• Nu S-Au Găsit Rezultate

View of Security Technique against Power Exhausting Attacks in WSN


Academic year: 2022

Share "View of Security Technique against Power Exhausting Attacks in WSN"

Arată mai multe ( pagini)

Text complet


Security Technique against Power Exhausting Attacks in WSN

Jaya Kaushik 1,Dr. Naresh Grover 2

1Department of ECE, Manav Rachna International University, Faridabad, Haryana

2Dean Academics, Manav Rachna International University, Faridabad, Haryana


Resistant to malware threats is the major difficult problem in WSN. Furthermost important challenge was Rejection of sleep attacks because power is the extremely valuable source for the network. Such type of attacks depletes sensor node power supplies and reduces sensor lifespan. For data transmission between wireless nodes, the most important consideration is power. A DoS attack on a WSN is being contemplated, with the attack affecting the battery life of the devices connecting to the network. The major role of a DoS attack is to reduce the availability of connected devices by shortening their battery life. The connected devices are kept on inactive status which decreases battery life and influences battery management. A novel approach will be used in the proposed work for power management of the connected devices to enhance the battery lifetimes. When either of the connected devices senses low power or is not in operation, it defaults to sleep mode to save battery power. The framework is made vulnerable to such attacks using the methodology discussed, and it also works to detect such attacks and nodes. The description and in-depth understanding of energy exhausting attacks and tactics is a major consideration in the work presented. The RSSI value, in conjunction with route information, is used in the proposed technique to identify malicious nodes and ensure network security. The cluster mechanism is also considered for better and improved performance.


WSN, DoS, Energy Exhausting Attacks, sensor nodes, Intrusion detection, RSSI, Routing protocols


Over the last decade, (WSNs) wireless sensor networks have progressed through a point where they were developedin a technology-based framework to one where there are few broad theoretical considerate problems. WSN is acomplex, self-configuring, and infrastructure-free topology. Since a communication network is made up of manynodes for effective communication, the nodes must be linked using cables in a home network or in an organization,which is expensive, so the wireless network offers a connection-free environment

for effective communication.


[5][6][7],smarthouse[8][9][10],andotherapplicationscanallbenefitfromwirelesssensorsandsecurity becomesmoreessentialfortheintroducedapplications.

Wireless sensors, on the other hand, are vulnerable to malefactors for the numerous reasons: The number of sensorsavailable is limited. WSN systems are still in their development, and as a outcome, the resulting security tools areinsufficient. In certain environments, the security of

information [11] [12] for a long time is important.



lplesstoavariationof security threats. Security is the most significant problem of wireless technology. Thus, it is necessary to look atpotentialattacksagainstwirelessterminals. [13]

The WSN has its significance in all available fields in the physical universe, considering the growing globalrequirements. Aside from sensing in low-power mode, the sensors are utilized in a variety of applications liketemperature tracking, pressure and pollution detection. Most of the time constrained set the SNs in a sleep state toconserve energy, which also raises the nodes' life span. The DoS attacks are those that cause nodes to wake up andaffect the lifespan of nodes. As a result, this study devised a system for dealing with such attacks by detecting non ormaliciousnodes.

The security parameter of the preferred path will be determined for discovering security in WSN, and the state ofgetting malicious nodes will be approximately calculated in the accepted conditions for the assessment of the results.The RSSI value and routing information would be merged to identify suspicious nodes and to validate the attacker'sidentity. During the initial stages of transmission, the route would be properly defined for routing as well as for thecalculation and recording of RSSI values. After that, the network confirms the packet strength from the source nodetoeverynode.

The energy or power of a sensor node(s) (SN) and security issues in WSN are significant because

they support

indefininghowlikelyanetworkistobeusedforfuturecommunicationaswellaspreservingtheWSNsyste m'scompletelifetimeandaccuracy.

Figure1:SensorNetworkArchitecture 2.CharacteristicsofWSN

The mobility, switching character, and battery power are just a few of the characteristics that limits the capacity of awireless sensor networks. WSN has certain unique characteristics when compared to these wireless networks. ThefollowingarethecharacteristicsofWSN[14][15]:

Computing capabilities: Due to cost, size, and battery power usage constraints, the sensor's program andmemorycapacityareseverelylimited.

Energy of battery: As the energy is exhausted, SNs often come to be neglected and invalid. As a result,protocols and algorithms for battery energy conservation should be considered advance. Furthermore, theenergy consumed by the nodes that relay information of data is greater than consumed energy by the nodesthatexecutecomputation.




Communication capabilities: The communication bandwidth of the Senor network is limited and unstableand the communications range is just tens to several hundred meters. Since the natural world, such as hills,houses, and winds, rainfall and lighting, landscape challenges, and weather, would have a strong effect onthe senor. Hardware and software of WSN must be reliable and fault-tolerant, as well as safe, which is aninterestingfutureresearchpath.

Dynamic: Because of the tasks' requirements, certain additional SNs may be moved or

connected to

thenetwork.Asaresultoftheseimprovementsinnetworktopology,theWSNtopologymusthavetheabilit ytoreconfigure,dynamicallyadapt,andself-


No Centre, self-organization: There is no need to install any network infrastructure before deployingwireless sensor nodes. After the nodes are switched on, the sensor node will

easily and efficiently form

anautonomousnetworkbycollaborativelyadaptingitsoutputanddistributionalgorithm.TheWSNisane tworkofpeers.

Multihop communications: In the WSN, a sensor node can only interact with its immediate neighbours. Ifone node must connect with nodes that are outside of radio frequency spectrum of the node, a multihoppathwaymight beappliedtotransmit informationthroughintermediatenodes.


napplications;theirprincipalroleis togatherdataabout

environment.Sincevarioussensornetworksapplicationshandledifferentphysicalsignals,sensornetwo rksprotocolsofroutingcannotbeextendedtoallofthemeffectively.Wirelesssensornetworksareapplicat ionoriented.


Low magnetic, seismic, optical, infrared, thermal, radar and acoustic sampling frequencies are

some of the

sensorsthatcanbeusedinaWSN.Theycantracktheextensivevariabilityofambientcircumstances,inclu dingtemperature,vehicularactivity,pressure,compositionofsoil,monitoringofspecifictypesofobjects ,thelevelofmechanicalstresson the associated objects, and current characteristics such as the object's trajectory, speed, and scale [16]. WSNs aremostlyusedinmilitary, health,home,environmental, andothercommercialapplications[17].


Indoor and outdoor real-time environmental monitoring for uncontrolled wildlife and farmland, health,power, and safety monitoring, monitoring of inventory position, structural, seismic, industrial unit, andautomation process are all examples of monitoring applications. The use of environment monitoring as asecurityandmanagementtoolhasgrowninpopularity,allowingforreal- timesystemandhavelow-cost,andlow energy. It can also be used to keep track of greenhouses, indoor living spaces, woodlands, and climatechange[18].


Target tracking is one of the most fascinating developments in WSNs, as it entails identifying and trackingremote targets. Sensor Nodes detect and communicate the position of movable targets to the application'suser with limited delay. Target tracking has a wide range of real-world applications, including detectingunlawful border crossings, battlefield monitoring, fire spread


identification, gas leak surveillance, andwildlife monitoring. Target tracking may be carried out by a single node or by a group of sensors operatingtogether[19].



regardingenemyactivities, detonations, and other incidents like frontline monitoring, biological,

nuclear, and detection

ofchemicalthreat,andinvestigation[20].Thesensorcanrecognize,differentiate,andidentifythreadsdep endingontheirquantity, number,categorywhetheritisarmouredautomobilesormenonfoot,kind, andweaponsquantitytheyhold,andmanymore.Furthermore,thedevicehelpsintrooppreparationandre actiontimereduction[21].

