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International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume: 3 | Issue: 2 | Jan-Feb 2019 Available Online: www.ijtsrd.com e-ISSN: 2456 - 6470
@ IJTSRD | Unique Reference Paper ID - IJTSRD20300 | Volume – 3 | Issue – 2 | Jan-Feb 2019 Page: 438
Detection of Vampire Attacks in Ad-Hoc
Wireless Sensor Network Evaluation and Protection
Anand. M
Assistant Professor, Department of Information Science & Engineering,
GSSSIETW, Mysuru, Karnataka, India
ABSTRACT
Wireless Sensor Networks (WSNs) in today’s world are the means of communication. These contain nodes that act as
transmitter and receivers are prone to different attacksleadingtodifferenttypesof losses. Theresourcedepletionattack thatis
called vampire attack drains out the energy from thenodesleavingthemuseless.These attacks are protocol compliant,they are
easy to implement. Since they are orthogonal in nature they can easily intrude into any routing protocol. They affecttheentire
network causing large loss of energy and A vampire attack is caused bythemaliciousnodeonthedecentralized ad hocwireless
network. The paper analyses how protocols faces these attacks. Vampire attacks are not protocol specific rather uses its
compliant message. The current security measures to prevent these attacks are been reviewed along with resultof simulation
of representative protocols in the presence of a vampire attack is been presented. The paper also describes how the existing
sensor network protocol is been modified for protection from the vampire attacks for which PLGP (Parno, Luk, Gaustad and
Perrig) solution is also been proposed.
KEYWORDS: Wireless Sensor Network; Denial of service; Resource depletion; Routing; Energy consumption; Security; carousel
attack; stretch attack; PLGP
I. INTRODUCTION
Ad hoc wireless sensor network consists of various sensors
that are expanded in a space where each sensor performs
signal processingand datanetworkingprovidingoperational
efficiency. The ad hocwirelessservers areself-organizedand
energy constrained. These sensor networks are used to
detect information of enemy base, monitor environmental
changes and are also used for security purposes in various
places like shopping and parking area and when these
networks face attacks causing negative effect by causing
battery exhaustion and higher energy utilization.
Fig 1: Ad hoc Wireless sensor network
Vampire attacks are caused when amessageisbeeninitiated
and transmitted through a malicious node over the network
causing higher battery utilization and battery exhaustion.
Vampire attacks are not constrained to a specific type of
protocol and does not alter specific path in the network.
When a network is been attacked by them, even transfer of
small data consumes more energy.
Fig 2: Architecture of WSN
The basic architecture of a WSN [10] contains number of
nodes that act as routing nodes, sensing nodes and base
nodes. Figure 2 shows the architecture of a WSN, where all
the different types of nodes are shown.Itisalsopossiblethat
every node in the network functions as an aggregationpoint,
delaying transmission of an outgoing message until a
sufficient number of incoming messages have been received
and aggregated. Power management in sensor networks is
critical. Consequently, if we want sensor networks tolast for
years, it is crucial that they run at around a 1%dutycycle (or
less). Similarly, since the power consumption of the radio is
three orders of magnitude higher when transmitting or
listening than when in sleep mode, it is crucial to keep the
radio in sleep mode the overwhelming majority of the time.
Sensor networks provide economically viablesolutionsfora
wide variety of applications, includingsurveillanceof critical
infrastructure, safety monitoring, and many health-care
applications [6]. As sensor networks are increasingly
deployed in such security-and safety critical environments,
the need forsecurecommunicationprimitivesisself-evident.
