacks (34.5percent improvement). Statistical Tests alsodemonstrate higher confidence in detectionaccuracy for our method. Finally, we show thatour system is robust and is able to handle noisy

data without compromising performance.

10. Privacy-PreservingSharing of Sensitive

Information

Privacy-preserving sharing of sensitiveinformation (PPSSI) is motivated by theincreasing need for entities (organizations orindividuals) that don't fully trust each other toshare sensitive information. Many types ofentities need to collect, analyze, anddisseminate data rapidly and accurately,without exposing sensitive information tounauthorized or untrusted parties. Althoughstatistical methods have been used to protectdata for decades, they aren't foolproof andgenerally involve a trusted third party.Recently, the security research community hasstudiedand, in a few cases, deployedtechniques using secure, multiparty functionevaluation, encrypted keywords, and privateinformation retrieval. However, few practicaltools and technologies provide data privacy,especially when entities have certain commongoals and require (or are mandated) somesharing of sensitive information. To this end,PPSSI technology aims to enable sharinginformation, without exposing more than theminimum necessary to complete a commontask.

Securityand privacy

.net

11. PEACE Security and privacy issues are of most concernin pushing the success of WMNs(Wireless Mesh


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Networks) for their wide deployment and forsupporting service-oriented applications.Despite the necessity, limited security researchhas been conducted toward privacypreservation in WMNs. This motivates us to

develop PEACE, a novel Privacy-Enhancedyet Accountable security framework, tailored forWMNs

12. The Phish-MarketProtocol: Secure

Sharing Between

Competitors

One way banks mitigate phishing's effects is toremove fraudulent websites or suspend abusivedomain names. The removal process, called a"take-down," is often subcontracted tospecialist firms, who refuse to share feeds ofphishing website URLs with each other.Consequently, many phishing websites aren'tremoved. The take-down companies are

reticent to exchange feeds, fearing thatcompetitors with less comprehensive lists mightfree-ride off their efforts. Here, the authorspropose the Phish-Market protocol, whichenables companies to be compensated forinformation they provide to their competitors,encouraging them to share. The protocol isdesigned so that the contributing firm iscompensated only for those websites affectingits competitor's clients and only thosepreviously unknown to the receiving firm. Thereceiving firm, on the other hand, is guaranteed

privacy for its client list. The protocol solves amore general problem of sharing betweencompetitors; applications to data brokers inmarketing, finance, energy exploration, andbeyond could also benefit.

.net

13. Internet FilteringIssues and Challenges

Various governments have been consideringmechanisms to filter out illegal or offensiveInternet material. The accompanying debateraises a number of questions from a technicalperspective. This article explores some of thesequestions, such as, what filtering techniquesexist,are they effective in filtering out the

specific content, how easy is circumventingthem ,where should they be placed in theInternet architecture.

.net

14. Can Public-CloudSecurity Meet ItsUnique Challenges?

Because cloud-computing environments'security vulnerabilities differ from those oftraditional data centers, perimeter-securityapproaches will no longer work. Security mustmove from the perimeter to the virtualmachines.

.net

15. Encrypting KeysSecurely

Encryption keys are sometimes encryptedthemselves; doing that properly requires special

care. Although it might look like an oversight atfirst, the broadly accepted formal security

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definitions for cryptosystems don't allowencryption of key-dependent messages.Furthermore, key-management systemsfrequently use key encryption or wrapping,which might create dependencies among keys

that lead to problems with simple access-control checks. Security professionals should beaware of this risk and take appropriatemeasures. Novel cryptosystems offer protectionfor key-dependent messages and should beconsidered for practical use. Through enhancedaccess control in key-management systems,you can prevent security-interface attacks.