Environmental Applications

Frommonitoringandregulatingqualityofair,trafficflows,andweatherconditions,WSNdevicecancapt ureand process a huge quantity of information. WSN has been deployed to track animal

movements and

detectenvironmentalconditionsthataffectcropsandlivestockandtoassistpeopleintheirwork.WSNuses includeschemicalandbiologicalidentification,preciseagriculture,biologicalmonitoring,forestfiretrac king,volcanosurveillance,meteorologicalorgeophysicalobservation,flooddetection,andpollutionan alysis [22].


Patients' physiological data could be tracked using body sensor networks. It can identify and monitor agedpeople's actions, such as when a patient has fallen and allow patients greater

freedom of movement

whilealsoassistingphysiciansindetectingsymptomsearlier.Thetinysensorcanalsobeusedtodetectand monitorpatientsanddoctorsinahospital.




The broad range of WSNs applications that make life easier and much cost-efficient. With advances intechnology, SNs able to build into the appliances like microwave ovens, vacuum

cleaners, and

refrigerators.Theywillinterconnectthrougheachotherandtheroomserverandstudyabouttheresourcest heyoffer,suchas copying, faxing, and scanning. These sensor nodes and room servers can be combined with current fixeddevicestodevelopself-regulating,adaptivenetworksandself- organizing,formingasmartecosystem [24].


WSN can effectively track and control traffic conditions. Temporary situations, such asroadwork andaccidents,maybetracked.Itgatherstrafficdataandusestheinformationtocontroltrafficflow.Mosttr afficlightfacilitiesuseatimersystemwithafixedcyclelengththatturnsthelightsonandoffafteracertain amount of time. The concept within intelligent traffic systems is that drivers would not waste time waitingfor traffic signals to change, which could lead to crashes and traffic violations if patience loosed by anydrivers [25].


Three performance metrics are relevant to WSN protocols and applications when it comes to providing security forWSNs. The security method used has no impact on these performance

metrics. Storage is the first, interaction is


thesecond,andcomputationexpenditureisthethird.Thecommunicationcostisthemostexpensiveofallf orWSNs,andthe chosen protection framework should aim to use these terrifying techniques efficiently [26]. Table 1 demonstratessecurityservicesanditsdescriptioninWSN.

Table1:SecurityGoalsinWSN Services Description

Confidentiality[27] The information about the node is kept secret for others while the legitimate users can view the same.Thecapabilityto concealmessagesthroughapassiveattacker.



Thecapabilitytoconformthatinformationhasnotbeendamagedandrequiredt oguarantythedependabilityofthe information.

Authentication [28][29]


Dataverificationensuresthesendersarewhotheysaytheyare.Itindicatesthere liabilityofthemessage.

Validation Tofurnish correctnessofaccesstomanipulateorutilizeresources.

AccessControl[30] Theauthorisation tothesupportsislimited.

Revocation Renunciationofcertificationorauthorization.

Survivability Inthecasewhenthenodeisattackedthenalsothelifetimeofthesameshouldbee nsured.

Non-repudiation[31] therenegeofapreviouscommitment have Prevented.


In the WSN framework the all-time available is the desire of the design so that the services should beavailable all the time are available because of the factors like power available, hardware failure, systemupdations.


Datafreshnessgoal ensuresabout thefreshnessofthepacket receivedat thereceiverend, meaningensuringthatthereceived messageisnotpreviously used.


WirelessSensorNetworks haveseveralsafetyflawsbecauseofwireless medium'sbroadcastand transparentexistence. The given Table 2 describes the list of the most popular forms of attacks of TCP/IP model Attacks onwireless sensornetworksareclassifiedasfollows[33]:

1. AttacksonNetworkAvailability:Anattackeraimstopreventthenetworkfromreceivingservi ces.Adenial-of-service attackiswhatthisisreferredtoas. Thisattackcouldbedevelopedonanylayer.

2. AuthenticationandAttacks

onSecrecy:Attacksonpacketrelays,eavesdropping,andpacketspoofingareexamples ofsecrecyandauthenticationattacks.

3. StealthyAttackagainstServiceIntegrity: Aftergainingaccesstothesensor'snode, anattacker's aim istoinsertaincorrect valueofdata.



Layer Attacks Definition DefenseMeasure

PhysicalL ayer

Jamming [34] TheemittedRFsignalbythejammerinte rferesamong radio frequency applied by wireless sensornetwork.


PhysicalL ayer

Tampering [34] Anadversary replacesand capturesthesensor

Physicalexistenceadjacentgoaln odes.

Utilizationoftamper- resistantpackaging.

NetworkL ayer

Sybil[35] The adversary establishes a

malicious node into

thenetworkbygeneratingnewidentitie sorstealsidentitiesfromothersandscatt eredacrossthenetwork


Data lin klayer



DuetothebroadcastnatureofWirelessc ommunication, MAC identity of a

sensor node isopento


Errorcorrectingcodes,ratelimita tion,smallframes

Data lin klayer

Collision[37] When an adversary sends a warning, it causes frameerrors. Collide frames

are recycled, using


Useoferrorcorrecting codes

Applicati onLayer


aggregat iondistortion[3 7]

Once the data is gathered, it is

forwarded to the

basestationforprocessing.Thedataisc ompletelydisrupted.

Useofvariousencryptionmecha nism

Networkl ayer

Wormhole[38] Bybuildingawell-

placedwormhole,anattackertotally disrupts routing, and adversaries

gain accesstoanewradio



graphicroutingprotocol,securero utingprotocol

NetworkL ayer

SelectiveForwa rding[39]

Topreventsuspensionamongneighbor s,themalicious node selectively lowers and forwards thepacket.

Adoptmultipathroutingandbidir ectionallinkverification

Transport Layer

Flooding[40] Theattackerwillsendoutafloodofhello messagestonodesand advertiseahigh- qualitysink path.

Multipath routing and

bidirectionalconnecti onauthenticationcanbeincluded .


The structure of the sensor network, which is a variant of those discovered in cellular ad hoc networks, has severalissues. SNs are communicated across wireless, lossy lines because there is no infrastructure. Furthermore, theavailability of non-renewable energy is normally minimal for SNs. To optimize the network's life, protocols must bedesigned from the start with the goal of effective energy resource management [41]. There are several issues inWireless SensorNetwork:









Themoreefficientcontrollersand transceivers in sensor nodesallow for moresecuremessageplanning andtransmission. Energy usage and node abilities are, of course, related. As a result, protection is a trade-off amongimproved energy consumption due to longer computing and node characteristics and transmission times, specificallytheamountofaccessiblememory.Risingprotectionnecessitatesanincreaseinenergyusage.

Theresourcelimitationsof WSN are one of their distinguishing characteristics. To protect the

energy accessible from their batteries and, as

aresult,prolongtheirlifecycles,theyhavelittleexcesscapabilities.SinceWSNsusewirelessnetworking, theyare

vulnerabletothreatsthataremorecomplicatedtoinitiateinawirednetwork.Integrity,privacy,andnodeco nfidentialityareessentialsecurityutilities

forrestrictingintruders,adversarynodes,orsomeoneelsefrominterferingwiththebehaviorofadistribute dsensornetwork.ProtectioninWSNs,ontheotherhand,isstillarelativelynewfieldwith

numerousopportunities andchallenges.Since it adds difficulty and needs more energy, mostcommercialWSNsdonothaveanyencryptionfortheircommunications[43].