Likewise, the development of such primitives facilitates the
use of sensor networks in a wider range of applications. The
central goal of this work is to ensure node-to-node message
delivery, even if the sensor network is under active attack
International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Reference Paper ID - IJTSRD20300 | Volume – 3 | Issue – 2 | Jan-Feb 2019 Page: 439
[8]. The presence of an attacker, it is an extremely
challenging task to maintaincorrectroutinginformation;the
attacker could inject malicious routing information or alter
routing setup/update messages from legitimatenodes.Even
when route setup/update messages are authenticated,
compromised sensor nodes can supply incorrect routing
information of their own and cripple the routing
infrastructure. WSNs consist of nodes they are independent
and have no infrastructure. The nodes of WSN consists of
Data acquisition unit, Data transfer unit and Process unit to
which power is supplied as shown in the figure 3. These
nodes are used in different fields to gather information in
different ways. Base stations are typically many orders of
magnitude more powerful than sensor nodes [12]. They
might have workstation or laptop class processors,memory,
and storage, AC power, and high bandwidth links for
communication amongst themselves.
Fig 3: Nodes of WSN
The sensors are constrained to use lower-power, lower-
bandwidth, shorter-range radios, and so it is envisioned that
the sensor nodes would form a multi-hop wireless network
to allow sensors to communicate to the nearest base station.
A base station might request a steady stream of data, such as
a sensor reading every second, from nodes able to satisfy a
query [9]. We refer to such a stream as a data flow and to the
nodes sending the data as sources. In order to reduce the
total number of messages sent and thus save energy, sensor
readings from multiple nodes may be processed at one of
many possible aggregation points. An aggregation point
collects sensor readings from surrounding nodes and
forwards a single message representing an aggregate of the
values. Aggregation points [3] are typically regular sensor
nodes, and their selection is not necessarily static.
Aggregation points could be chosen dynamically for each
query or event.
II. PROTOCOLS AND ASSUMPTIONS
In this paper we discuss the effect of vampire attacks on Ad-
hoc On Demand Vector Routing (AODV) [5]. AODV is a
reactive protocol for ad-hoc and a mobile network that
maintains routes only between nodes which need to
communicate. The routing messages do not contain
information about the entire route path, but only about the
source and destination. Therefore routing messages don’t
not have an increasing size. It uses destination sequence
numbers to specify how fresh a route is, which is used to
grant loop freedom. As seen in figure 4, whenever a node
needs to send a packet to a destination for which it has no
„fresh enough‟ route (i.e., a valid route entry for the
destination whose associated sequence number isat leastas
great as the ones contained in any RREQ that the node has
received for that destination) it broadcasts a route request
(RREQ) message to its neighbors. Each node that receives
the broadcast sets up a reverse route towards the originator
of the RREQ (unless it has a „fresher‟ one). When the
intended destination (or an intermediate node that has a
„fresh enough‟ route to the destination) receives the RREQ,
it replies by sending a Route Reply (RREP). It is importantto
note that the only mutable information in a RREQ and in a
RREP is the hop count (which is being monotonically
increased at each hop). The RREP travels back to the
originator of the RREQ (this time as a unicast). At each
intermediate node, a route to the destination is set (again,
unless the node has a „fresher‟ route than the one specified
in the RREP). In the case that the RREQ is replied to by an
intermediate node (and if the RREQ had set this option), the
intermediate node also sends a RREP to the destination. In
this way, it can be granted that the route path is being set up
bidirectional. In the case that a node receives a new route
(by a RREQ or by a RREP) and the node already has a route
„as fresh‟ as the received one, the shortest one will be
updated. If there is a subnet (a collection of nodes that are
identified by a common network prefix) that does not use
AODV as its routing protocol and wants to be able to
exchange information with an AODV network, one of the
nodes of the subnet can be selected as their „network
leader‟. The network leader is the only node of the subnet
that sends forwards and processes AODV routing messages
and every RREP that the leader issues, it sets the prefix size
of the subnet optionally. A Route Reply Acknowledgment
(RREP-ACK) message may be sent by the originator of the
RREQ to acknowledge the receipt of the RREP.
Fig 4: AODV protocol
RREP-ACK message has no mutable information. In addition
to these routing messages, Route Error (RERR) message are
used to notify the other nodes that certain nodes are not
anymore reachable due to a link breakage. When a node
rebroadcasts a RERR, it only adds the unreachable
destinations to which the node might forward messages.