16. Auto-Context and ItsApplication to High-

Level Vision Tasks and

3D Brain ImageSegmentation

The notion of using context information forsolving high-level vision and medical imagesegmentation problems has been increasinglyrealized in the field. However, how to learn an

effective and efficient context model, togetherwith an image appearance model, remainsmostly unknown. The current literature usingMarkov Random Fields (MRFs) and ConditionalRandom Fields (CRFs) often involves specificalgorithm design in which the modeling andcomputing stages are studied in isolation. Inthis paper, we propose a learning algorithm,auto-context. Given a set of training imagesand their corresponding label maps, we firstlearn a classifier on local image patches. Thediscriminative probability (or classification

confidence) maps created by the learnedclassifier are then used as context information,in addition to the original image patches, totrain a new classifier. The algorithm theniterates until convergence. Auto-contextintegrates low-level and context information byfusing a large number of low-level appearancefeatures with context and implicit shapeinformation. The resulting discriminativealgorithm is general and easy to implement.Under nearly the same parameter settings intraining, we apply the algorithm to threechallenging vision applications:

foreground/background segregation, humanbody configuration estimation, and sceneregion labeling. Moreover, context also plays avery important role in medical/brain imageswhere the anatomical structures are mostlyconstrained to relatively fixed positions. Withonly some slight changes resulting from using3D instead of 2D features, the auto-contextalgorithm applied to brain MRI imagesegmentation is shown to outperform state-of-the-art algorithms specifically designed for thisdomain. Furthermore, the scope of theproposed algorithm goes beyond image

analysis and it has the potential to be used for awide variety of problems for structured

PatternAnalysisandMachine

Intelligence

.net
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Off-Task Behaviors in

Intelligent Tutoring

Systems with Machine

Learning Techniques

tutoring systems is a practical and challengingresearch topic. This paper proposes a machinelearning model that can automatically detectstudents' off-task behaviors. The proposedmodel only utilizes the data available from the

log files that record students' actions within thesystem. The model utilizes a set of timefeatures, performance features, and mousemovement features, and is compared to 1) amodel that only utilizes time features and 2) amodel that uses time and performancefeatures. Different students have different typesof behaviors; therefore, personalized version ofthe proposed model is constructed andcompared to the correspondingnonpersonalized version. In order to addressdata sparseness problem, a robust RidgeRegression algorithm is utilized to estimatemodel parameters. An extensive set ofexperiment results demonstrates the power ofusing multiple types of evidence, thepersonalized model, and the robust RidgeRegression algorithm.

Technologies

20. Web-ApplicationSecurity: From Reactive

to Proactive

Here's a sobering thought for all managersresponsible for Web applications: Withoutproactive consideration for an application'ssecurity, attackers can bypass nearly all lower-layer security controls simply by using theapplication in a way its developers didn't

envision. Learn how to address vulnerabilitiesproactively and early on to avoid thedevastating consequences of a successfulattack.

IT .net

21. Trust and ReputationManagement

Trust and reputation management research ishighly interdisciplinary, involving researchersfrom networking and communication, datamanagement and information systems, e-commerce and service computing, artificialintelligence, and game theory, as well as thesocial sciences and evolutionary biology. Trustand reputation management has played and

will continue to play an important role inInternet and social computing systems andapplications. This special issue addresses keyissues in the field, such as representation,recommendation aggregation, and attack-resilient reputation systems.

INTERNETCOMPUTING

.net

22. Multi-body Structure-and-MotionSegmentation byBranch-and-BoundModel Selection

An efficient and robust framework is proposedfor two-view multiple structure-and-motionsegmentation of unknown number of rigidobjects. The segmentation problem has threeunknowns, namely the object memberships, thecorresponding fundamental matrices, and the

number of objects. To handle this otherwiserecursive problem, hypotheses for fundamental

ImageProcessing

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matrices are generated through local sampling.Once the hypotheses are available, acombinatorial selection problem is formulatedto optimize a model selection cost which takesinto account the hypotheses likelihoods and the

model complexity. An explicit model for outliersis also added for robust segmentation. Themodel selection cost is minimized through thebranch-and-bound technique of combinatorialoptimization. The proposed branch-and-boundapproach efficiently searches the solution spaceand guaranties optimality over the current setof hypotheses. The efficiency and theguarantee of optimality of the method is due toits ability to reject solutions without explicitlyevaluating them. The proposed approach wasvalidated with synthetic data, andsegmentation results are presented for realimages.

