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LBSS: A Lightweight Blockchain-Based Security Scheme for IoT-Enabled Healthcare Environment

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Abstract and Figures

Recently, global healthcare has made great progress with the use of Internet of Things technology. However, for there to be excellent patient care, there must be a high degree of safety for the IoT health system. There has been a massive increase in hacking systems and the theft of sensitive and highly confidential information from large health centers and hospitals. That is why establishing a highly secure and reliable healthcare system has become a top priority. In this paper, a security scheme for the IoT-enabled healthcare environment, LBSS, is proposed. This security scheme comprises three security mechanisms. The first mechanism is based on the blockchain technology and is used for transaction integrity. The second mechanism is used to store the healthcare system data in a secure manner through the distribution of its data records among multiple servers. The third mechanism is used to access the healthcare data after applying a proposed authorization test. To minimize the security overhead, the healthcare data is prioritized in regard to its importance. Therefore, each security mechanism has specific steps for each level of data importance. Finally, the NS3 package is used to construct a simulation environment for IoT-enabled healthcare systems to measure the proposed security scheme performance. The simulation results proved that the proposed healthcare security scheme outperformed the traditional models in regard to the performance metrics.
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Sensors2022,22,7948.https://doi.org/10.3390/s22207948www.mdpi.com/journal/sensors
Article
LBSS:ALightweightBlockchain‐BasedSecuritySchemefor
IoT‐EnabledHealthcareEnvironment
OmarSaid
1,2
1
DepartmentofInformationTechnology,CollegeofComputersandInformationTechnology,TaifUniversity,
P.O.Box11099,Taif21944,SaudiArabia;o.saeed@tu.edu.sa
2
MathematicsandComputerScienceDepartment,FacultyofScience,MenoufiaUniversity,
ShebinElkom32511,Egypt
Abstract:Recently,globalhealthcarehasmadegreatprogresswiththeuseofInternetofThings
technology.However,fortheretobeexcellentpatientcare,theremustbeahighdegreeofsafetyfor
theIoThealthsystem.Therehasbeenamassiveincreaseinhackingsystemsandthetheftof
sensitiveandhighlyconfidentialinformationfromlargehealthcentersandhospitals.Thatiswhy
establishingahighlysecureandreliablehealthcaresystemhasbecomeatoppriority. Inthispaper,
asecurityschemefortheIoT‐enabledhealthcareenvironment,LBSS,isproposed.Thissecurity
schemecomprisesthreesecuritymechanisms.Thefirstmechanismisbasedontheblockchain
technologyandisusedfortransactionintegrity.Thesecondmechanismisusedtostorethe
healthcaresystemdatainasecuremannerthroughthedistributionofitsdatarecordsamong
multipleservers.Thethirdmechanismisusedtoaccessthehealthcaredataafterapplyinga
proposedauthorizationtest.Tominimizethesecurityoverhead,thehealthcaredataisprioritized
inregardtoitsimportance.Therefore,eachsecuritymechanismhasspecificstepsforeachlevelof
dataimportance.Finally,theNS3packageisusedtoconstructasimulationenvironmentforIoT‐
enabledhealthcaresystemstomeasuretheproposedsecurityschemeperformance.Thesimulation
resultsprovedthattheproposedhealthcaresecurityschemeoutperformedthetraditionalmodels
inregardtotheperformancemetrics.
Keywords:blockchain;healthcare;IoT,IoTsimulation;security;IoTsecurity
1.Introduction
Healthcarecanbedefinedasalarge‐scaleecosystemthatincludesmany
components,suchashealthinsurance,medicine,healthfacilities,warehouses,robots,
sensors,andmore.Moderntechnologieshavehadthegreatestimpactonhealthpractices
andhavetransformedthemfromtraditionalpracticestotechnologicalpractices,suchas
monitoringhumanhealthusingsensorsandwearabledevicessuchassmartwatchesand
wristbands.Thismayberequiredforagroupofpatients,suchasthosewithabnormal
bloodpressureordiabetes,whoneedperiodicmonitoringandrapidinterventionby
specialiststofindquickandeffectivesolutions[1,2].
TheInternetofThings(IoT)technologyconnectsagroupofcomputers,tablets,
mobilephones,andotherdevicesthathaveaCentralProcessingUnit(CPU)tohandle
programsorapplications.ThemaingoalofIoTtechnologyistoextendthefunctionofthe
InternetinordertolinkthedeafthingsthatarenotequippedwithCPUs,suchasdaily
livetools,people,medicalequipment,andothertrackingsensors.Accordingly,thereare
manyapplicationsofIoTtechnologyinvariousareasoflife,suchasthemilitary,security,
transportation,andeconomy.Allofthesefieldscontributetotheconstructionofsmart
cities,whichleadstothepromisedgoalofIoTtechnology,whichisasmartworldthat
considerstheentireuniverseasoneentitywithautonomousmanagement(i.e.,without
humanintervention)[3].
Citation:Said,O.LBSS:A
LightweightBlockchain‐Based
SecuritySchemeforIoT‐Enabled
HealthcareEnvironment.Sensors
2022,22,7948.https://doi.org/
10.3390/s22207948
AcademicEditor:JuWookJang
Received:9September2022
Accepted:16October2022
Published:18October2022
Publisher’sNote:MDPIstays
neutralwithregardtojurisdictional
claimsinpublishedmapsand
institutionalaffiliations.
Copyright:©2022bytheauthor.
LicenseeMDPI,Basel,Switzerland.
Thisarticleisanopenaccessarticle
distributedunderthetermsand
conditionsoftheCreativeCommons
Attribution(CCBY)license
(https://creativecommons.org/license
s/by/4.0/).
Sensors2022,22,79482of20
ThereisaboomintheIoTmarketwhichisrelatedtohealthcarebecauseofthe
presenceofhigh‐speedInternet.Thisleadstothecreationoftheappropriateconditions
forhealthcaredevicestoworkandoperateinonebignetworkaswellasforthespreadof
sensorsthatsupportmosthealthcaredevicesandequipment.Furthermore,themedical
environmentisdevelopedtechnologicallyandhumanelytokeeppacewiththis
tremendousdevelopmentintheinformationtechnologyandartificialintelligencesectors.
Moreover,devicesandIoTapplicationsthataregraduallyadaptedtopatientsand
healthcareworkersareclearlyincreasing.Additionally,allcomponentsofhealthcare,
suchaspatientsanddoctors,benefitfromIoTtechnologyanditsapplicationsin
monitoring,tracking,maintaining,treating,andmore.TheIoT‐basedhealthcaresystem
shouldcovermanylocations,whichleadstoahugenumberofcommunicatingdevices
thatproduceamassivenumberofgigabytes.Thedataproducedaretransmittedthrough
manytypesoftransmissionmediaandprocessedbydifferenttypesofusers[4].