Therefore, the mutable information in a RERR is the list of
unreachable destinations and the counter of unreachable
destinations included in the message. Anyway, it is
predictable that, at each hop, theunreachabledestination list
may not change or become a subset of the original one. The
vampire attack disrupts the AODV protocols ability to avoid
loops and choose the shortest path, AODV are prone to
wormhole attacks [14] and false injection of data [7] which
can be avoided by using an encryption system [7] [13] [11].
International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Reference Paper ID - IJTSRD20300 | Volume – 3 | Issue – 2 | Jan-Feb 2019 Page: 440
III. VAMPIRE ATTACK DETECTION
There are two types of attacks in WSN, the routing depletion
and resource depletion attack. The routingdepletionattacks
usually only affect the routing path the resource depletion
attacks are the ones that attack the network features like
bandwidth, power, and energy consumption. These attacks
are commonly called as “Vampire attacks” [2]. They are
called so because they drain the battery power from the
nodes. These are a type of Denial of Service [1] since they
affect the entire system from performing. They are difficult
tobe detected since they are protocol compliant and are
orthogonal to them [4]. They are not protocol specific. They
do not affect a single node they take their time attack one by
one and disrupt the entire system. Vampire attacks can be
defined as the composition and transmission of a message
that cause more energy to be consumed by thenetwork than
if an honest node transmitted a message of identical size to
the same destination, although using different packet
headers. The strength of the attack is measured by the ratio
of network energy used in the benign casetotheenergyused
in the malicious case. Safety from Vampire attacks implies
that this ratio is 1. Energy use by malicious nodes is not
considered, since they can always unilaterally drain their
own batteries.
A. Carousel attack
In this attack, an adversary composes packets with
purposely introduced routing loops. It is called carousel
attack, since it sends packets in circles as shown in Figure 4.
It targets source routing protocols by exploiting the limited
verification of message headers at forwarding nodes,
allowing a single packet to repeatedly traverse the same set
of nodes. On average, a random located carousel attacker in
the example mentioned topology can increase the network
energy consumption by a factor of 1.48±0.99.
Fig 5: Carousel attack
The reason for this large standard deviation is that the
attack does not always increase energy usage, the length of
the adversarial path is a multiple of the honestpath, which is
in turn, affected by the position of theadversary’s position of
the adversary in relation to the destination, so the
adversary’s position is important to the success of this
attack. Figure 5 shows the network under attack where the
packets are sent in loops causing more usage of energy and
time.
B. Stretch attack
In this attack, also targeting source routing, an adversary
constructs artificially long routes, potentially traversing
every node in the network. It is call this the stretch attack,
since it increases packet path lengths, causing packets to be
processed by a number of nodes that is independent of hop
count along the shortest path between the adversary and
packet destination. An example is illustrated in figure 6. In
the example topology, thereisanincreaseinenergyusage by
as much as a factor of 10.5 per message over the honest
scenario, with an average increases in energy consumption
of 2.67±2.49. As with the carousel attack, the reason for the
large standard deviation is that the position of the
adversarial node affects the strength of the attack. Not all
routes can be significantly lengthened, depending on the
location of the adversary.
Fig 6: Stretch attack
The carousel attack, where the relative positions of the
source and sink are important, the stretch attackcanachieve
the same effectiveness independent of the attacker’s
network position relative to the destination, so the worst-
case effect is far more likely to occur .The impact of these
attacks can be further increased by combining them,
increasing the number of adversarial nodes in the network,
or simply sending more packets. Although in networks that
do not employ authentication or only use end-to-end
authentication, adversaries are free to replace routes in any
overhead packets, we assume that only messages originated
by adversaries may have maliciously composed routes.
IV. SECURITY AGAINST VAMPIRE ATTACKS
A Clean Slate Sensor Network Routing by PLGP (Parno, Luk,
Gaustad and Perrig) can be applied which consists of two
phases:
1. Topology Discovery Phase
2. Packet Forwarding Phase
1. Topology Discovery Phase:
A node starts with its virtual address as zero. At each node a
certificate is been issues which contains the public key for
identification. Each node is connected to the other and
shares virtual address, public key and the certificate when
they merge with closest nearby group.