23. Active Image Reranking

Image search reranking methods usually fail tocapture the user's intention when the queryterm is ambiguous. Therefore, reranking withuser interactions, or active reranking, is highlydemanded to effectively improve the searchperformance. The essential problem in activereranking is how to target the user's intention.To complete this goal, this paper presents astructural information based sample selectionstrategy to reduce the user's labeling efforts.

Furthermore, to localize the user's intention inthe visual feature space, a novel local-globaldiscriminative dimension reduction algorithm isproposed. In this algorithm, a submanifold islearned by transferring the local geometry andthe discriminative information from the labelledimages to the whole (global) image database.Experiments on both synthetic datasets and areal Web image search dataset demonstratethe effectiveness of the proposed activereranking scheme, including both the structuralinformation based active sample selectionstrategy and the local-global discriminative

dimension reduction algorithm.

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24. Content Based ImageRetrieval using PSO

An innovative approach based on anevolutionary stochastic algorithm, namely theParticle Swarm Optimizer (PSO), is proposed inthis paper as a solution to the problem ofintelligent retrieval of images in largedatabases. The problem is recast to anoptimization one, where a suitable cost functionis minimized through a customized PSO.Accordingly, the relevance-feedback is used inorder to exploit the information of the user withthe aim of both guiding the particles inside the

search space and dynamically assigning

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different weights to the features.

25. Automatic Compositionof Semantic Web

Services An Enhanced

State Space Search

Approach

This paper presents a novel approach forsemantic web service composition based ontraditional state space search approach. We

regard automatic web service compositionproblem as an AI problem-solving problem andpropose an enhanced state space searchapproach toward web service compositiondomain. This approach can not only be used forautomatic service composition, but also forgeneral problem-solving domain. In addition, inorder to validate the feasibility of our approach,a prototype system is implemented.

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26. Knowledge-first webservices an E-

Government example

Although semantic technologies aren't used incurrent software systems on a large scale yet,they offer high potential to significantly improve

the quality of electronic services especially inthe E-Government domain. This paper thereforepresents an approach that not only incorporatessemantic technologies but allows to create E-Government services solely based on semanticmodels. This multiplies the benefits of theontology modeling efforts, minimizesdevelopment and maintenance time and costs,improves user experience and enforcestransparency.

.net

27. The Applied Researchof Cloud ComputingPlatform ArchitectureIn the E-Learning Area

This paper firstly introduces the characteristicsof the current E-Learning, and then analyzesthe concept and characteristics of cloudcomputing, and describes the architecture ofcloud computing platform; by combining thecharacteristics of E-Learning and learning fromcurrent major infrastructure approach of cloudcomputing platform, this paper structures arelatively complete set of integration and use inone of the E-Learning platform, puts the cloudcomputing platform apply to the study of E-Learning, and focus on the application in orderto improve the resources' stability, balance andutilization; under the conditions, this platform

will meet the demand for the current teachingand research activities, improve the greatestvalue of the E-Learning.

Cloud

comput

ing

.net

28. Cloud ComputingSystem Based onTrusted ComputingPlatform

Cloud computing provides people a way toshare large mount of distributed resourcesbelonging to different organizations. That is agood way to share many kinds of distributedresources, but it also makes security problemsmore complicate and more important for usersthan before. In this paper, we analyze somesecurity requirements in cloud computingenvironment. Since the security problems both

in software and hardware, we provided amethod to build a trusted computing

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environment for cloud computing by integratingthe trusted computing platform (TCP) into cloudcomputing system. We propose a newprototype system, in which cloud computingsystem is combined with Trusted Platform

Support Service (TSS) and TSS is based onTrusted Platform Module (TPM). In this design,better effect can be obtained in authentication,role based access and data protection in cloudcomputing environment.

