Wireless Sensor Networks have emerged as an important new area in wireless
technology. In the near future, the wireless sensor networks are expected to consist of
thousands of inexpensive nodes, each having sensing capability with limited
computational and communication power  which enable us to deploy a large-scale
A wireless network consists of tiny devices which monitor physical or
environmental conditions such as temperature, pressure, motion or pollutants etc. at
different areas. Such sensor networks are expected to be widely deployed in a vast
variety of environments for commercial, civil, and military applications such as
surveillance, vehicle tracking, climate and habitat monitoring, intelligence, medical, and
acoustic data gathering. The key limitations of wireless sensor net-works are the storage,
power and processing. These limitations and the specific architecture of sensor nodes
call for energy efficient and secure communication protocols. The feasibility of these
inexpensive sensor networks is accelerated by the advances in MEMS (Micro
Electromechanical Systems) technology, combined with low power, low cost digital
signal processors (DSPs) and radio frequency (RF) circuits .They consists of a radio
transceiver, microcontroller, power supply, and the actual sensor. The sensing circuitry
measures ambient condition related to the environment surrounding the sensor and
transforms them into an electric signal. Processing such a signal reveals some properties
about objects located and/or events happening in the vicinity of the sensor. The sensor
sends such collected data, usually via radio transmitter, to a command center (sink)
either directly or through a data concentration center (a gateway).
Normally sensor nodes are spatially distributed throughout the region which has
to be monitored; they self-organize in to a network through wireless communication,
and collaborate with each other to accomplish the common task. Basic features of sensor
networks are self-organizing capabilities, dynamic network topology, limited power,
node failures and mobility of nodes, short-range broadcast communication and multi-
hop routing, and large scale of deployment . The strength of wireless sensor network
lies in their flexibility and scalability. The capability of self-organize and wireless
communication made them to be deployed in an ad-hoc fashion in remote or hazardous
location without the need of any existing infrastructure. Through multi-hop
communication a sensor node can communicate a faraway node in the network. This
allows the addition of sensor nodes in the network to expand the monitored area and
hence proves its scalability and flexibility property.
The key challenge in sensor networks is to maximize the lifetime of sensor
nodes due to the fact that it is not feasible to replace the batteries of thousands of sensor
nodes. Therefore, computational operations of nodes and communication protocols must
be made as energy efficient as possible. Security in data communication is another
important issue to be considered while designing wireless sensor networks, as wireless
sensor networks may be deployed in hostile areas such as battlefields. Therefore, data
aggregation protocols should work with the data communication security protocols, as
any conflict between these protocols might create loopholes in network security.
1.1 Wireless Sensor Network Model
Unlike other networks, WSNs are resource limited, they are deployed densely,
they are prone to failures, the number of nodes in WSNs is several orders higher than
that of ad hoc networks, WSN network topology is constantly changing, WSNs use
broadcast communication mediums and finally sensor nodes don’t have a global
identification tags . The major components of a typical sensor network are fig1:
Fig1.1 Components of Wireless Sensor Networks
• Sensor Field:
A sensor field can be considered as the area in which the nodes are placed.
• Sensor Nodes
Sensors nodes are the heart of the network. They are in charge of collecting data
and routing this information back to a sink.
A sink is a sensor node with the specific task of receiving, processing and
storing data from the other sensor nodes. They serve to reduce the total number of
messages that need to be sent, hence reducing the overall energy requirements of the
network. The network usually assigns such points dynamically . Regular nodes can
also be considered as sinks if they delay outgoing messages until they have aggregated
enough sensed information. Sinks are also known as data aggregation points.
• Task Manager
The task manager also known as base station is a centralized point of control
within the network, which extracts information from the network and disseminates
control information back into the network. It also serves as a gateway to other networks,
a powerful data processing and storage centre and an access point for a human interface.
The base station is either a laptop or a workstation. Data is streamed to these
workstations either via the internet, wireless channels, satellite etc. . Hundreds to
several thousand nodes are deployed throughout a sensor field to create a wireless multi
hop network. Nodes can use wireless communication media such as infrared, radio,
optical media or Bluetooth for their communications. The transmission range of the
nodes varies according to the communication protocol is use.