International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
@ IJTSRD | Unique Reference Paper ID - IJTSRD20300 | Volume – 3 | Issue – 2 | Jan-Feb 2019 Page: 441
Fig 7: Topology Discovery Phase
2. Packet Forwarding Phase:
The packets are forwarded in this phase as shown in figure
8.
Fig 8: Packet Forwarding Phase
PLGP proposed a solution which suggests:
A. Providing a verifiable path history to all the packets
involved.
B. Using this path history the packet transmission can take
place through every node securely passing through at
least one honest node.
C. Each node upon receiving the message, checks for
authentication in the chain.
CONCLUSION
In this paper, the routing protocolaffectedbyvampire attack
in WSN is discussed. This is a new class of resource
consumption attack that use routing protocols to
permanently disable ad-hoc WSNs by depleting node’s
battery power. Simulation results show that depending on
the location of adversary, network energy expenditure
during the forwarding phase increasing. The security flaws
of AODV can be fixed by using RSA encryption system that
will avoid the adversary from entering the system. These
attacks does not depend on particular type of protocol and
Ad hoc network sensors have been applied in various fields
which needs to create and identify solutions for prevention
of the network from these attacks. There are different types
of vampire attacks depending on the protocol. When the
attack take place it not only consumeshigherpowerbutalso
takes additional time. There are many solutions and
techniques that have been presented to prevent these
attacks but were not effective enough which creates a need
for a better solution. PLGP solutions can be applied to these
protocols in order to prevent these networks that are often
prone to vampire attacks.
REFERENCES
[1] A. Wood and J. Stankovic. Denial of Service in sensor
networks. IEEE Computer, pages 54-62, Oct, 2002.
[2] Eugene Y. Vassermann and Nicholas Hopper “Vampire
Attacks: Draining Life from Wireless Ad Hoc Sensor
Networks” IEEE Trans. Mobile Computing, vol. 12, no.
2, pp. 318-332 Feb-2013.
[3] B. Przydatek, D. Song, and A. Perrig. SIA:Secure
information aggregation in sensor network. In ACM
SenSys, Nov 2003.
[4] B. Karp and H. T. Kung, “GPSR: greedy perimeter
stateless routing for wireless networks.” In mobile
Computing and Networking, 2000, pp.243-254.
[5] C. Perkins and E. Royer, “Ad-hoc on demand distance
vector routing,” in MILCOM ‟97 panel on Ad Hoc
Networks, 1997.
[6] Chris Karloff and David Wager “Secure Routing in
Wireless Sensor Networks: Attacks and
countermeasures” Proc. IEEE Int‟l workshop sensor
network protocols and applications, 2003.
[7] F. Ye, H. Luo and S. “Statistical En-Route Filtering of
Injected False Data in Sensor Networks,” IEEE Journal
on Selected Areas in Communication, vol. 23, No.4,
2005, pp.839-8.
[8] H. Chan and A. Perrig, “Security and Privacy in Sensor
Networks,” Computer, vol. 36, no. 10, pp. 103-105, Oct.
2003.
[9] J. Deng, R. Han, and S. Mishra, “Maximum Lifetime
Routing in Wireless Sensor Networks,” IEEE/ACM
Trans. Networking, vol 12. 4, pp. 609-619, Aug. 2004.
[10] J.Hill, R.Szewczyk, A. Woo, S. Hollar, D. Culler, and K.
Pister, “System architecture directions for networked
sensors,” in Proceedings of ACM ASPLOS IX, November
2000.
[11] L. Buttyan, et al., “Statistical Wormhole Detection in
Sensor Networks,” Lecture Notes in Computer Science
Vol. 3813, 2005, pp. 128-141.
[12] M. Tubaishat and S. Madria, “Sensor Networks: An
Overview,” IEEE Potentials, Vol. 22, No. 2,2003, pp.20-
23. doi:10.1109/MP.2003.1197877.
[13] M. McLoone and M. Robshaw, “Public Key
Cryptography and RFID Tags,” Proc. RSA conf.