Sincethelifespanofaquantumlifetimenodeisnormallylimitedtothelifeofasmallbattery,powerisavitalr esourcecap. Theamountofextraenergyusedbysensornodes forsecuritypurposesisdependedby:

Forsecurityfunctionssuchasciphering,deciphering,orsignatureauthentication,measurements arerequired.


Key storagerequiresasignificantamountofenergy.


EnergyisavitalconsiderationtorememberwhenpreparingsecurityprecautionsforWSNs.Node capacityconservationandnetworkfeatureextension.

The main attacks for power exhaustion are selfish, denial of sleep, and collision, Unauthenticated Broadcast Attack[47], intelligent replay attack [44] [45] [46], full domination attack [44] [45].

Denial of sleep attack is discussedbelow indetail.


The adversary node seeks to reduce the sensor nodes' lifetime by WBANs through increasing the sensor nodes'operating time in this sleep-assault technique renege. The main goal of sleep renege is to compel WBAN nodes toremain either during the wake-up phase or during the active cycle.

Since the MAC protocols are rejected, the energyconsumption is influenced by preventing the nodes from sleeping and forcing them to wake up without requirement.When a malicious node


has information of a layered protocol, it tries to manage the network in accordance withcommunicationcycleslikeSensor-MAC[44],Timeout-

MAC[45],andBerkeleyMAC[45],causingthenode'slifeto be reduced. WBANs are classified as the denial of sleep attacks in three separate models by Raymond et al. [46]:unauthenticated broadcast attacks, smart replay attacks, and full supremacy attacks. Figure 2 illustrates the denial ofSleepattackinnetwork.Figure2showsthedenialofsleepattackinanetwork.


8.Review ofLiterature

The DoSA attack causes energy depletion in sensor nodes by stopping them from going into

energy-saving or

sleepmodes.Ahybridmethodbasedonmobilesink,fireflyalgorithmestablishedonleach,andHopefield NeuralNetworkis proposed in this article [48] (WSN-FAHN). As a result, mobile sink is used to reduce energy usage and increasenetwork lifespan. To avoid DoSA, the Firefly algorithm is

suggested to cluster nodes and authenticate at two

stages.Furthermore,theHopefieldNeuralNetworksensesthepositionofthesinkmovementtotransmitC Hdata.Moreover,the WSN-FAHN technique is evaluated using extensive simulations in the NS-2

environment. Simulation findingsindicatethattheWSN-


Packet Distribution Ratio, average throughput, detection ratio, and lifetime of the network while lowering averageresidualenergy.

Some novel attacks, such as battery depletion, denial of information, and so on, are not

mentioned in recent

surveysofintrusiondetectionsystemsinWSNandIoTapplications.Methodsforcomprehensiveanalysis ofnovelattacksarelacking. As a result, author consider a model of wireless network node behaviour under energy exhaustion attacks inarticle [49]. The authors suggest a new framework of node behaviour in the face of a battery depletion attack. Theattack may be the result of a deliberate act or a random mixture of situations. A mathematical model established oncontinuous-timediscrete-statestochasticprocesseshasbeenformedtoestimatetheattackeffect.

Author [50] investigate existing research to offer a thorough analysis of(energy depletion attacks) EDAs andprotections in (low power wireless) LPW networks. We infer from this analysis that the majority of current LPWtechnologies are vulnerable to EDAs. This paper also addresses the

security problems that EDAs raise in

LPWnetworks,aswellasfutureresearchdirections.Theireffortswillencourageresearcherstoimproveth esecurityoftheunderlyingprotocolsthatwillformtheconnectivityofbillions


Rejection-of-Sleep attacks on WSN are analyzed and modelled in this article [51]. A modelling of a specific type ofRejection-of-Sleep attack was executed, tests were showed, and potential countermeasures to such attacks werestudied based on an understanding of the works and current

results in the area. Such countermeasures may

beimplementedasdefenseprotocolsforawiderangeofcyber-physicalnetworksagainstDenial-of- Serviceattacks.ThepapersuggestsanoverviewandmodellingofDenial-of-

Service(DoS)attacks,inwhichanattackerdisguisesinvadingdata packets as normal traffic. The intruder then takes advantage of a compromised standard XBee module. Theattacker adds a


parasite module to the XBee module, forcing an manipulated node to send attacking traffic to othernetworknodes, drainingtheirenergy.

Power-positive networking (PPN) is a technique developed by the author [52] and used to minimise the risk of anenergy denial-of-service attack. Their process, which is built on wireless charging signals, is not only low-cost interms of hardware, but it also replenishes the power of the receiving node, harvesting energy DoS from its weaknesssurface. PPN provides an RF- separate data transfer channel with power-positive properties that can be enabled/usedevenwhileunderenergyDoSassaults, ratherthanmerelydisablingnetworking.

[53] is concerned with the classification, comparison, and evaluation of various types of Energy

resource exhaustion(ERE)attacksoncyber-

physicalnetworks,varyingfromphysicaleffectstohybridattacksinvolvingsocialandcyber-physical aspects. The aim of this paper is to analyze ERE attacks and model them analytically, concentrating

onvarioustypesofattackinginfluencesandtheircontexts,beforesimulatingsomeoftheattacksinphysica llyperformedcyber-physical settings to assess their efficacy and draw some conclusions about

their effectiveness. In terms

ofpracticalapplication,theexperimentallygatheredliteratureonmeasuringtheeffectivenessofdenial- of-sleepassaultsonmodelsofcyber-physicaldevicesisalsonovel.

The (SLDA) Sleep attack Detection Algorithm is proposed in this paper [54] to identify and avoid Denial of Serviceattacks in wireless sensor network. This suggested Sleep attack Detection Algorithm detects the Sleep attack usingMobile agent, trust value, random key pre-distribution, and random password generation in a complex and accuratemanner. They discern and then validate a normal node and an intruder node using a password generated at randomandatrustvalue.Furthermore,bypreventingDenialofSleepattacksandreducingresourceusage, thisalgorithmaidsin the transmission of information in a more reliable manner. The proposed algorithm was implemented in NS2 andthe detection efficiency of SLDA as well as the throughput and packet distribution ratio in a wireless sensor networkwerechecked.

This paper [55] discusses the numerous security concerns and risks that WSNs face. Also provides a short overviewof some of the protocols used to improve network security. Analytically evaluates the planned methodologies andshows the outcomes in a table. This paper explores security risks using a variety of parameters. Various protocolshave been proposed to achieve the security requirements. To keep data secure, an encryption method is used, and aMACisaddedtoeachdatapackettoensureauthenticity.

Using support vector machine learning, this [56] study simulates the impact of a denial-of-service

attack that

resultsinadenialofsleepattackinwirelesssensornetworks.Normally,classifierSVMisusedtobuildanef fectivedetectionmethod for denial of sleep attack. Support vector machines are used in the suggested technique for developing aneffective intrusion detection system (IDS). The detection engine for denial of sleep attacks uses this technique. Thenetwork simulation Opnet modeler 17.5 is used to execute the denial of sleep attack (DOSA) for WSNs. The ZigBeemodel, which better defines the sensor network nodes, is used to create effective IDS for distributed denial of sleepattacks.