1.2 Sensor Network Challenges
Wireless sensor network uses a wide variety of application and to impact these
applications in real world environments, we need more efficient protocols and
algorithms. Designing a new protocol or algorithm address some challenges which are
need to be clearly understood . These challenges are summarized below:
1.2.1 Physical Resource Constraints
The most important constraint imposed on sensor network is the limited battery
power of sensor nodes. The effective lifetime of a sensor node is directly determined by
its power supply. Hence lifetime of a sensor network is also determined by the power
supply. Hence the energy consumption is main design issue of a protocol. Limited
computational power and memory size is another constraint that affects the amount of
data that can be stored in individual sensor nodes. So the protocol should be simple and
light-weighted. Communication delay in sensor network can be high due to limited
communication channel shared by all nodes within each other's transmission range.
1.2.2 Ad-hoc Deployment: Many applications are requires the ad-hoc deployment of
sensor nodes in the specific area. Sensor nodes are randomly deployed over the region
without any infrastructure and prior knowledge of topology . In such a situation, it is
up to the nodes to identify its connectivity and distribution between the nodes. As an
example, for event detection in a battlefield the nodes typically would be dropped in to
the enemy area from a plane.
1.2.3 Fault-Tolerance: In a hostile environment, a sensor node may fail due to physical
damage or lack of energy (power). If some nodes fail, the protocols that are working
upon must accommodate these changes in the network. As an example, for routing or
aggregation protocol, they must find suitable paths or aggregation point in case of these
kinds of failures.
1.2.4. Scalability: Most of the applications are needed; the number of sensor nodes
deployed must be in order of hundreds, thousands or more[1,3]. The protocols must
scalable enough to respond and operate with such large number of sensor nodes.
1.2.5. Quality of Service: Some real time sensor application are very time critical which
means the data should be delivered within a certain period of time from the moment it is
sensed, otherwise the data will be unusable .So this must be a QoS parameter for some
1.2.6Unattended operation: In many application sensor networks is deployed once, and
after deployment have no human intervention. Hence the nodes themselves are
responsible for reconciliation in case of any changes.
1.2.7. Untethered: The sensor nodes are not connected to any energy source. They have
only a finite source of energy, which must be optimally used for processing and
communication. To make optimal use of energy, communication should be minimized
as much as possible.
1.2.8. Security: Security is very critical parameter in sensor networks, given some of the
proposed applications. An effective compromise must be obtained, between the low
bandwidth requirements of sensor network applications and security demands for secure
data communication in the sensor networks (which traditionally place considerable
strain on resources).Thus, unlike traditional networks, where the focus is on maximizing
channel throughput with secure transmission.
1.3 Applications of Wireless Sensor Network
1.3.1 Military Applications
The concept of wireless sensor network is very closely related to the military
applications. Regarding military applications the area of interest extents from
information collection to enemy tracking, battle field surveillance or target tracking.
Classification algorithms use, for instance, input data that come from seismic and
acoustic signal sensing . For example, in near future mines can be replaced by sensor
nodes which will detect the intrusion of hostile units. In spite of being used in war times
wireless sensor nodes can also be used in peace times such as homeland security,
property protection and etc.
1.3.2 Environment Monitoring
These applications are related to animal tracking, behavior monitoring wildlife
protection, weather conditions and environmental disasters monitoring. Sensor nodes
are deployed indoor to monitor light and temperature. The capability of sensor nodes to
detect light, air pollution, frame status (windows and doors), air streams can be utilized
for optimal control of indoor environment
1.3.3 Agricultural Applications
Sensor nodes are deployed in the agricultural fields with the firm motive of enhancing
the eﬃciency and growth of cultivation describes the case of deploying sensor nodes in
a vine yard, and how the sensor networks turned out to be useful for the farmers from
the time of growing grapes to wine production and marketing.