Cryptography, 2006.
[14] Y.C, Hu, A.Perrig, and D.B. Johnson, “Wormhole
detection in wireless ad hoc networks,” Department of
Computer Science, Rice University, Tech. Rep TR01-
384, June 2002.

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Detection of Vampire Attacks in Ad-Hoc Wireless Sensor Network Evaluation and Protection

  • 1. International Journal of Trend in Scientific Research and Development (IJTSRD) Volume: 3 | Issue: 2 | Jan-Feb 2019 Available Online: www.ijtsrd.com e-ISSN: 2456 - 6470 @ IJTSRD | Unique Reference Paper ID - IJTSRD20300 | Volume – 3 | Issue – 2 | Jan-Feb 2019 Page: 438 Detection of Vampire Attacks in Ad-Hoc Wireless Sensor Network Evaluation and Protection Anand. M Assistant Professor, Department of Information Science & Engineering, GSSSIETW, Mysuru, Karnataka, India ABSTRACT Wireless Sensor Networks (WSNs) in today’s world are the means of communication. These contain nodes that act as transmitter and receivers are prone to different attacksleadingtodifferenttypesof losses. Theresourcedepletionattack thatis called vampire attack drains out the energy from thenodesleavingthemuseless.These attacks are protocol compliant,they are easy to implement. Since they are orthogonal in nature they can easily intrude into any routing protocol. They affecttheentire network causing large loss of energy and A vampire attack is caused bythemaliciousnodeonthedecentralized ad hocwireless network. The paper analyses how protocols faces these attacks. Vampire attacks are not protocol specific rather uses its compliant message. The current security measures to prevent these attacks are been reviewed along with resultof simulation of representative protocols in the presence of a vampire attack is been presented. The paper also describes how the existing sensor network protocol is been modified for protection from the vampire attacks for which PLGP (Parno, Luk, Gaustad and Perrig) solution is also been proposed. KEYWORDS: Wireless Sensor Network; Denial of service; Resource depletion; Routing; Energy consumption; Security; carousel attack; stretch attack; PLGP I. INTRODUCTION Ad hoc wireless sensor network consists of various sensors that are expanded in a space where each sensor performs signal processingand datanetworkingprovidingoperational efficiency. The ad hocwirelessservers areself-organizedand energy constrained. These sensor networks are used to detect information of enemy base, monitor environmental changes and are also used for security purposes in various places like shopping and parking area and when these networks face attacks causing negative effect by causing battery exhaustion and higher energy utilization. Fig 1: Ad hoc Wireless sensor network Vampire attacks are caused when amessageisbeeninitiated and transmitted through a malicious node over the network causing higher battery utilization and battery exhaustion. Vampire attacks are not constrained to a specific type of protocol and does not alter specific path in the network. When a network is been attacked by them, even transfer of small data consumes more energy. Fig 2: Architecture of WSN The basic architecture of a WSN [10] contains number of nodes that act as routing nodes, sensing nodes and base nodes. Figure 2 shows the architecture of a WSN, where all the different types of nodes are shown.Itisalsopossiblethat every node in the network functions as an aggregationpoint, delaying transmission of an outgoing message until a sufficient number of incoming messages have been received and aggregated. Power management in sensor networks is critical. Consequently, if we want sensor networks tolast for years, it is crucial that they run at around a 1%dutycycle (or less). Similarly, since the power consumption of the radio is three orders of magnitude higher when transmitting or listening than when in sleep mode, it is crucial to keep the radio in sleep mode the overwhelming majority of the time. Sensor networks provide economically viablesolutionsfora wide variety of applications, includingsurveillanceof critical infrastructure, safety monitoring, and many health-care applications [6]. As sensor networks are increasingly deployed in such security-and safety critical environments, the need forsecurecommunicationprimitivesisself-evident. Likewise, the development of such primitives facilitates the use of sensor networks in a wider range of applications. The central goal of this work is to ensure node-to-node message delivery, even if the sensor network is under active attack