SharingdatawithinhealthcaresystemsthatarebasedonIoTtechnologyisan
importantissue.Inthesesystems,thedataisusuallysharedthroughcloud‐computing
technology.Patientdataiscollectedanduploadedtothecloudandisthenavailableto
users.Subsequently,itisdistributedtoauthorizedpersons,suchasspecialistsand
administrators,accordingtothetypeofdataandpatients.Afterthat,aninitialdiagnosis
isproposedandthenatreatmentisprescribedwhereerrors,whichmayarisebecauseof
themanualwritingofdata,areeliminated.Afterward,datamaybesentorreceivedina
real‐timemanner,ifrequired,throughthecloud‐computingservers.Becauseofthe
presenceofsensitivedataonthecloud,itmaybeinsecureforseveralinternalorexternal
reasons.Forexample,theauthorizedpersonstomanagethehealthdatacentersmaybe
dishonestandtamperwiththisdata.Therefore,thereweregreatsecuritychallengesfor
healthcaresystemsthatdependontheIoTtechnology,whichhasuniquespecifications
suchasamassivenumberofterabytesofdata,alargenumberofcloud‐computing
servers,theirextensioninmanylocations,andalargenumberofusersandhuge
transactionsthatmayhaveoccurredforhealthdatawithinashortperiod[5].Themain
contributionsofthiswork:
ApplyblockchaintechnologyfordatatransactionintegrityintheIoT‐enabled
healthcareenvironment;
• ProposeasecuritymechanismfordatastoringintheIoT‐enabledhealthcare
environment;
• ProposeasecuritymechanismfordataaccessintheIoT‐enabledhealthcare
environment;
• ConstructasimulationfortheIoT‐enabledhealthcareenvironmentandexaminethe
efficiencyoftheproposedsecurityscheme;
• Finally,showanddiscussthesimulationresults.
Theorganizationofthepaperisstatedasfollows:Section2introducestherelated
works.Section3demonstratesthedesignoftheproposedsecurityscheme.Section4
presentsthesimulationconstructioninadditiontothediscussionoftheresults.Finally,
thepaperisconcludedinSection5.
2.RelatedWorks
ThispaperfocusesonthesecurityissueforIoT‐enabledhealthcareenvironments.The
research,whichisrelatedtohealthcareandblockchain,isevaluatedregardingfourmain
factors.Thefirstfactoris“IoTRepresentation(IoTRep.)”,whichevaluatesiftherelated
workrepresentedtheIoTenvironmentaccurately.Thesecondfactoris“IoTSuitability
(IoTSut.)”,whichevaluatesiftherelatedworkwassuitablefortheIoTenvironment.The
thirdfactoris“SecurityWeakness(SW)”,whichevaluatesiftherelatedworkhadsecurity
weakness(es).Thefourthfactoris“Review(Rev.)”,whichmeansthattherelatedwork
wasjustareviewarticle.TherelatedworksareevaluatedandcategorizedinTable1.
Sensors2022,22,79483of20
Table1.Summaryoftherelatedworks.
AuthorsYearRef.Contributions
LimitationFactors
IoT
Rep.IoTSut.SWRev.
Wangetal.2020[6]
Proposedasecuritymechanismforhealthcare
systems.Thismechanismcombinedtheedgecloud
andIoTtechnologiestosecuretheretrievalofdata.
✓✗✓✗
Fotouhietal.2020[7]Introducedanauthenticationschemetoprevent
attackstargetedatwirelessbodyareanetworks. ✓✗✗✗
Wangetal. 2020[8]
Demonstratedaparallelhealthcaresysteminwhich
theblockchaintechnologyandcareauditabilitywere
applied.
✓✗✗✗
Ismailetal.2019[9]
Introducedablockchainsystemforhealthcare
environments.Itdividedthenetworkintoclustersto
applyitssecuritymodel.
✓✗✓✗
Haghparastetal. 2020[10]
ProposedasecurityframeworkforIoT‐basede‐health
systems.Thisframeworkconsistedoffourlayersof
sensors.Eachlayerachievedfunction(s)fromthe
frameworktarget.
✓✗✗✗
Gupta2017[11]
Demonstratedageneralizedarchitectureforthe
securityandmanagementofcloudserversinIoT
healthcaresystems.Itdividedthecloudcentersinto
threecategoriestoguaranteethesecure
communicationofinformation.
✓✗✗✗
Ning,etal.2021[12]
Demonstratedablockchainframeworkfordistributed
trafficmanagementintransportationsystems.It
analyzedthisframeworkintotwosub‐problemsto
decreaseitscomplexity.
✓✗✓✗
Lakhanetal.2022[13]
Identifiedandensuredthefraudofmedicaldatain
additiontoprivacypreservationatlocalfognodes
andclouds,withminimumdelayandenergy
consumption.
✓✗✓✗
Manoharanetal.2022[14]
Presentedamodeltoanalyzethebiomedicalsignals
behaviorandcompletetheoutputtracking
mechanismofthetransceiverresultswithlowpower
consumption.
✓✗✓✗
Selvarajan,etal.,2022[15]
Introducedasystemtominimizethelossof
functionalitiesinthebiomedicalsignals.Additionally,
anactivationfunctionwaspresentedinthemiddle
stage.
✓✗✓✗
Anithaetal.2021[16]
Proposedasecuritymethodthatdetectedthe
replicationattack.Thissecuritymethodwasforthe
healthcaresystem,whichwasbasedonaWireless
SensorNetwork(WSN).
✗✓✓✗
Beniletal.2020[17]Demonstratedasecurityschemetoverifyandaudit
medicalcloudserversusingblockchaintechnology. ✗✓✗✗
Kongetal.[11]2019[18]
Introducedasecuritymodelusinganeuralnetwork
andthepre‐classificationofhealthdataanddynamic
gamingtheory.
✗✓✗✗
Wangetal.[12]2020 [19]Introducedasecurityframeworkusedtoevaluatethe
securityspecsofInternetofHealthThings(IoHT).✗✓✗✗
Sensors2022,22,79484of20
AbouNassar et
al.2020[20]
Proposedasecuritymodelbasedonblockchain
technology.Itusedasmartcontracttoenhancethe
TrustworthyFactor(TF)andestablishtrustworthy
communicationsintheIoHTinfrastructure.