1.3.4 Support for logistics
Wireless sensor networks are used in case of fleet management, which tracing of
loading trucks and tracking of parameters regarding carried goods.
1.3.5 Human Centric Applications
Human Science and health care systems can also benefit from the use of wireless
sensor networks . For patients monitoring inside hospitals and at home, tracking the
patients vitals or other information of interest and making it available to doctors for
further medication at anytime from anywhere securely through the Internet. Cognitive
disorders, which perhaps lead to Alzheimer’s, can be monitored and controlled at their
early stages, using wireless sensors.
1.3.6 Public Safety
In applications where chemical, biological or other environmental threats are
monitored, it is vital that the availability of the network is never threatened. Attacks
causing false alarms may lead to panic responses or even worse total disregard for the
The monitoring of material fatigue was made by experts introducing the
observed situation inside devices to be collected on a central site for processing. Further
sensing techniques were developed on the form of wired sensors; nevertheless its
implementation was slow and expensive due the necessary wiring. WSNs bring the best
of both methods by sensing the events without the need of expert personnel and the cost
of wiring .
Other applications of WSN are traffic controlling, resource management,
product quality monitoring, smart offices/houses; underground and underwater
monitoring, guidance & watch over manufacturing environments, interactive fairs,
process control industry, automobiles, machine analysis, transportation management,
automobile tracking and detection and spectrum detection for cognitive radio networks
ROUTING IN WIRELESS SENSOR NETWORKS
Since transmission of data from the targeted source to the sink is the main task
of the wireless sensor networks, the method used to do the data forwarding is an
important issue which should be considered in developing these networks.
Considering the unique features of low power wireless sensor networks, routing in
WSN is much more challenging compared to traditional wireless networks such as ad-
hoc networks [3, 4]. First, considering the high density of nodes, the routing protocols
should route data over long distances, regardless of the network structure and size, in
addition to the above requirement some of the active nodes may fail during the
operations due to the environmental factors or energy depletion of sensor nodes or
hardware faults, but these issues should not interrupt the normal operations of the
network. Moreover, as mentioned earlier the wireless sensor nodes are restricted in
terms of power supply, processing capability and available bandwidth, routing and data
forwarding should be performed with eﬀective network resource utilization. Further,
considering the performance demands of the wireless sensor networks are totally
application dependent, routing algorithms should satisfy the QoS demands of the
application for which the network is being deployed. For example, challenges in
designing the routing algorithms for environment monitoring will be diﬀerent from
issues that should be considered for health care monitoring or target tracking.
2.1 Types of Routing Protocol in WSN
Based on the diﬀerences between wireless sensor networks and traditional
wireless networks, various routing protocols were proposed over the past few years [3,
5], to address the routing challenges introduced by the new features of the wireless
sensor networks. From network point of view fig 2.1, routing algorithms are classified
as flat, hierarchical and location based routing protocols.
Figure 2.1 Types of Routing Protocols
2.1.1 Flat routing protocols
They are designed for network structure with homogeneous nodes meaning all
nodes have the same transmission and processing capability. Directed Diﬀusion ,
Sensor Protocol for Information via Negotiation (SPIN) , Rumour Routing ,
Minimum Cost Forwarding Algorithm (MCFA) , Energy Aware Routing (EAR) 
can also be added in this category. In this group of protocols they demonstrate several
advantages such as low topology maintenance overhead and the ability of multi-path
2.1.2 Hierarchical routing protocols
They were proposed to increase the scalability of the network and make the
network energy eﬃcient through node clustering. In this group of protocols all the
sensor nodes are grouped into clusters and each cluster will have a cluster head which
will be responsible for the collection of data from its cluster nodes, data processing and
then forwarding the data towards the sink node. Though this structure provides high
network scalability, clustering operation but the cluster head replacement impose high
signaling overhead to the network. Several routing algorithms such as Low-Energy
Adaptive Clustering Hierarchy (LEACH), Threshold-Sensitive Energy-Eﬃcient Sensor
Network Protocol (TEEN) fall in this category .