  • 2. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Reference Paper ID - IJTSRD20300 | Volume – 3 | Issue – 2 | Jan-Feb 2019 Page: 439 [8]. The presence of an attacker, it is an extremely challenging task to maintaincorrectroutinginformation;the attacker could inject malicious routing information or alter routing setup/update messages from legitimatenodes.Even when route setup/update messages are authenticated, compromised sensor nodes can supply incorrect routing information of their own and cripple the routing infrastructure. WSNs consist of nodes they are independent and have no infrastructure. The nodes of WSN consists of Data acquisition unit, Data transfer unit and Process unit to which power is supplied as shown in the figure 3. These nodes are used in different fields to gather information in different ways. Base stations are typically many orders of magnitude more powerful than sensor nodes [12]. They might have workstation or laptop class processors,memory, and storage, AC power, and high bandwidth links for communication amongst themselves. Fig 3: Nodes of WSN The sensors are constrained to use lower-power, lower- bandwidth, shorter-range radios, and so it is envisioned that the sensor nodes would form a multi-hop wireless network to allow sensors to communicate to the nearest base station. A base station might request a steady stream of data, such as a sensor reading every second, from nodes able to satisfy a query [9]. We refer to such a stream as a data flow and to the nodes sending the data as sources. In order to reduce the total number of messages sent and thus save energy, sensor readings from multiple nodes may be processed at one of many possible aggregation points. An aggregation point collects sensor readings from surrounding nodes and forwards a single message representing an aggregate of the values. Aggregation points [3] are typically regular sensor nodes, and their selection is not necessarily static. Aggregation points could be chosen dynamically for each query or event. II. PROTOCOLS AND ASSUMPTIONS In this paper we discuss the effect of vampire attacks on Ad- hoc On Demand Vector Routing (AODV) [5]. AODV is a reactive protocol for ad-hoc and a mobile network that maintains routes only between nodes which need to communicate. The routing messages do not contain information about the entire route path, but only about the source and destination. Therefore routing messages don’t not have an increasing size. It uses destination sequence numbers to specify how fresh a route is, which is used to grant loop freedom. As seen in figure 4, whenever a node needs to send a packet to a destination for which it has no „fresh enough‟ route (i.e., a valid route entry for the destination whose associated sequence number isat leastas great as the ones contained in any RREQ that the node has received for that destination) it broadcasts a route request (RREQ) message to its neighbors. Each node that receives the broadcast sets up a reverse route towards the originator of the RREQ (unless it has a „fresher‟ one). When the intended destination (or an intermediate node that has a „fresh enough‟ route to the destination) receives the RREQ, it replies by sending a Route Reply (RREP). It is importantto note that the only mutable information in a RREQ and in a RREP is the hop count (which is being monotonically increased at each hop). The RREP travels back to the originator of the RREQ (this time as a unicast). At each intermediate node, a route to the destination is set (again, unless the node has a „fresher‟ route than the one specified in the RREP). In the case that the RREQ is replied to by an intermediate node (and if the RREQ had set this option), the intermediate node also sends a RREP to the destination. In this way, it can be granted that the route path is being set up bidirectional. In the case that a node receives a new route (by a RREQ or by a RREP) and the node already has a route „as fresh‟ as the received one, the shortest one will be updated. If there is a subnet (a collection of nodes that are identified by a common network prefix) that does not use AODV as its routing protocol and wants to be able to exchange information with an AODV network, one of the nodes of the subnet can be selected as their „network leader‟. The network leader is the only node of the subnet that sends forwards and processes AODV routing messages and every RREP that the leader issues, it sets the prefix size of the subnet optionally. A Route Reply Acknowledgment (RREP-ACK) message may be sent by the originator of the RREQ to acknowledge the receipt of the RREP. Fig 4: AODV protocol RREP-ACK message has no mutable information. In addition to these routing messages, Route Error (RERR) message are used to notify the other nodes that certain nodes are not anymore reachable due to a link breakage. When a node rebroadcasts a RERR, it only adds the unreachable destinations to which the node might forward messages. Therefore, the mutable information in a RERR is the list of unreachable destinations and the counter of unreachable destinations included in the message. Anyway, it is predictable that, at each hop, theunreachabledestination list may not change or become a subset of the original one. The vampire attack disrupts the AODV protocols ability to avoid loops and choose the shortest path, AODV are prone to wormhole attacks [14] and false injection of data [7] which can be avoided by using an encryption system [7] [13] [11].