29.

IT Auditing to Assurea Secure CloudComputing.

In this paper we discuss the evolvement ofcloud computing paradigm and present aframework for secure cloud computing throughIT auditing. Our approach is to establish ageneral framework using checklists by following

data flow and its lifecycle. The checklists aremade based on the cloud deployment modelsand cloud services models. The contribution ofthe paper is to understand the implication ofcloud computing and what is meant securecloud computing via IT auditing rather thanpropose a new methodology and newtechnology to secure cloud computing. Ourholistic approach has strategic value to thosewho are using or consider using cloudcomputing because it addresses concerns suchas security, privacy and regulations andcompliance.

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30. PerformanceEvaluation of CloudComputing Offerings

Advanced computing on cloud computinginfrastructures can only become viablealternative for the enterprise if theseinfrastructures can provide proper levels ofnonfunctional properties (NPFs). A companythat focuses on service-oriented architectures(SOA) needs to know what configuration wouldprovide the proper levels for individual servicesif they are deployed in the cloud. In this paperwe present an approach for performanceevaluation of cloud computing configurations.

While cloud computing providers assure certainservice levels, this it typically done for theplatform and not for a particular serviceinstance. Our approach focuses on NFPs ofindividual services and thereby provides a morerelevant and granular information. Anexperimental evaluation in Amazon ElasticCompute Cloud (EC2) verified our approach.

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31. Providing PrivacyPreserving in cloudcomputing

People can only enjoy the full benefits of Cloudcomputing if we can address the very realprivacy and security concerns that come alongwith storing sensitive personal information in

databases and software scattered around theInternet. There are many service provider in the

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internet, we can call each service as a cloud,each cloud service will exchange data withother cloud, so when the data is exchangedbetween the clouds, there exist the problem ofdisclosure of privacy. So the privacy disclosure

problem about individual or company isinevitably exposed when releasing or sharingdata in the cloud service. Privacy is animportant issue for cloud computing, both interms of legal compliance and user trust, andneeds to be considered at every phase ofdesign. Our paper provides some privacypreserving technologies used in cloudcomputing services.

32. VEBEK: VirtualEnergy-BasedEncryption and Keying

for Wireless SensorNetworks

Designing cost-efficient, secure networkprotocols for Wireless Sensor Networks (WSNs)is a challenging problem because sensors are

resource-limited wireless devices. Since thecommunication cost is the most dominantfactor in a sensor's energy consumption, weintroduce an energy-efficient Virtual Energy-Based Encryption and Keying (VEBEK) schemefor WSNs that significantly reduces the numberof transmissions needed for rekeying to avoidstale keys. In addition to the goal of savingenergy, minimal transmission is imperative forsome military applications of WSNs where anadversary could be monitoring the wirelessspectrum. VEBEK is a secure communication

framework where sensed data is encoded usinga scheme based on a permutation codegenerated via the RC4 encryption mechanism.The key to the RC4 encryption mechanismdynamically changes as a function of theresidual virtual energy of the sensor. Thus, aone-time dynamic key is employed for onepacket only and different keys are used for thesuccessive packets of the stream. Theintermediate nodes along the path to the sinkare able to verify the authenticity and integrityof the incoming packets using a predicted valueof the key generated by the sender's virtual

energy, thus requiring no need for specificrekeying messages. VEBEK is able to efficientlydetect and filter false data injected into thenetwork by malicious outsiders. The VEBEKframework consists of two operational modes(VEBEK-I and VEBEK-II), each of which is optimalfor different scenarios. In VEBEK-I, each nodemonitors its one-hop neighbors where VEBEK-IIstatistically monitors downstream nodes. Wehave evaluated VEBEK's feasibility andperformance analytically and throughsimulations. Our results show that VEBEK,without incurring transmission overhead

(increasing packet size or sending controlmessages for rekeying), is able to eliminate

WirelessComputing

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Title With Abstract - 2011

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