Thereisadiscussionofvariouswirelesscommunicationstandards,cybersecurityproblems,andWSNsol utions.Thispaper [57] discusses topology regulation for wireless sensor network cyber protection,

in addition to well-



ure,secureinteroperabilitybetweendifferentcommunicationprotocolsisrequired.ForWSNnodeswith minimalcomputationalandcommunicationcapacities, topologycontrolcanbeaviableoption.

The suggested scheme [58] implements timely aggregator node selection based on their position to balance thenetwork's energy usage. Additional protection problems emerge because of such location-based aggregator nodecollection. Non-pairing homomorphic encryption is used in the

proposed authentication system, which is based

onellipticcurvecryptography.Duetoitsabilitytoprovideimprovedsecurityevenwithminimalkeysizes, ECCis

usedtoswapprivateandpublickeysinWSNstoprotectdatatransmission.Homomorphicencryptionisus edtoreducetheCH's total energy demand because it allows for the aggregation of encrypted data

without the need to decrypt it.

InWSNs,theproposedschemeincreasesnetworklifetimeandprovidesastrongermethodtocounterattac ks.

This paper [59] proposed a new method for evaluating the security of applications in the face of denial-of-service(DoS) attacks. The system provides for resource and service timeout justification for both services and intruders. Avariety of samples of attacks and attacker models are used to

demonstrate the model's strength. The DoS


completeforbalancedverificationscenarios.Finally,theuseofRewritingModuloSMTisillustratedfore ffectivelyautomatingtheverificationtask.

One such attack is distributed denial of service (DDoS), which consumes SNs' limited energy and causes data packetloss in a network. A distributed denial-of-service (DDoS) attack performs a

concerted attack by overwhelming

targetnodeswithfalserequests,consumingtheirresourcesandpressuringthemtodenyservicetolegitima temembernodes.The authors [60] suggest a message analyzer scheme (MAS) for WSNs. The method can detect compromised SNsthat are vulnerable to DDoS attacks. Furthermore, it can detect all infected messages sent to the base station via thesendernodesbytheattackers.Othersimilarprotocolsarecomparedtotheproposedsystem.Theresults demonstratedthattheirmethodcoulddetectandprotectagainstDDoSattacksinWSNseffectively.

Hsueh, Wen, and Ouyang (2015) [61] suggested a system in which the authors consider power

exhausting attacks

inWSNtofixtheproblemofnode(s)ornetworklifetime.Toconstructahierarchicaltopology,theauthorus esSATCA,whichhasfourstages:Anti-


[62] Using the master key transmitted, a key generation-based secure communication scheme known as KeyGenSCproduces a specific key for each message encryption and MAC computation for each message transfer. Simulationresults indicate, total energy consumption decreases, and the solution also enhances security. A symmetric key-basedDiffie-Hellman (SKDH) key renewal scheme also suggested that uses far less energy than ECC-based DH keyrenewal.Alsoconductedasecurityauditoftheproposedschemeandfoundthattheconfidentialityofk eys,aswellasthe confidentiality, authenticity, and honesty of communications, are all entirely guaranteed. The simulation resultsshow that the system requires less energy than the classic secure communication scheme while still having improvedsecurity.

TocombatDeoSattacks,theauthorspropose[63]anEncryptionandAuthenticationbasedSecuritySche me(EASS).EASS is focused on the use of SHA and symmetric cryptography to avoid power

draining attacks, allowing sensornodesinapower-



requirements and outperforms other methods currently available in the literature. Our approach usespowerwisely, accordingtosimulationdata,andcanreducetheeffectivenessofDeoSthreats.

Thegiventable3depictsthesummeryofliteratureforusedmethodsanditsparameters fortherespectiveattacks.


Author Attack Impact Methodused Parameters

RezaFotohi and

Denialofsleep Energydepletion FireflyandHopefield neural

Reduceenergyusage,incr ease

SomayyehFiro ozi

network networklifespan, throughput,

Bari[48] packetdistributionratio.

Vladimir V. Intrusiondetecti on


depleti on,

Mathematical mod el


Shakhov[49] system denialofinformati on

continuoustimediscre te

statestochasticproces s




depleti on


batteri es

of Depletingenergy method

Improvesecurity of protocols,

[50] attack devices addressfutureresearchdir

ection Vasily A.



depleti onattack

Depletedeviceen ergy

usesarangeofcriteriat oinvestigatesecurityt hreats.Differentproto colshavebeensuggest ed.

Anencryptiontechniqueis usedtokeep data secure,

and a MAC

isattachedtoeachdatapac kettoensureauthenticity.

DigiXBeev2modules ischosenasamodelofa nattackedsystem.

SYChangetal. Energy denial- of-

consumesthevicti m’s



Throughoffloading the power

[52] service(DoS) battery (PPN) requirementstotheperson


thenetworking demands, the

vulnerabilityisfullyelimi nated.

VDesnitsky[53 ]

Energyresource exhaustion(ER E)attacks

discharging of battery

the ZigBeeprotocol,wire lessXBees2ZBmodul es

Improvedpowerconsump tion



Denialof Service

Energydepletion Sleep attack Detection

throughputandpacketdist ribution



[54] attacks Algorithm(SLDA) ratioimproved

JitenderGrover and


threa ts

networksecurity Encryption

process and

Securethedataand authenticity Shikha

Shar ma

based on routing,


[55] capability, an d

protocollayer Mohd.Nooreta


denial-of- serviceattack

Powerconsumpti on

classifierSVM Incrediblethroughputfor detectingdenialofsleepstr ikeattacks

LipiChhayaata l.


securi ty

Securityissues IDS and


fault tolerance, security, and

[57] problems security reliability


Bhush an

Spoofing Attac k,

decreasedlifetime of

ellipticcurvecryptogr aphy

enhanced security, improved andG.Sahoo


Selective thenetwork networklifetimeandbetter

ForwardingAtta ck,

mechanismtocounteratta cks

SybilAttack AAUrquizaeta


denial-of- service

Usedup all of the

useofRewritingModu lo


automati ng


[59] (DoS) target'senergy,su


SMT verificationtask


amountofstaff, computing

spac e,

memory,andnetw ork

bandwidth APAbidoyeand


distributeddenia lof

consumesSNs'li mited

messageanalyzer scheme

candetect compromised

SNs, Obagbuwa[60] service(DDoS) energyandcauses


(MAS) detectallinfected messages packet loss in a



CTHsueh [61] powerexhaustin gattacks, replay attackandforgea ttack

problemofnode(s )andnetworklifeti me

cross-layer design of securescheme

integrating the MACprotocol

reducetheenergyconsum ption

R.B.Gudivada and

BruteForceattac k

Securityand energy

KeyGenerationSche meand

total energy consumption RCHansdah


consumption symmetrickey- basedDiffie-

decreases,andthesolution also

Hellman(SKDH) enhancessecurity and system

requireslessenergy K

Muthumanicka m[63]

Denial of sleep(D eoS)

powerdraining attacks


an d

Authentication base dSecurityScheme(E ASS)

reducetheeffectivenessof DeoSthreats


The WSN has its own significance in all available fields in the physical universebecause of growing globalrequirements. Aside from low-power sensing, the sensors are used in a range of applications such as temperaturedetection, pressure detection, and pollution detection.

Constrained set the sensor nodes in a sleep state most of thetime to conserve energy, which also enhances the nodes' life spam. DoS attacks cause nodes to wake up and affecttheirlifespan.Asaresult,inthisstudy,wedevisedasystemfordealingwithsuchattacksbydetectinga ntiormaliciousnodes.