  • 3. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Reference Paper ID - IJTSRD20300 | Volume – 3 | Issue – 2 | Jan-Feb 2019 Page: 440 III. VAMPIRE ATTACK DETECTION There are two types of attacks in WSN, the routing depletion and resource depletion attack. The routingdepletionattacks usually only affect the routing path the resource depletion attacks are the ones that attack the network features like bandwidth, power, and energy consumption. These attacks are commonly called as “Vampire attacks” [2]. They are called so because they drain the battery power from the nodes. These are a type of Denial of Service [1] since they affect the entire system from performing. They are difficult tobe detected since they are protocol compliant and are orthogonal to them [4]. They are not protocol specific. They do not affect a single node they take their time attack one by one and disrupt the entire system. Vampire attacks can be defined as the composition and transmission of a message that cause more energy to be consumed by thenetwork than if an honest node transmitted a message of identical size to the same destination, although using different packet headers. The strength of the attack is measured by the ratio of network energy used in the benign casetotheenergyused in the malicious case. Safety from Vampire attacks implies that this ratio is 1. Energy use by malicious nodes is not considered, since they can always unilaterally drain their own batteries. A. Carousel attack In this attack, an adversary composes packets with purposely introduced routing loops. It is called carousel attack, since it sends packets in circles as shown in Figure 4. It targets source routing protocols by exploiting the limited verification of message headers at forwarding nodes, allowing a single packet to repeatedly traverse the same set of nodes. On average, a random located carousel attacker in the example mentioned topology can increase the network energy consumption by a factor of 1.48±0.99. Fig 5: Carousel attack The reason for this large standard deviation is that the attack does not always increase energy usage, the length of the adversarial path is a multiple of the honestpath, which is in turn, affected by the position of theadversary’s position of the adversary in relation to the destination, so the adversary’s position is important to the success of this attack. Figure 5 shows the network under attack where the packets are sent in loops causing more usage of energy and time. B. Stretch attack In this attack, also targeting source routing, an adversary constructs artificially long routes, potentially traversing every node in the network. It is call this the stretch attack, since it increases packet path lengths, causing packets to be processed by a number of nodes that is independent of hop count along the shortest path between the adversary and packet destination. An example is illustrated in figure 6. In the example topology, thereisanincreaseinenergyusage by as much as a factor of 10.5 per message over the honest scenario, with an average increases in energy consumption of 2.67±2.49. As with the carousel attack, the reason for the large standard deviation is that the position of the adversarial node affects the strength of the attack. Not all routes can be significantly lengthened, depending on the location of the adversary. Fig 6: Stretch attack The carousel attack, where the relative positions of the source and sink are important, the stretch attackcanachieve the same effectiveness independent of the attacker’s network position relative to the destination, so the worst- case effect is far more likely to occur .The impact of these attacks can be further increased by combining them, increasing the number of adversarial nodes in the network, or simply sending more packets. Although in networks that do not employ authentication or only use end-to-end authentication, adversaries are free to replace routes in any overhead packets, we assume that only messages originated by adversaries may have maliciously composed routes. IV. SECURITY AGAINST VAMPIRE ATTACKS A Clean Slate Sensor Network Routing by PLGP (Parno, Luk, Gaustad and Perrig) can be applied which consists of two phases: 1. Topology Discovery Phase 2. Packet Forwarding Phase 1. Topology Discovery Phase: A node starts with its virtual address as zero. At each node a certificate is been issues which contains the public key for identification. Each node is connected to the other and shares virtual address, public key and the certificate when they merge with closest nearby group.