✗✓✗✗
Kavithaetal.2019[21]
Introducedasecurityframeworktodealwiththe
securityflawsofthepersonaldatarecords,which
werefoundinhealthcaresystems.Itusedthe
hyperellipticcurve‐basedpublickeycryptosystem
insteadofthetraditionalcryptographicframeworkto
ensurethegroupcommunicationsweresecure.
✗✓✗✗
Tai2019[22]
IntroducedasecuritymodelforIoThealthcaredatain
whichthecontroloperationsfortheIoTsystemwere
adjustedandtheuseranonymityisconsideredto
introduceanauthenticationmodel.Additionally,the
controlsystemforIoThastheabilitytoensurereliable
e‐Healthservices.
✗✓✓✗
Pawaretal.2018[23]
Demonstratedasystemmodelthatwasbasedonthe
blockchaintechnologytomanagethehealthdatathat
wereobtainedfromthemedicaldevices.
✗✓✗✗
Hasanova,etal.2022[24]
Presentedanalgorithmthatwasbasedonmachine
learningtechnologytopredictheartdiseasesusingthe
blockchaindata.
✗✓✗✗
Marwanetal.2018[25]
Proposedasecuritymethodtopreventunauthorized
usersfromaccessinghealthcarerecords.Thismethod
usedmachine‐learningtechnology.
✗✗✓✗
Dingetal.2019[26]
Introducedasecuritysystemthathandlesthelimited
capabilitiesofsensors.Italsoverifieddataintegrity
andreducedthecomputationoverheadcost.
✗✗✓✗
Lietal.2020[27]
Introducedaframeworktoapplytheblockchain
technologytoguaranteesecuredatasharingin
additiontocomputingthesensitivedataofpatients.
✗✗✓✗
Vedarajetal.2020[28]
Providedaneffectivesecurityframeworkforthe
healthdatainadditiontopredictingthepatients’
diseases.Additionally,itcanencryptanddecrypt
usingaspecialsecurityalgorithm.
✗✗✓✗
Wangetal.2021[29]
Introducedasystemtoquantifythefreshnessof
informationusingcritical‐levelchanges.Itwasan
optimizedproblemofminimizationoftheAge‐of‐
Critical‐Information(AoCI).Furthermore,an
information‐awareheuristicalgorithmwas
introduced.
✗✗✓✗
Ning,etal.2021[30]
UsedUnmannedAerialVehicles(UAV)toinvestigate
Multi‐accessEdgeComputing(MEC)thatconsidered
edgeserverdeploymentandoffloadingcomputation.
Moreover,twolearningalgorithmswere
demonstratedtoreachtheNashEquilibrium(NE).
✗✗✓✗
Zarouretal.2015[31]
Introducedastudytodeterminetheimpactofusing
blockchaintechnologyonthehealthcaresystemfrom
groupsofexpertsandspecialists.
✗✗✗✓
Sensors2022,22,79485of20
Sharmaetal.2022[32]
Introducedaliteratereviewoftherelationship
betweentheblockchaintechnology,IoTtechnology,
andthehealthcaresystem.
✗✗✗✓
3.ProposedSecurityScheme
Theproposedsecurityschemeprovidedthreesecuritymechanisms:integrity,
confidentiality,andavailability.Theintegritymechanismensuresthatthehealthcaredata
transactionsareaccomplishedcorrectly;seeSection3.1.Theconfidentialitymechanism
guaranteesthatthoseauthorizedtodosocanonlyaccesssensitivehealthcaredata.The
availabilitymechanismguaranteesthatthehealthcaredatashouldbeavailabletothose
whoneedit;seeFigure1.Forconfidentialityandavailability,seeSection3.2.
DB1 DB2 DB3
User
Data Access Data Store Data Trans action
Distributed Databases
Healthcare IoT System
Figure1.Thethreemechanismsoftheproposedsecurityscheme.
OneofthechallengesofIoTtechnologyisscalability,whichcausesahugenumber
ofheterogeneousthingstosuddenlyjoinorleavethisenvironmentinadditiontoa
massivenumberofterabytesofexchangeddatawithinshortperiods.Tofacethese
challengesintheproposedsecurityscheme,theIoT‐basedhealthcaresystemisdivided
intomanyclusters.Eachclustermaycompriseheterogeneousorhomogenousthings
(devices,tools,andusers).Theclusteringprocessisachievedbasedonavailablenetwork
resources,sizeandtypeoftransmitteddata,numberofthings,andthelevelofimportance
ofthingsanddata.Theclusteringprocess,whichisbasedonconstructingaclustering‐
basedattributeselectionscaleafterpartitioningthetrainingsampleintoanumberof
clusters,isdescribedin[33].
Inthesectionsbelow,thethreemechanismsarediscussedinadditionto
mathematicalnotations.
3.1.Integrity
Thehealthcaresystemcomprisesdifferenttypesofthings.Eachthinghasatypeof
exchangeddata.Therefore,thehealthcareenvironmenthasmanytypesofdatawith
differentlevelsofimportance.Hence,healthcaredataisclassifiedintomanylevels
dependingonitsimportancesuchthateachlevelcanbehandledwithdifferent
procedures[34].Thisconceptcanleadustothecoreideaoftheproposedintegrityfactor,
andtheblockchaintechnologyisusedtoensurethateachtransactioniscorrectlyverified.
First,eachtransactioncanbestoredasablock,eachcontainingthehashfunctionofthe
previousblock.Incaseanytransactionneedstobeaddedtothechain,itshouldbeverified
byagroupofpersonswhicharecalled“miners”.Therearemanymechanismstoprove
thetransaction,suchasProofofWork(PoW),ProofofStake(PoS),andothers[35].As
Sensors2022,22,79486of20
statedpreviously,themainchallengewiththehealthcaresystembasedonIoTtechnology
istheterabytesofdata(stored,exchanged,andprocessed).Thismakestheuseofone
transactionverificationmechanismsodifficult(ifnotimpossible).So,intheproposed
blockchainmechanism,amixtureoftransactionverificationmechanismsisapplied
dependingonthetypeofhealthcaredata(i.e.,importancelevel).Formoreclarification,
theproposedmodelclassifiesthehealthcaredatainto“N”levelsofimportancesuchthat
thefirstlevelisassignedtothemostimportantlevelofdata,thesecondlevelisassigned
tothenextlevelofimportance,andsoon.Thisprovidesflexibilitytocreateotherlevels
ofimportance,especiallyforanIoT‐basedhealthcaresystem.Foranaccurate
determinationoftheimportanceofhealthcaredata,thedatatypeshouldbecombined
withthething’sstate.Forexample,incaseofdanger,apatient’sstatus,suchascancer
patients,prescriptions,andprescriptionchanges,willhavetobecompletedinanaccurate
mannerandunderthesupervisionofanexpert(i.e.,inmostcasesspecialistsarenecessary
butinsufficient).Onthecontrary,apatientundergoingasimplegeneralsurgerymust
haveaccurateanesthesiacalculations.