The security parameter of the preferred path will be determined for finding security in WSN, and

the state of

gettingmaliciousnodeswillbeapproximatelycalculatedintheagreedcircumstancesfortheresultsapprai sal.TheRSSIvalueand routing information would be merged to identify malicious nodes and to check the attacker's identity. During theinitial stages of transmission, the route would be properly defined for routing as well as for the calculation andrecording of RSSI values. After that, the network confirms the packet strength from the source node to each node. Ifthe RSSI value is not equal to the data packet's signal strength, the network has found a malicious node, and the datapacketwillbeencryptedwithaprivatekeyforsecurity.

The energy or power of a sensor node(s) and security issues in WSN are significant because they

help to

determinehowlikelyanetworkistobeusedforfuturecommunicationaswellaspreservingtheWSNsyste m'scompletelifetimeandaccuracy.

10.ResearchObjective Thestudy'skeyobjectivesareasfollows:






Topresenta studyandevaluationofthepresentedtechnique.


A framework for power exhausting attacks in WSN is suggested in the proposed research work.

The WSN has

itssignificanceinallavailablefieldsinthephysicaluniverse,consideringthegrowingglobalrequirement s.Thesensorsare used in a variety of applications, including temperature detection, pressure detection, and emission detection, inaddition to detecting the low power mode. To conserve energy, the constrained put the sensor nodes in a sleep statefor most of the time, which also extends the nodes' life span. The DoS attacks are those that cause nodes to wake upand effects the life span of the nodes. As a result, the framework in this study is designed to address such attacks bydetectingantiormaliciousnodes.

It is recommended that the work is done so far be extended, to reduce overhead and improve the security parameterfor the same form of attacks in WSN. The key renewal phase generates the most overhead because it ensures a newkey is generated and distributed every time. To reduce overhead, the key renewal phase is skipped and the RSSI(Receiving Signal Strength Indicator) value can be used instead. Figure 3 shows the process flow of proposedmethodology.

Inanutshell, theplannedworkwillbe completedinthestagesbelow:

1. Cluster formation: - A set of nodes with identical characteristics is called a cluster, and

the cluster head

ischosenbasedonthewaitingtimerfortransmittingandlisteningtothehellomessagefromneighbors,asw ellaspowerisconsideredforassigninganynodeasclusterhead.

2. Keydistribution:-Clusterheadgeneratesandbroadcaststhetwo- waysymmetrickeyfordecryptionofthehellomessagesbroadcasted, soclusterheadisexpectedtobeefficientinpower.

3. Anti-node detection phase: - Encrypted hello messages are communicated including the RSSI value, andwhen the sensor node is unable to decode the hello message, as well as when the RSSI value and signalstrengthmismatch, anti-noteidentificationisdemonstrated.

TheRSSIvalueandroutinginformationarecombinedforthepurposeofdetectingsuspiciousnodesandde terminingtheattacker'sidentity.Duringtheinitialstagesoftransmission,therouteisproperlydefinedforr outingas wellasforthe computation and recording of RSSI values. After that, any node in the network verifies the packet strength fromthe source node's perspective. When the RSSI value is greater than or equal to the signal strength of the data packet,the network has found a malicious node. A private key is often considered for data packet encryption security. Theenergy or control of a sensing node(s) and the protection problem in WSN are critical since they help define howlikelyanetworkwillbeusedforpotentialcommunication.ItcontributestotheWSNsystem'slong- termviabilityandaccuracy.

If the RSSI of communicating nodes matched then check whether the distributed key matches, if not matched, thenetwork has found an anti-node or malicious node. If the distributed key matched thus, established the securecommunicationchannel.


Figure3:Proposedmethodology 12.ImplementationResults

The proposed RSSI-based approach is compared to existing methods for power exhausting attacks in WSN in termsofenergyconsumptionandpacketdeliveryratio.MATLAB2020is usedasasimulationtool.

MATLAB is a numeric processing environment and a proprietary multi-paradigm programming language.

Matrixmanipulations,functionanddataplotting,algorithmexecution,userinterfacecreation,andinterfa cingwithprogramswritten in other languages are all possible. Since MATLAB is mainly designed

for numerical computations,

anoptionaltoolboxusestheMuPADsymbolicenginetoprovidesymboliccomputingcapabilities.Simuli nk,astandalonepackage,providesgraphicalmulti-domainsimulationandmodel-



OperatingSystem:Windows 7/8/8.1/10



HardDisk Space:30GBoffreespacerequired.


Figure 4 shows the cluster formation in a network which consists of sensor nodes and cluster head. At initial phase,therootisestablishedinanetworkandantinodeisdetectedinacluster.

Figure4:Clusterformation ofnodes Forthedetectionofantinode,randomizedpre-






Figure6:energy ofeachnode.








Table5:RSSIforNodeB NodeI







1 16.8 38.8 -50.796

3 59.8 17.3 -71.0861

4 74.4 32 -77.1936

5 80.6 19 -79.2298

6 85.8 34.38 -81.0201

7 79 26.69 -72.8963

8 79 26.69 -78.6336

Figure8:Graph fornodeA

Figure9:Graph fornodeB

100 TableofAnode

50 0

0 2 4 6 8 10



Position(X) Position(Y) RSSI Node


Position(X )



2 19.8 24.38 -50.796

3 59.8 17.3 -74.4554

4 74.4 32 -78.2089

5 80.6 19 -81.0346

6 85.8 34.38 -81.7231

7 63.6 16.69 -75.9323

8 79 26.69 -79.9792

100 TableofBnode

50 0

0 2 4 6 8 10

-50 -100

Position(X) Position(Y) RSSI



Figure 10:Graph fornodeC Table7:RSSIforNodeD NodeI







1 16.8 38.8 -78.2089

2 19.8 24.38 -77.1936

3 59.8 17.3 -57.6204

5 80.6 19 -50.3484

6 85.8 34.38 -46.0989 7 63.6 16.69 -55.6089

8 79 26.69 -35.9906

Figure11:Graph fornodeD

100 Table of C node


-50 10

Position (X) Position (Y) RSSI Node

ID Position(X) Position


1 16.8 38.8 -74.4554

2 19.8 24.38 -71.0861

4 74.4 32 -57.6204

5 80.6 19 -57.7656

6 85.8 34.38 -65.7495

7 63.6 16.69 -23.9544

8 79 26.69 -58.242

100 TableofDnode


0 2 4 6 8 10


Position(X) Position(Y) RSSI



ID Position(X) Position(Y


1 16.8 38.8 -75.9323

2 19.8 24.38 -72.8963

3 59.8 17.3 -23.9544

4 59.8 17.3 -23.9544

5 80.6 19 -53.8472

6 77 26.69 -53.8472


100 50

0 0 2 4 6 8 10

-50 -100

Position(X) Position(Y) RSSI

Table8:RSSIforNodeE Node


Position(X )

Position (Y)


1 16.8 38.8 -81.0346

2 19.8 24.38 -79.2298

3 59.8 17.3 -57.7656

4 59.8 17.3 -57.7656

6 85.8 34.38 -52.7437 7 63.6 16.69 -53.8472

8 79 26.69 -38.2222

Figure 12:Graph fornodeE

Table9:RSSIforNodeF NodeI







1 16.8 38.8 -81.7231

2 19.8 24.38 -81.0201

3 59.8 17.3 -65.7495

4 59.8 17.3 -65.7495

5 80.6 19 -52.7437

7 63.6 16.69 -63.9181

8 79 26.69 -43.5754

Figure 73:Graph fornodeF Table10:RSSIforNodeG Figure 14:Graph fornodeG

100 TableofEnode

50 0

0 2 4 6 8 10



Position(X) Position(Y) RSSI


100 50

0 0 2 4 6 8 10

-50 -100

Position(X) Position(Y) RSSI



ID Position(X) Position(Y


1 16.8 38.8 -79.9792

2 19.8 24.38 -78.6336

3 59.8 17.3 -58.2427

4 59.8 17.3 -58.2427

5 80.6 19 -38.2222

6 80.6 19 -38.2222

7 19.8 24.38 -78.6336


100 50


0 2 4 6 8



Position(X) Position(Y) RSSI


Figure15:Graph fornodeH Figure 16 shows the detection of Antinode A and B in a cluster using RSSI value after the

clustering of nodes in anetworkandgenerationanddistributionofkey.