  • 4. International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470 @ IJTSRD | Unique Reference Paper ID - IJTSRD20300 | Volume – 3 | Issue – 2 | Jan-Feb 2019 Page: 441 Fig 7: Topology Discovery Phase 2. Packet Forwarding Phase: The packets are forwarded in this phase as shown in figure 8. Fig 8: Packet Forwarding Phase PLGP proposed a solution which suggests: A. Providing a verifiable path history to all the packets involved. B. Using this path history the packet transmission can take place through every node securely passing through at least one honest node. C. Each node upon receiving the message, checks for authentication in the chain. CONCLUSION In this paper, the routing protocolaffectedbyvampire attack in WSN is discussed. This is a new class of resource consumption attack that use routing protocols to permanently disable ad-hoc WSNs by depleting node’s battery power. Simulation results show that depending on the location of adversary, network energy expenditure during the forwarding phase increasing. The security flaws of AODV can be fixed by using RSA encryption system that will avoid the adversary from entering the system. These attacks does not depend on particular type of protocol and Ad hoc network sensors have been applied in various fields which needs to create and identify solutions for prevention of the network from these attacks. There are different types of vampire attacks depending on the protocol. When the attack take place it not only consumeshigherpowerbutalso takes additional time. There are many solutions and techniques that have been presented to prevent these attacks but were not effective enough which creates a need for a better solution. PLGP solutions can be applied to these protocols in order to prevent these networks that are often prone to vampire attacks. REFERENCES [1] A. Wood and J. Stankovic. Denial of Service in sensor networks. IEEE Computer, pages 54-62, Oct, 2002. [2] Eugene Y. Vassermann and Nicholas Hopper “Vampire Attacks: Draining Life from Wireless Ad Hoc Sensor Networks” IEEE Trans. Mobile Computing, vol. 12, no. 2, pp. 318-332 Feb-2013. [3] B. Przydatek, D. Song, and A. Perrig. SIA:Secure information aggregation in sensor network. In ACM SenSys, Nov 2003. [4] B. Karp and H. T. Kung, “GPSR: greedy perimeter stateless routing for wireless networks.” In mobile Computing and Networking, 2000, pp.243-254. [5] C. Perkins and E. Royer, “Ad-hoc on demand distance vector routing,” in MILCOM ‟97 panel on Ad Hoc Networks, 1997. [6] Chris Karloff and David Wager “Secure Routing in Wireless Sensor Networks: Attacks and countermeasures” Proc. IEEE Int‟l workshop sensor network protocols and applications, 2003. [7] F. Ye, H. Luo and S. “Statistical En-Route Filtering of Injected False Data in Sensor Networks,” IEEE Journal on Selected Areas in Communication, vol. 23, No.4, 2005, pp.839-8. [8] H. Chan and A. Perrig, “Security and Privacy in Sensor Networks,” Computer, vol. 36, no. 10, pp. 103-105, Oct. 2003. [9] J. Deng, R. Han, and S. Mishra, “Maximum Lifetime Routing in Wireless Sensor Networks,” IEEE/ACM Trans. Networking, vol 12. 4, pp. 609-619, Aug. 2004. [10] J.Hill, R.Szewczyk, A. Woo, S. Hollar, D. Culler, and K. Pister, “System architecture directions for networked sensors,” in Proceedings of ACM ASPLOS IX, November 2000. [11] L. Buttyan, et al., “Statistical Wormhole Detection in Sensor Networks,” Lecture Notes in Computer Science Vol. 3813, 2005, pp. 128-141. [12] M. Tubaishat and S. Madria, “Sensor Networks: An Overview,” IEEE Potentials, Vol. 22, No. 2,2003, pp.20- 23. doi:10.1109/MP.2003.1197877. [13] M. McLoone and M. Robshaw, “Public Key Cryptography and RFID Tags,” Proc. RSA conf. Cryptography, 2006. [14] Y.C, Hu, A.Perrig, and D.B. Johnson, “Wormhole detection in wireless ad hoc networks,” Department of Computer Science, Rice University, Tech. Rep TR01- 384, June 2002.