Toclarifythemodelidea,threelevelsofimportanceareusedandappliedfordata
andthings.Thesethreelevelsofimportancearecritical,middle,andtraditional.Thefirst
levelofimportanceisassignedtothedatapackage,whichcomprisesthecriticalthings
describedbycriticaldata.Thesecondlevelofimportanceisassignedtothedatapackage,
whichcomprisesthecriticalthingsthataredescribedbythedataofmiddleimportancein
additiontothecriticaldata,whichisrelatedtothethingsofmiddleimportance.Thethird
levelofimportanceisassignedtothedatapackage,whichcomprisesthethingsofmiddle
importancethatarerelatedtothedataofmiddleimportance,thedataofmiddle
importancethatisrelatedtothetraditionalthings,thethingsofmiddleimportancethat
arerelatedtothetraditionaldata,andthetraditionaldatathatisrelatedthetraditional
things;seeFigure2.
Critical
Middle
Importan ce
Traditional
Critical
Middle
Importan ce
Traditional
Things
Data
Figure2.Thelevelsofdataimportancefordatacombinedwiththings.
Theimportancelevelofdatamaybechangedbyatimeperiod.Forexample,the
timingofbloodpressuremeasurementforahypertensivepatientissometimescrucial.
Thisisbecauseitcanbeperformedasaroutineorconsideredanimportantissuetothe
pointwhereitmaysavethispatientfromdeath.Inaddition,acertainresultfromforensic
medicinemaybeusedincourtandchangethedirectionofjudgment,oritmaybeused
onlyforexperiments.
Theclassificationofthingsanddatashouldbeachievedbyahigh‐levelcommittee
whichisconstructedbyanelectedadministrationinthehealthcaresystem.Theoutputof
theclassificationprocessmaybechangedbyachangeofcommitteeorovertime.
Changingthespecialists’committeemayaffecttheoutcomeoftheclassificationprocess
becauseeachspecialisthasapointofviewabouttheimportanceofthingsanddata.For
Sensors2022,22,79487of20
example,therearespecialistswhoconsiderthedataofthemedicalanalysisforaparticular
diseasetobeveryimportant,andotherspecialistsmayconsiderthisdataastraditional.
Inaddition,thetimefactorisimportantinchangingtheresultoftheclassificationprocess,
assomedataatacertaintimecanbeconsideredimportant,whilethesamedataatanother
timemaybecomeunimportant.Therefore,theprocessofthingsanddataclassification
maybedynamicallychanged.
Eachlevelofimportanceshouldhaveagroupofminers.Theseminerscanbeelected,
oritispossibletoappointthemaccordingtotheprotocolorregulationsatthehospital.
Forexample,theheadoftheoncologydepartment,theheadofthenarcoticsdepartment,
thedirectorofthehospital,theheadofthementalhealthdepartment,thephysician,and
thepharmacistinchargeofdrugsinthehospitalmaybeconsideredminerswhoverify
thedrugtransactions.Thisideaprovidesscalability,whichisoneofthechallengesof
blockchainsuchthat,incaseofanextensionofhealthcaredata,thenumberofminers
shouldbedecreasedtoincludethemostexperiencedspecialistsandhigh‐levelmanagers
forcriticalcases.Todifferentiatebetweentheoldsecuritysystems,whichverifythe
transactionthroughalltheavailableminers,andourproposedscheme,theminersshould
beselectedfromdifferentorganizationsinvariouslocations.Thisminerselectionrule
camefromIoTenvisioning(i.e.,thehealthcaresystemthatisbasedonIoTtechnology
transformsmanyhealthorganizationsintoonelargeorganizationtoprovidean
advantageinselectingminersfromdifferentcountries,whichgivesthetransaction
verificationprocessmorecredibilityandsecurity;seeFigure3).Asstatedinthebitcoin
blockchainsystem[36],thedataisdividedintoblocks.Eachblockcomprisesagroupof
controlfieldsinadditiontothedata.Oneofthemostimportantfieldsinthedatablockis
thehashfunction.Eachdatablockhasahashfunctionfromthepreviousblock.Inthe
proposedscheme,ahashfunctionisusedtocondenseeachtransaction.
TrBlock1TrBlock2TrBlockN‐1
Prioritizer
123
TrBlockN
Blockchain System
Verificat ion
Random Selection
Blo ckc hain A pplyin g
AllPredeterminedMinersSelectedMiners
Tr=Transaction
Figure3.Dataprioritycenter,datablocks,andminers’relationship.
Thisfunctioniscomplexbecauseitconsistsofanumberofsimplehashfunctions.
Thecomplexitydegreeofthehashfunctiondependsonthedataimportancelevelon
whichthetransactiontookplace.Thenumberofsimplehashfunctionsequalsthenumber
ofminerswhoareauthorizedtocheckthetransactions.Everyminerprovidesthesystem
withitssimplehashfunctionincaseoftheiragreementonthetransaction.
Thecompletionoftheapprovalbyalloftheminersmeansthatthesimplehash
functionsarecollectedtocreatethecomplexhashfunctionwhich,inturn,isusedtotest
whetherthetransactionisacceptedornot.Ifoneminerdoesnotpassthetransaction,then
theirsimplehashfunctionisnotsenttothesecuritysystem.Therefore,thecomplex
functionwillbeconsideredincomplete,whichmeansthetransactionisrejected.Thereis
Sensors2022,22,79488of20
acomplexhashfunctionthatisassignedtoeachtransactionblocksuchthateachminer
usesadifferentsimplehashfunctiontotestthecurrenttransactionandaccesstheold
complexhashfunctionsinadditiontotheiroldsimplehashfunctionstoreviewtheold
transactions;seeFigure4.Thesimpleandthecomplexhashfunctionsarecreatedusing
the“HashFunctionCreator”component.Forfurtherdescription,seeAlgorithm1.
TrBlock1TrBlock2TrBlockN‐1
ComplexHash
Simple Hash1
Simple Hash2
Simple Hash 3
TrBlockN
Hash Functions’ Creato r
Tr=Transaction
Figure4.Usingsimpleandcomplexhashfunctions.