Figure 17 shows the RSSI value of each node of a cluster. If the RSSI of communicating nodes matches, Cluster andGateway key generated. Cluster node is the node from which the data is transferred. Gateway is to which data istransferred. Check if the distributed Cluster and Gateway

key matches after the RSSI value of communicating

nodesmatches.Securecommunicationchannelisestablishedifthedistributedkeymatchedthatisdemon stratedinthebelowfigure.



Table12:energyconsumptionofexistingandproposedapproach SimulationTime


Existing Proposed

1 32.4352 13.1426

25 48.1428 34.6430

49 52.5428 40.5769

73 76.8143 64.3035

97 85.1502 68.9897

Figure 18 shows the comparison of energy consumption of existing and proposed approach.

Proposed approachshows theconsumptionofenergybythenodesislessthantheexistingapproach.



Thepacketdeliveryratioistheaverageofthesourcenode'stotalgeneratedpacketsandthepacketsreceived atthesourcetarget.

Table13:Packetdeliveryratioofexistingandproposedapproach SimulationTime


Existing Proposed

1 0.7042 0.7681

25 0.6330 0.7681

49 0.3423 0.5254

73 0.3229 0.4814

97 0.1694 0.3244

Figure19showsthecomparisonofpacketdeliveryratiofortheexistingandproposedapproach.Packetdel iveryratioofproposedapproachishighthantheexistingapproach.

Figure19:ComparisonofPacketdeliveryRatio 12.Conclusionand Future Scope

ThelatestworkoffersaconcisesummaryofWSN,itscharacteristics,mostsignificantproblemsandchalle nges.Afteranalyzing numerous domain-related issues and challenges, the power management for

sensor nodes is the

mostessentialparttoconsider.Thebulkoftheworksareconcernedwiththeadditionalenergyusedbecause ofunnecessarycomputation.SuchasDoS(DenialofSleep),whichisatypeofattackthatholdsnodesawak eforlongperiodsoftimewithout being used in current communication, thus exhausting the sensor nodes' power. The literature review is alsodone in the research presented for a deeper interpretation of the problem and for a better formulation of the problem,which results in power exhaustion. The WSN has its own significance in all available fields in the physical universe,given the growing global requirements. Aside from sensing in low-power mode, the sensors are used in a variety ofapplications such as temperature monitoring, pressure detection,


and emission detection. Constrained set the sensornodesinasleepstatemostofthetimetoconserveenergy,whichalsoraises thenodes' lifespam.

DoS attacks cause nodes to wake up, reducing their life span. In this paper, a basic power management system isintroduced based on the issue formulated in the literature review, which uses RSSI and encryption strategies forauthentication and power management to prevent the network from losing power and also to inspect and maliciousnodes. The work focuses on the context study and solution to the formulated problem for validation using real- timesimulationplatformssuchasMATLABforbettervalidationoftheworkpresented.


[1] Ma, Y., Richards, M., Ghanem, M., Guo, Y., Hassard, J.: Air Pollution Monitoring and Mining Based on Sensor Grid in London. Sensors 8, 3601–3623 (2008).

[2] Zhao, Y., Shouzhi, X., Shuibao, Z., Xiaomei, Y.: Distributed detection in landslide prediction based on Wireless Sensor Networks. In: Proceedings of World Automation Congress, Puerto Vallarta, Mexico, June 24-28, pp. 235–238 (2012).

[3] Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless Sensor Networks: A Survey. Computer Networks 38, 393–422 (2002).

[4] Istepanian, R., Jovanov, E., Zhang, Y.: Guest editorial introduction to the special section on M-Health: Beyond seamless mobility and global wireless Health-Care connectivity. IEEE Trans. Inf. Technol. Biomed. 8, 405–414 (2004)

[5] Milenkovic, A., Otto, C., Jovanov, E.: Wireless sensor network for personal health monitoring: Issues and an implementation. Comput. Commun. 29, 2521–2533 (2006).

[6] Junnila, S., Kailanto, H., Merilahti, J., Vainio, A.-M., Vehkaoja, A., Zakrzewski, M., Hyttinen, J.: Wireless, Multipurpose In-Home Health Monitoring Platform: Two Case Trials. IEEE Trans. Inf. Technol. Biomed. 14, 447–455 (2010).

[7] Bachmann, C., Ashouei, M., Pop, V., Vidojkovic, M., Groot, H.D., Gyselinckx, B.:

Low-power wireless sensor nodes for ubiquitous long-term biomedical signal monitoring. IEEE Commun. Mag. 50, 20–27 (2012).

[8] Han, K., Shon, T., Kim, K.: Efficient mobile sensor authentication in smart home and WPAN. IEEE Trans. Consum. Electr. 56, 591–596 (2010).

[9] Byun, J., Jeon, B., Noh, J., Kim, Y., Park, S.: An intelligent self-adjusting sensor for smart home services based on ZigBee communications. IEEE Trans. Consum. Electr.

58, 591–596 (2012).

[10] Nakamura, M., Igaki, H., Yoshimura, Y., Ikegami, K.: Considering Online Feature Interaction Detection and Resolution for Integrated Services in Home Network System.

In: Proceedings of the 10th International Conference on Feature Interactions in Telecommunications and Software Systems, Lisbon, Portugal, June 11-12, pp. 191–

206 (2009).

[11] D. Johnson, Y. Hu, and D. Maltz, ―The Dynamic Source Routing Protocol (DSR) for Mobile Ad Hoc Networks for IPv4,‖ IETF RFC 4728, vol. 15, pp. 153-181, Feb. 2007.

[12] C. Perkins, E. Belding-Royer, and S. Das, ―Ad Hoc On-Demand Distance Vector


(AODV) Routing,‖ IETF RFC 3561, July 2003.

[13] Shakhov, Vladimir V. "Protecting wireless sensor networks from energy exhausting attacks." In International Conference on Computational Science and Its Applications, pp. 184-193. Springer, Berlin, Heidelberg, 2013.

[14] Yong-Min, Liu, Wu Shu-Ci, and Nian Xiao-Hong. "The architecture and characteristics of wireless sensor network." In 2009 International Conference on Computer Technology and Development, vol. 1, pp. 561-565. IEEE, 2009.

[15] M. Ahmed, X. Huang, D. Sharma, and H. Cui; ―Wireless Sensor Network:

Characteristics and Architectures‖, in World Academy of Science, Engineering and Technology, Penang, Malaysia, (2012), vol. 72, pp. 660–663.

[16] Mohanty and Sanatan, ―Energy Efficient Routing Algorithms for Wireless Sensor Networks and Performance Evaluation of Quality of Service‖, IEEE 802.15.4 Networks, MTech by Research thesis (2010). http://ethesis.nitrkl.ac.in/2077/.

[17] Iavor K. Vladimirov, Desislava Tacheva, and Vladislav Dobrinov, ―The Present and Future of Embryo Cryopreservation‖, Book- Embryology- Theory and Practice, (2018), doi: 10.5772/intechopen.80587.

[18] Alsadig Ismail Altahir, Sahl Ali Abdsllah Ali and Safa Mohamed Almahi Alsadig,

―Controlling and monitoring greenhouse using microcontroller Arduino maga base system‖, Project submitted to Sudan University of Science and Technology, (Oct 2016).

[19] Asmaa Ez-Zaidi and Said Rakrak, "A Comparative Study of Target Tracking Approaches in Wireless Sensor Networks", Journal of Sensors, (2016), vol. 2016, Article ID 3270659, 11 pages. https://doi.org/10.1155/2016/3270659.

[20] Prabhu S, R. Boselin, Pradeep M. and Gajendran E., ―Military Applications of Wireless Sensor Network System‖, (January 25, 2017), A Multidisciplinary Journal of Scientific Research & Education, (December-2016), Vol. 2, Issue: 12, Available at SSRN: https://ssrn.com/abstract=2905627.

[21] S.R. Boselin Prabhu, N. Balakumar and A. Johnson Antony, ―Evolving Constraints in Military Applications using Wireless Sensor Networks‖, International Journal of Innovative Research in Computer Science and Technology (IJIRCST), (January 2017), ISSN: 2347-5552, Vol. 5, Issue-1. doi: 10.21276/ijirst.2017.5.1.2.

[22] Mohd Fauzi Othman and Khairunnisa Shazali, ―Wireless Sensor Network Applications: A Study in Environment Monitoring System‖, Procedia Engineering,

(2012), Vol. 41, pp. 1204-1210, ISSN 1877-7058.


[23] P. Neves, M. Stachyra and J. Rodrigues, "Application of Wireless Sensor Networks to Healthcare Promotion", Journal of Communications Software and Systems, (2008), vol.4, Issue- 3, pp 181-190. https://doi.org/10.24138/jcomss.v4i3.218.

[24] Belghith A., and Obaidat M. S., ―Wireless sensor networks applications to smart homes and cities‖, In Smart Cities and Homes, (2016), pp. 17-40.

[25] Faisal Ahmed Al-Naseer and Magdi S. Mehmoud, ―Wireless Sensors Network


Application: A Decentralized Approach for Traffic Control and Management‖, Wireless Sensor Networks- Technology and Applications, doi: 10.5772/48212, 2012.

[26] Divya C, ―Security mechanisms on key pre-distribution in wireless sensor network‖, thesis- Manonmaniam Sundaranar University, centre for information technology and engineering, March, (2015). http://hdl.handle.net/10603/38341.

[27] C. T. Li, M. S. Hwang, and Y. P. Chu, ―An efficient sensor to sensor authenticated path – key establishment scheme for secure communications in wireless sensor network‖, International Journal of Innovative Computing, Information and Control, (2009), vol.5, no.8, pp.2107-2124.

[28] Camtepe S. A., B. Yener, and M. Yung, ―Expander graph-based key distribution mechanisms in wireless sensor network,‖ in Proc. IEEE Int. Conf. Communication, (2006) pp.2262–2267.

[29] Arif Selcuk Uluagac, ―A secure Communication framework for wireless sensor networks‖, Ph.D. Thesis, Georgia Institute of Technology, (August 2010).

http://docplayer.net/51229736-A-secure-communication-framework-for-wireless- sensor- networks.html.

[30] Shi E., and A. Perrig; ―Designing Secure Sensor Networks‖, Wireless Communication Magazine, (December 2004), vol.11, no.6, pp.38–43.

[31] P. Sinha, V. K. Jha, A. K. Rai, and B. Bhushan, "Security vulnerabilities, attacks and countermeasures in wireless sensor networks at various layers of OSI reference model:

A survey," 2017 International Conference on Signal Processing and Communication (ICSPC), Coimbatore, India, (2017), pp. 288-293, doi: 10.1109/CSPC.2017.8305855.

[32] Hiren Kumar, Deva Sarma, and Avijit Kar, ―Security Threats in Wireless Sensor Networks‖, Carnahan Conferences Security Technology, Proceedings (2006), 40th Annual IEEE International.

[33] S. K. Singh, M. P. Singh, and D. K. Singh; ―A Survey on Network Security and Attack Defense Mechanism for Wireless Sensor Networks‖, International Journal of Computer Trends and Technology, (Jun. 2011), vol. 1, no. 2, pp. 1–9.

[34] The Five-Layer TCP/IP Model: Description/Attacks/Defense, (2008) http://wiki.cas.mcmaster.ca/index.php/The_Five_Layer_TCP/IP_Model:_Description/


[35] Shehnaz T. Patel and Nital H. Mistry, ―A Review: Sybil Attack Detection Techniques in WSN,‖ in 4th International Conference on Electronics and Communication Systems, (2017), pp. 184-188.

[36] Albandari Mishal Alotaibi, Bedour Fahaad Alrashidi, Samina Naz and Zahida Parveen,

―Security issues in Protocols of TCP/IP Model at Layers Level‖, International Journal of Computer Networks and Communications Security, (May 2017), Vol. 5, No.5, pp.96-104

[37] Jilani, Sayamuddin Ahmed, Chandan Koner, and Shovon Nandi. "Security in Wireless Sensor Networks: Attacks and Evasion." In 2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA), IEEE,


(2020), pp. 1-5.

[38] Azer Sherif Magdy, ―A Full Image of Wormhole Attacks Towards Introducing Complex Wormhole Attacks in Wireless Adhoc Networks‖, IJCSIS, (May 2009), Vol.

1, No 1, pp. 41-51.

[39] Zhou H, Wu Y, Feng L, Liu D. ―A Security Mechanism for Cluster-Based WSN against Selective Forwarding. Sensors‖, (2016); 16(9):1537.


[40] Virendra Pal Singh, Sweta Jain, and Jyoti Singhai. "Hello flood attack and its countermeasures in wireless sensor networks." International Journal of Computer Science Issues (IJCSI) 7, no. 3 (2010): 23

[41] Koushanfar. F, M. Potkonjak, A. Sangiovanni-Vincentelli, ―Fault Tolerance in Wireless Sensor Network‖, Chapter 36, Handbook of Sensor Network: Compact Wireless and Wired Sensing Systems (Edited by Mohammad Ilyas and Imad Mahgoub), CRC Press, (2005).

[42] Ishmanov F, Malik AS, and Kim SW, ―Energy consumption balancing (ECB) issues and mechanisms in wireless sensor networks (WSNs): A comprehensive overview‖, European Transactions on Telecommunications, (2011), vol.22, pp.151– 167.

[43] Chang, Chih-Chun, David J. Nagel, and Sead Muftic. "Balancing security and energy consumption in wireless sensor networks." In International Conference on Mobile Ad- Hoc and Sensor Networks, pp. 469-480. Springer, Berlin, Heidelberg, 2007.

[44] Ye, Wei, John Heidemann, and Deborah Estrin. "Medium access control with coordinated adaptive sleeping for wireless sensor networks." IEEE/ACM Transactions on Networking 12.3 (2004): 493-506.

[45] Van Dam, Tijs, and Koen Langendoen. "An adaptive energy-efficient MAC protocol for wireless sensor networks." Proceedings of the 1st international conference on Embedded networked sensor systems. 2003.