Algorithm1:TransactionIntegrity
DIDataImportance
LImportanceLevel
nNumberofImportanceLevels
HTrHashedTransaction
HCComplexHash
mNumberofMinors
HSSimpleHash
SSSecurityServer
AlgorithmBegin
1:DI=L[i],1<i<n
2:Fori=1toL
3: Begin
4: HTr=HC[i](Tr)
5: HC[i]=∑𝐻󰇟j󰇠

6: Forj=1tom
7: mj→𝐻󰇟j󰇠
8: While(Tr) 
9: Begin
10: mj→ 𝐻󰇟j󰇠→𝑆𝑆
11: SS=𝐻󰇟j󰇠𝐻
󰇟j1󰇠…𝐻󰇟m󰇠
12: IFSS=∑𝐻󰇟j󰇠
 
13: Tr→ 𝑆𝑢𝑐𝑐𝑒𝑒𝑑
14: Else
15:  Tr→𝐹𝑎𝑖𝑙𝑒𝑑
16: End
17: End
18:EndAlgorithm
Sensors2022,22,79489of20
3.2.ConfidentialityandAvailability
Oneofthemostimportantsecurityissuesinthehealthcaresystemistheprotection
ofdatafromunauthorizedviewingoraccessing.Additionally,theproposedsecurity
schemeshouldguarantee,forauthorizedusers,accesstothesystem’sresources.In
traditionalhealthcaresystems,thedatathatbelongstoahealthcareorganizationisstored
onitsserversascompleteunits,whichmeansthateverythingrelatedtoaspecificpatient
isstoredasagroupofrecordsinonestoragedatabaseunit.Thismeansanybreachinthe
securitysystemmayallowaccesstopatients’records.Toavoidthissecurityweakness,
theproposedschemeusedthedatafragmentationidea.Thepatient’sdataistransformed
intoagroupofrecords,andeachpatientrecordisdividedintoagroupofblocks.These
blocksaredistributedbythe“distributer”componentoverdifferentserversinsideor
outsideoftheorganization;seeFigure5.
Server1Server2ServerN
User
Laptop
Storing of Data Parts in Different DB Servers
Data Slicer
Data Parts
Assembler
Data Parts
Distributer
Data Part Vs. Server Mapping Codes
Transaction Integrity
(Blockchain)
Figure5.Thegeneralviewofdatadistributionoverservers.
Todecreasetheoverloadoftheproposedmechanism—inthecaseoflower‐
importancedata—itsrecordswillbedirectlydistributedoverthedatabaseservers
withouttransformationintoblocks.Therefore,the“prioritizer”componentshouldbe
consultedtodeterminewhatwillbeconductedinthedatafragmentationbythe“slicer”
component;seeFigure6.Thefunctionofthe“prioritizer”componentisachievedusing
thetechniquestatedin[37] whichusedthequeueingtheory byassigningonequeuefor
eachimportancelevel.Thedataineachqueueisprocesseddependingonavailable
resourcesintheentiresystem.
Eachblockofdatacomprisesastampofitsrelatedpatient.Thisstampmaybea
picture,anumber,orasymbol.Theprocessofchoosingthestamptypeshouldtakeinto
accountthatitdoesnotrepresentanexcessiveoverloadonthepacketorincreaseits
complexity.Thisstampisdynamicallyexchangeddependingonthenetworkstatus(i.e.,
availableresources).Therefore,thestampmaybefirstselectedasanumber.Then,its
difficultyisincreasedbytheselectionofamorecomplexform,suchasagroupof
characters.Afterthat,itistransformedintoapictureandmaybereturnedtoasimple
formagain.Thisstampisusedbythe“assembler”componenttocollectthedatarecord
afteritsfragmentation.The“assembler”dataisencrypted.Therequesttoaccessdatais
senttotheadministrator,who,inturn,contactsthe“prioritizer”askingaboutthe
importanceleveloftherequireddata.Then,theadministratordeterminesthe
requirementsforthisdatatobeaccessed.Afterthat,theadministratorcontactstheuser
askingabouttherequireddataauthorization.Regardingthecorrectinputofthedata
Sensors2022,22,794810of20
authorization,theadministratorcontactsthe“assembler”tocollectthedataandsendsit
totheintendeduser;seeFigure7.Communicationbetweenthecomponentsofthe
proposedsecurityschemeisachievedusingmanagementmessages.Thestructureofthese
messagesissimilartothemessagesoftheSimpleNetworkManagementProtocol(SNMP)
[38].Eachmanagementmessageissimple.ItcomprisesthesourceanddestinationIP
addressesinadditiontotherequiredfieldssuchasvariablesandtheirvalues.These
managementmessagesareencrypted.Intheeventofnetworkstarvation,thenumberof
managementmessageswillbedecreaseduntilthenetworkisreturnedtoitsnormalstatus.
Therearetwotypesofmanagementmessages.Thefirsttypeiscalled“query”andisused
toaccessspecificvariables’values.Thesecondtypeiscalled”response”andisusedto
sendspecificdatatooneormoreschemecomponents.
Data Slicer
Prioritizer
123
User
Send Data
Data Parts
Distributer
Sends Data
Parts
Administrations
Data Priority
Decision
Figure6.Prioritizerandslicerrelationship.
Laptop
Data Parts
Assembler
Prioritizer
12 3
Administrations
Authorization Test
Figure7.Healthcaredataaccessmechanism.
Theauthorizationdataisdirectlyrelatedtoitsimportancelevel(i.e.,the
authorizationdataischangedbyadjustingtheimportancelevel).Theapplicationofthis
ideainourproposedsecurityschemecanbestatedasfollows:Eachdatablock(orrecord)
comprisesadigitalsignatureoftheauthorizedusers.Whentheauthorizeduserneedsto
accessahealthcaredatarecord,thesystemshouldreceivethedigitalsignatureofthat
user.Tobemoreaccurate,asstatedpreviously,thereareseverallevelsofimportancefor
healthcaredata.Therefore,eachlevelofimportanceforthedatawillhaveadifferent
Sensors2022,22,794811of20
securitymechanismthatshouldbeappliedforanaccessrequest.Inthecaseofdatawith
ahighdegreeofimportance,allusers’electronicsignaturesmustberequiredtoaccess
suchdata.Hence,theuserwhosendsanaccessrequesteitherentersallofthedigital
signaturesfortheuserswhoareauthorizedtoaccessthistypeofsensitivedata,orthis
userhasapriorauthorizationdeedfromthoseusers.