[46] Raymond, David R., et al. "Effects of denial-of-sleep attacks on wireless sensor network MAC protocols." IEEE transactions on vehicular technology 58.1 (2008):


[47] Chen, Chen, et al. "An effective scheme for defending denial-of-sleep attack in wireless sensor networks." 2009 Fifth International Conference on Information Assurance and Security. Vol. 2. IEEE, 2009.

[48] Fotohi, Reza, and Somayyeh Firoozi Bari. "A novel countermeasure technique to protect WSN against denial-of-sleep attacks using firefly and Hopfield neural network (HNN) algorithms." The Journal of Supercomputing (2020): 1-27.

[49] Shakhov, Vladimir, Insoo Koo, and Alexey Rodionov. "Energy exhaustion attacks in wireless networks." In 2017 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON), pp. 1-3. IEEE, 2017.

[50] Nguyen, Van-Linh, Po-Ching Lin, and Ren-Hung Hwang. "Energy depletion attacks in low power wireless networks." IEEE Access 7 (2019): 51915-51932.

[51] Desnitsky, Vasily A., Igor V. Kotenko, and Nikolay N. Rudavin. "Protection


mechanisms against energy depletion attacks in cyber-physical systems." In 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), pp. 214-219. IEEE, 2019.

[52] Chang, Sang-Yoon, Sristi Lakshmi Sravana Kumar, Yih-Chun Hu, and Younghee Park. "Power-positive networking: Wireless-charging-based networking to protect energy against battery DoS attacks." ACM Transactions on Sensor Networks (TOSN) 15, no. 3 (2019): 1-25.

[53] Desnitsky, Vasily, Igor Kotenko, and Danil Zakoldaev. "Evaluation of Resource Exhaustion Attacks against Wireless Mobile Devices." Electronics 8, no. 5 (2019):


[54] Mahalakshmi, G., and P. Subathra. "Denial of sleep attack detection using mobile agent in wireless sensor networks." Int J Res Trends Innov 3, no. 5 (2018): 139-149.

[55] Grover, Jitender, and Shikha Sharma. "Security issues in wireless sensor network—a review" In 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO), pp. 397-404. IEEE, 2016.

[56] Mohd, Noor, Annapurna Singh, and H. S. Bhadauria. "A novel SVM based IDS for distributed denial of sleep strike in wireless sensor networks." Wireless Personal Communications 111, no. 3 (2020): 1999-2022.

[57] Chhaya, Lipi, Paawan Sharma, Govind Bhagwatikar, and Adesh Kumar. "Wireless sensor network based smart grid communications: Cyber-attacks, intrusion detection system and topology control" Electronics 6, no. 1 (2017): 5.

[58] Bhushan, Bharat, and G. Sahoo. "Secure Location-Based Aggregator Node Selection Scheme in Wireless Sensor Networks." In Proceedings of ICETIT 2019, pp. 21-35.

Springer, Cham, 2020.

[59] Urquiza, Abraão Aires, Musab A. AlTurki, Max Kanovich, Tajana Ban Kirigin, Vivek Nigam, Andre Scedrov, and Carolyn Talcott. "Resource-bounded intruders in denial- of-service attacks." In 2019 IEEE 32nd Computer Security Foundations Symposium (CSF), pp. 382-38214. IEEE, 2019.

[60] Abidoye, Ademola P., and Ibidun C. Obagbuwa. "DDoS attacks in WSNs: detection and countermeasures." IET Wireless Sensor Systems 8, no. 2 (2017): 52-59.

[61] Hsueh, Ching-Tsung, Chih-Yu Wen, and Yen-Chieh Ouyang. "A secure scheme against power exhausting attacks in hierarchical wireless sensor networks." IEEE Sensors journal 15.6 (2015): 3590-3602.

[62] R. B. Gudivada and R. C. Hansdah, "Energy Efficient Secure Communication in Wireless Sensor Networks," 2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA), Krakow, Poland, 2018, pp. 311- 319, doi: 10.1109/AINA.2018.00055.

[63] Muthumanickam, K., S. Elango, PC Senthil Mahesh, and P. Vijayalakshmi. "EASS:

Encryption and Authentication Based Security Scheme to Prevent Power Exhausting Attacks in Wireless Sensor Networks." Adhoc & Sensor Wireless Networks 45 (2019).



In comparison to the conventional load balancing approach, Openflow provides another form of load balancing architecture method, the server load balance based on SDN.. The

The proposed PRM mode is compared to the existing Energy Efficient Routing Model (EERM) in terms of Energy Consumed during Routing, Energy Consumed while

This paper proposes anintegrated approach of Internet of Things ,wireless sensor networks and Image processing bydesigninghybrid Unmanned Aerial Vehicle(UAV)to forest fire

This paper proposes anintegrated approach of Internet of Things ,wireless sensor networks and Image processing bydesigninghybrid Unmanned Aerial Vehicle(UAV)to forest fire

In this research paper we are going to introduce you to the various protocols and wireless communication standards that were previously used for security purposes

A global adversary using a Bayesian maximum-a- posteriori (MAP) evaluation strategy tried to screen communication between nodes in their research. A dynamic framework

Proving secure path is a major challenging security issues in wireless networks because various attacks occur in mobile networks during the route establishment

The results show that proposed scheme outperforms well compared to the existing schemes in terms of maximizes the coverage with respect to number of nodes & simulation

Sukavanam, "Human Action Recognition from Motion Trajectory using Fourier Temporal Features of Skeleton Joints," 2018 International Conference on Advances in Computing

Zeidler, E., Nonlinear Functional Analysis and its Applications, IV: Applications to Mathematical Physics, Springer Verlag New York Berlin Heidelberg,

• Radio NIC (Network Interface Card) or adapters or radio cards – Operate inside the device and offers wireless connectivity – Implements and supports one or many versions of

Moustafa et al., has proposed in these paper one of the significant exploration challenges in this field is the inaccessibility of an exhaustive organization

Cho, ―Intrusion detection scheme against sinkhole attacks in directed diffusion based sensor networks,‖ International Journal of Computer Science and Network Security, vol. Kumar et

In wireless sensor networks (WSNs), long lifetime necessity of various applications and restricted energy stockpiling capacity of sensor hubs has driven us to discover new

Energy efficient data collection and fusion using mobile sink in heterogeneous wireless sensor network is proposed to improve the network performance in terms of energy

Security in wireless sensor networks, Key management, Network Attacks, Node capture

Dash, "Arduino Based Automated Stick Guide for a Visually Impaired Person", IEEE International Conference on Smart Technologies and Management for

The EEADR protocol elects the proper location of the CHs closer to the energy centroid position and for gateway node selection to communicate the data towards the BS via

The experimental studyrevealedthat there is no commonresult for the problems of the LEACH and k- meansalgorithms for WSNs rather each of the existingdeviations of the algorithm

Proposed routing Cluster formation and selecting cluster head, which transfer data from their cluster nodes to base station, uses hierarchical clustering algorithm and considers

A Novel Quantum Beetle Swarm Optimization based Route Selection and Hybrid Data Transmission in Wireless Sensor Networks.. ¹A.Sathish and

1. It‟s one of algorithms most widely utilized for hierarchical routing in sensor networks. The LEACH protocol segments entire wireless sensors network in several clusters.

1.2 If no, check if enough buffer space is available at next node. Monitor* node generates a dummy RREQ to the same destination. 1.2.1 If the suspected node