Inthesameway,electronicsignatureswillbereducedaccordingtoareductioninthe
levelofimportancefortherequireddata.Additionally,eachusershoulddetermine
his/hersecuritybehavior,definedbytheregularstepsthataremostlyaccomplished
withinaspecifiedtime[39].Thissecuritybehaviorwillbeappliedasanadditional
securitystepforthemostimportantdata.So,iftheunauthorizedusertriestoaccessdata
andknowsthedigitalsignaturesofalloftheauthorizedusersrelatedtothatdata,this
unauthorizeduserdoesnothaveknowledgeoftheirregularbehaviors.
3.3.MathematicalNotations
Thismathematicalnotationisbasedon[40].Supposethatthenumberofminers
equals“M”,where“L”isthenumberoflevelsofimportance.Thecontentsofeachdata
block“DC”aredeterminedusingEquation(1),where“BPrev”isthepreviousblock,“H”is
thehashfunction,“TS”isthetimestamp(currenttime),“b”istheworkproofdifficulty,
and“G”isthetarget.The“Merkletree”and“nonce”areomittedfromthecontentsofthe
block.Thisisbecausethetimerequiredtotestthetransactiondependsonthe
predeterminednumberofminerswithsimplehashescreatedbytheproposedsecurity
scheme.Thevalidityofthetransaction“TV”isdeterminedbyEquation(2),where“P”is
thenumberofblocksrevisedbytheminers.Thetimerequiredtoaddonetransactioninto
thechain“TT”isdeterminedbyEquation(3).Theconsumptiontime“CT”istoensureall
systemtransactionsaredeterminedusingEquation(4),wherethenumberoftransactions
equals“T”.Theminerisselectedfromagroupofpredeterminedpersons.Additionally,
𝑀𝑁󰇟𝑖󰇠isthesetofminers,and“𝑀𝑁𝑆”istheselectedminers.Theminers“MS”are
determinedusingEquation(5).
𝐷=(H(𝐵 󰇟󰇠)
⊕
TS(t)
⊕
b)𝐺, 1<a<P(1)
𝑇∑∑𝐻 󰇛󰇛𝐻󰇛𝐵󰇜 ⊕𝑇𝑆󰇛𝑡󰇜 ⊕𝑏󰇜󰇜

 ,0<i<L (2)
𝑇𝑃∗∑𝑇
  (3)
𝐶∑∑
󰇛𝑃∗∑𝑇


 󰇜 (4)
𝑀󰇛󰇟󰇠󰇜 ∗ 𝑀𝑁󰇟𝑖󰇠𝑀𝑁𝑆
󰇛󰇟󰇠󰇜 (5)
4.SimulationandEvaluation
Thesimulationconstructionprocessforthehealthcareenvironment,whichisbased
onIoTtechnology,isdemonstratedinthefirstsection.Additionally,theresultsofthe
simulationareshownanddiscussedinthesecondsection.
4.1.SimulationInfrastructure
ThemainchallengewithIoT‐basedhealthcaresystemsishowtorepresentthenature
oftheIoTenvironment.So,thesimulation,statedin[41],isthemostsuitabletoreflectthe
realspecificationoftheIoTenvironment.Thisisbecauseitcomprisesapresentationof
threemainnetworks:WSN,Radio‐FrequencyIdentification(RFID),andMobileAdhoc
Network(MANET).ThesenetworkscommunicatewitheachotherusingtheInternet,
whichisalsodemonstrated.Moreover,thissimulationusedtwoalternativecoverage
methods:satelliteandHigh‐AltitudePlatform(HAP).Thesecoveragemethodsareused
incaseoflimitationintheInternetcoverageforagroupofthings.Thiswillprovidethe
healthcaresystemwithrepresentationflexibilitythroughtheconsiderationofthemany
heterogonousthingsthatarefoundatmanylocationswithaguaranteethatthesethings
Sensors2022,22,794812of20
willbecommunicated,eveniftheyarepassivethings.Thesimulationscenario,inaddition
totheparameters’valuesforthenetworksandcoveragetools,isstatedinFigure8.
Figure8.Simulationscenariowithnetworksandcoveragetoolsparameters.
Thecommunicationbetweendifferentpackets’headerformats,whichareraiseddue
totheusageofdifferentnetworktypes,isachievedusingthepackettransformationidea.
Simply,thisideaisdiscussedasfollows:encapsulatethereceivedpacketwiththeheader
thatissuitableforthereceivednode.Hence,thisnodecantranslatethispacket.Inthe
eventthatthenextnodehasthesametypeasitspreviousnode,theadditionalheaderwill
remain(i.e.,noencapsulation).However,ifthenextnodeisdifferent,theheaderwillbe
de‐capsulatedandanotherheaderwillbeaddedintheeventthatthereceivednodeisa
newone.
Thesimulationmodel,whichisusedtomeasuretheperformanceoftheproposed
securityscheme,representedthenatureoftheIoTenvironmentandisconsideredthefirst
partofthesimulationinfrastructure.So,somechangesareaddedtothissimulationmodel
tocompletetherepresentationoftherealnatureofhealthcaresystems,whichis
consideredthesecondpartofthesimulationinfrastructure.Thesechangesareconcluded
inTable2.Theselectedhealthcaredevicesarethemostcommonones,suchassurgery
roboticsandglucosemonitoringformedicaldevices,laptops,andbarcodereadersand
monitoringforinventoryaswellaschemicaldevicesandlaptopsforpharmacy.Each
devicecanbeconsideredpassiveoractive.Thepassivethingsarethethingsthatarenot
supportedbyaCPU.However,theactivethingscanconnecttotheInternet(oranyother
coveragetool)withoutadditionalhardwaresupport.Furthermore,thethirdpartofthe
simulationinfrastructureisrelatedtotherepresentationofsecurityspecifications,which
arestatedinTable3.Thesimulationofmedicaldevicesistakenfrom[42–44].Notably,
mostofthehealthcaresecurityparametersarerandom,rangedvaluesforanaccurate
representationoftheIoTenvironment.
Sensors2022,22,794813of20
Table2.Representedhealthcaretoolsinthesimulationenvironment.
PartDescriptionUsedNetwork
Patients
Wearabledevices(glucometer,fitnessbands,heartrate
monitoringcuffs,ingestible,andbloodpressure),RFID
tags,mobiles,andsmartwatches
WSNandRFID
andMANET
Physicians
RFIDtags,mobiles,sensors(monitoringandmedical),
clothes,cars,keys,sonar,surgicaltools,laparoscopes,
respiratorydevices,emergencydevices,etc.
WSNandRFID
andMANET
Inventories
RFIDtags,sensors(weight,temperature,motion,
monitoring,andhumidity),cargo,lamps,workers,
books,offices,etc.
WSNandRFID
Pharmacy
RFIDtags,sensors(temperature,touch,motion,
monitoringandhumidity),mobileapplications,
refractometer,thermometer,microscope,vacuumoven,
etc.
WSNandRFID
andMANET
Insurance
Company
RFIDtags,sensors(temperature,monitoring,and
touch),andselectedinsurancecompanydevices WSNandRFID
Table3.Securitysimulationparameters.
PartDescription
HashSecureHashAlgorithm(SHA)‐256
Blocksize1MB
NumberofclustersRandom(10to100)
ClustersizeRandom(50to100)
TotalnumberofminersRandom(10,000to200,000)
NumberofselectedminersRandom(10to50)
NumberofblocksRandom(144to288)
ImportanceofblockRandom(1/2H:1/4M:1/4L)
NumberofdigitalsignaturesRandom(1to10)
TotalnumberofnodesRandom(20,000to40,000)
4.2.ResultsandDiscussion
Theperformancemetricsareprocessingtime,thenumberofminers,averageenergy
consumption,averagethroughput,averageend‐to‐enddelay,packetlossratio,theaccess
timeofhealthcaredatarecords,andrateofchangebetweendatablockswithdifferent
levelsofimportance.ThesimulationresultsofLBSSarecomparedwiththeLeila’smodel
andtheBitcoinmodel[19,31].TheBitcoinmodelwaschosentocompareitsresultswith
theresultsoftheproposedsecurityschemebecauseitisoneofthemostimportantmodels
thatusestheblockchaintechnology.Inaddition,theLeila’smodelwaschosenbecauseit
istheclosestrelatedworktoourproposedsecurityscheme.
Theprocessingtimeperformancemetriccanbemeasuredusingaconsumptiontime
tovalidatethetransactions,whicharerepresentedbyblocksintheblockchainsystem.
Figure9showstheprocessingtimeresultsforthesecurityscheme,theLeila’smodel,and
theBitcoinmodel.Thex‐axisrepresentsthenumberofblocks(transactions)andthey‐axis
representstheprocessingtime(seconds).Notably,LBSShasthelowestprocessingtime
values.TheLeila’smodelandtheBitcoinmodelrankafterLBSS.Thisisexplainedbythe
classificationofhealthcaredataintomanylevelsofimportance,whichdecreasesthedata
processingrequirementsandleadstoreducedtimeconsumption.
Sensors2022,22,794814of20
Figure9.Processingtimefortransactionintegrity.
ThenumberofminersperformancemetricismeasuredforLBSSandtheBitcoin
model.ThisisbecausethenumberofminersmetricfortheLeila’smodelhasthesame
behaviorastheBitcoinmodel.Thisperformancemetricismeasuredusingthecalculation
oftheaveragenumberofminers,whichareusedtovalidatethedatatransactions.Figure
10showstheresultofthechangingminerperformancemetric.Thex‐axisrepresentsthe
simulationtimeinminutesdividedbytenandthey‐axisrepresentsthenumberofminers
dividedby104.Thenumberofminersintheproposedsecurityschemeislessthanthatof
theBitcoinmodel.Thisisbecausethedataclassificationminimizesthenumberofminers
incasetherearelessimportantdatatransactions.
Figure10.Changingthenumberofminersoveratime.
Theenergyconsumptionperformancemetricismeasuredbytheaverageofthe
energyconsumptionvaluesfortheenergy‐basedhealthcarethingsintheIoT
environment.Thisperformancemetricdeterminestheeffectoftheproposedschemeon
theenergy‐basednodes.Figure11showstheresultsoftheenergyconsumption.Thex‐
axisrepresentsthesimulationtimeinminutesdividedbytenandthey‐axisrepresents
theaverageoftheenergyconsumptionin“Joules”.TheplotofLBSShasthelowestvalues
forenergyconsumptionwithinthesimulationtime.TheLeila’smodelandtheBitcoin
modelcomeaftertheproposedsecurityscheme,respectively.Thisisexplainedbythe
availabilityofLBSStodecreasetheoverheadcomputations,whichlowertheenergy
consumptionrates.
Sensors2022,22,794815of20
Figure11.Energyconsumptionaverage.
Thethroughputperformancemetricismeasuredbycalculatingthesizeofthedata,
whichistransmittedandreceivedcorrectly.Thisperformancemetricalsoreflectsthe
effectoftheproposedsecurityschemeontheefficiencyoftheIoTenvironmentbecause,
iftheproposedschemecausesacomputationoverloadonthehealthcaresystem,thefirst
metricthatwillbeaffectedisthesizeofthecorrecttransmitteddata.Figure12showsthe
resultsofthethroughput.Thex‐axisrepresentsthesimulationtimeinminutesandthey‐
axisrepresentstheaveragethroughputin“kb/s.”dividedby107.Notably,thethroughput
plotofLBSShasthehighestvaluescomparedwiththatoftheLeila’smodelandtheBitcoin
model.Thisisexplainedbytheabilityoftheproposedsecurityschemetoreducethe
numberofcomputationswhenthereisanoccurrenceofbottlenecksorcollisions.
Additionally,boththeclusteringideaandthenumberofminersaffectthethroughput
performancemetric.Theclusteringidea,whichisappliedtoLBSSandtheLeila’smodel,
reducestheircomplexityandincreasestheirthroughput.However,inLBSS,reducingthe
numberofminersleadstoareductioninthenumberoftransmittedmessages,including
messagesrelatedtothesecuritysystem.Italsoleadstoadecreaseinthenegativeimpact
ofhashfunctions’usagethatcontributestoanadditionalincreaseinthethroughput,
whichwasnotpresentinothermodels.Furthermore,classifyinghealthcaredatainto
severallevelsofimportanceisconsideredthemainfactorindeterminingthebehaviorof
LBSSandmakingitmoreflexible.
Figure12.Throughputaverage.
End‐to‐enddelayisanimportantperformancemetrictomakesurethattheproposed
securitymodeldoesnotnegativelyaffecttheentireIoTsystemefficiency.Thismetricis
measuredbythecalculationoftheaverageofqueuing,processing,andtransmission
Sensors2022,22,794816of20
delays.Figure13showstheend‐to‐enddelayresults.Thex‐axisrepresentsthesimulation
time,andthey‐axisrepresentsaverageend‐to‐enddelay.Notably,theend‐to‐enddelay
valuesfortheproposedsecurityschemearelessthanboththeBitcoinandLeila’smodels.
Inaddition,theBitcoinmodelhasthelargestend‐to‐enddelay.Thisisexplainedbythe
flexibilityoftheproposedschemetodecreasethenumberofsecuritymessagesincaseof
networkstarvation.However,thecomplexityoftheBitcoinmodelissohighthatithas
negativelyaffectedtheIoT‐basedhealthcareenvironmentandincreasedtheaverageend‐
to‐enddelay.
Figure13.End‐to‐enddelayaverage.
Packetlossisalsoaveryimportantperformancemetrictomeasuretheefficiencyof
theIoT‐basedhealthcaresystem.Thismetricismeasuredbytheratioofpacketsthatare
lostduringthetransmissionprocesstothetotalnumberofsentpackets.Figure14shows
thepacketlossratioresults.Thex‐axisrepresentsthesimulationtimeinminutesdivided
byten.They‐axisrepresentsthepacketlossratiovalues.Notably,thepacketlossratiofor
theproposedsecurityschemeislessthanthatofboththeLeila’sandBitcoinmodels.This
alsoreflectstheefficiencyoftheproposedsecurityschemetodynamicallychangeits
behaviordependingonthenetworkstatus.
Figure14.Packetlossratio.
Theaccesstimeperformancemetricequalstheaverageconsumptiontimethatis
requiredtoaccesshealthcaredata.Thismetricmeasurestheperformanceofthedata
accessmechanism,whichisproposedinLBSS.Therefore,itismeasuredforLBSSand
comparedtotheLeila’smodel.Figure15showstheresultsoftheaccesstimeperformance
Sensors2022,22,794817of20
metric.Thenumberofdatablocksisrangedfrom1000to10,000andtheaccesstimeis
rangedfromzeroto9000“ms”.Theaccesstimefortheproposedsecurityschemeisless
thanthatoftheLeila’smodel.Thisisbecausethevarietyofsecurityactionsthatare
executeddependsonthelevelofdataimportanceandtypeofthings.
Figure15.Averageconsumptiontimethatisrequiredtoaccesshealthcaredata.
Forthetransactionswithdataperformancemetricsthathavedifferentimportance
levels,theyaremeasuredbythenumberoftransactionswhichoccurredfordifferent
levelsofdataimportance:high,medium,andlow.Thisismeasuredtoensurethatthe
changesbetweenthelevelofdataimportanceworkeffectively.Figure16showstheresults
ofthisperformancemetric.Thex‐axisrepresentsthesimulationtimeinminutesdivided
bytenandthey‐axisrepresentsthenumberoftransactionblocks.
Theimportancelevelsaredistributedbetweenhigh,medium,andlow.Additionally,
thenumberoftransactionblocksismostlyarrangedinascendingorder:low,medium,
andhigh.Inthefewsimulationtimepoints,thehighimportancelevelincreasesthe
mediumimportancelevel,whichreflectstherealnatureofthehealthcareenvironment
andcomprisesoccasionallyimportantdata.
Figure16.Numberoftransactionswithdifferentlevelsofimportance.
AsshowninTable4,thesimulationresultsprovedthattheproposedsecurity
scheme,LBSS,outperformedtheperformanceoftherelatedmodels,theBitcoinmodel
andtheLeila’smodel.

Sensors2022,22,794818of20
Table4.ConclusionofLBSSenhancementscomparedtobothoftheLeila’sandBitcoinmodels.
PerformanceMetricEnhancement
TheaverageprocessingtimefortransactionintegrityDecreasedby≈22.727%↓—Leila’smodel.
Decreasedby≈34.349%↓—Bitcoinmodel
ThechangingrateofminersDecreasedby≈84.821%↓—Bitcoinmodel.
TheenergyconsumptionaverageDecreasedby≈15.752%↓—Leila’smodel.
Decreasedby≈21.367%↓—Bitcoinmodel.
TheaveragethroughputIncreasedby≈28.643%↑—Leila’smodel.
Increasedby≈41.347%↑—Bitcoinmodel.
Theend‐to‐enddelayDecreasedby≈25.865%↓—Leila’smodel.
Decreasedby≈42.171%↓—Bitcoinmodel.
ThepacketlossratioDecreasedby≈27.404%↓—Leila’smodel.
Decreasedby≈43.880%↓—Bitcoinmodel.
TheaccesstimeforthehealthcaredatablocksDecreasedby≈39.189%↓—Leila’smodel.
5.Conclusions
Inthispaper,asecurityscheme,LBSS,wasproposedfortheIoT‐enabledhealthcare
environment.Theproposedsecurityschemedeployedblockchaintechnologytoenhance
integrity,confidentiality,andavailability.Therefore,thehealthcaredatafoundinthe
blockchainwasdifficult(ifnotimpossible)toaccess,change,andstorewithout
notificationandconsensusfromthealltheminersusingsimpleandcomplexhash
functions.Additionally,theproposedschemewaslightweightbecauseitscomplexitywas
decreasedorincreaseddependingonthedataimportancelevel.Moreover,the
performanceofLBSSwasevaluatedusinganIoT‐enabledhealthcaresimulation
environment,andallofitscharacteristicswerepreciselygeneratedusingtheNS3
package.Furthermore,themetricswerechosentomeasuretheperformanceofLBSSin
additiontoevaluatingitsimpactontheentireIoTsystem.Moreover,thesimulation
resultsprovedthatLBSSoutperformedboththeBitcoinmodelandtheLeila’smodel.
Finally,therecommendedareasforfutureworkaredeeperanalysisofthehealthcaredata
todetermineitssensitivity,constructionofadditionalsimulationexperimentstoinclude
othernetworktypessuchascellular,applyingLBSStootherIoTfieldssuchasthemilitary
andagriculture,andcomparingLBSSwithmorecomplicatedsystemssuchasEthereum.
Funding:TheworkwassupportedbytheTaifUniversityResearchersSupportingProjectnumber
(TURSP‐2020/60),TaifUniversity,Taif,SaudiArabia.
InstitutionalReviewBoardStatement:Notapplicable.
InformedConsentStatement:Notapplicable.
DataAvailabilityStatement:Thedatausedinthisstudyiscreatedbythesimulationpackage(NS3).
Acknowledgments:TheauthorextendstheirappreciationtotheTaifUniversityResearchers
SupportingProjectnumber(TURSP‐2020/60),TaifUniversity,Taif,SaudiArabia.
ConflictsofInterest:Theauthordeclaresnoconflictofinterest.
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