2.1.3 Location based routing protocols
This routing protocol utilizes the exact location of the sensor nodes for the
routing purposes. The geographic Location of the nodes can be obtained directly using
Global Positioning System (GPS) devices or indirectly through exchanging some
information regarding to the signal strengths received at each node. Since the
localization requires special hardware support and also imposes significant computation
overhead, this approach cannot be easily used in resource constrained wireless sensor
networks. Geographic and Energy-Aware Routing (GEAR)  and Geographic
Adaptive Fidelity (GAF) can be referred as the geographic routing protocols.
From the protocol operation perspective, the existing protocols can be classified
into negotiation based, query based, QoS based, multi-path based and coherent-based
Negotiation based routing protocols was designed to provide energy-eﬃcient
communication by reducing the data redundancy during data transmission. Each sensor
adds a high level data description to its collected data and performs some negotiations
with all its neighboring nodes to eliminate the redundant data packets. SPIN  is an
example of such type of protocol.
In the query based routing protocols, the sink node sends a query throughout the
network regarding the desired sensing task. If any node senses any related query it sends
back the collected data through the reverse path. Directed Diﬀusion  and Rumor
Routing  are two examples of the query-based routing protocols.
The next groups of protocols are the QoS based protocols is mainly designed to
satisfy the QoS demands (delay, reliability, and bandwidth) of the diﬀerent applications.
The main aim of these types of protocols is to establish the trade oﬀ between the data
quality and energy consumption. Sequence Assignment Routing (SAR), SPEED,
Multipath Multi-SPEED (MMSPEED), Delay-minimum Energy-aware Routing
Protocol(DERP) can be considered as the QoS-aware routing algorithms.
Multi-path Routing protocols in contrast to the single path routing protocols
provide multiple paths between the source and sink, there are many routing algorithms
that fall under this category, for example Braided Multipath Routing, N-to-1 Multipath
Routing Protocol .
In the last group of protocols the coherent based protocols, as all the network
nodes process the same flooded data in the network, the algorithms are based on
coherent data processing to avoid flooding . In this group of protocols data packets
are sent to the aggregators in order to reduce data redundancy. Routing algorithms such
as Directed Diﬀusion, SPIN and SAR use data aggregation and can fall under coherent
data processing -based routing protocols.
Chapter – 3
SECURITY ISSUES IN WIRELESS SENSOR NETWORKS
3.1 Obstacles of Sensor Security
A wireless sensor network is a special network which has many constraints
comparing to the other networks. These constraints make difficult to directly employ the
existing security to the wireless sensor networks. The followings are the brief discussion
on these constraints of a sensor network .
3.1.1 Limited Resources
Security approach requires a certain amount of resources for the implementation,
including data memory, code space, and energy to power the sensor. However, currently
these resources are very limited in a tiny wireless sensor.
•Limited Memory and Storage Space - A sensor is a tiny device with only a small
amount of memory and storage space for the code. In order to build an effective security
mechanism, it is necessary to limit the code size of the security algorithm. For example,
one common sensor type has an 8-bit, 4MHz CPU only with only 4.5K available disk
space. Due to such limitation, the security related code must also be quite small .
•Limitation Power Energy – Limited power is the biggest constraint of the wireless
sensor networks. It is not feasible to replace or recharge the thousands of high cost of
sensors. Therefore, the battery charge taken with them to the field must be conserved to
extend the life of the individual sensor node as well as the entire sensor network. The
processing of security related functions (e.g., encryption, decryption, signing data,
verifying signatures) consume extra battery power.
3.1.2 Unreliable Communication
Unreliable communication is another key challenge to sensor security. The network
security depends on network protocol, which in turn depends on communication.
• Unreliable Transfer - The packet-based routing of the sensor network is
normally connectionless and thus inherently unreliable. Packets may get
damaged due to channel errors or dropped at highly congested nodes.. The
result is lost or missing packets. If the protocol lacks of appropriate error
handling, it is possible to lose critical security packets. This may include, for
example, a cryptographic key.
• Conflicts - In a high-density sensor network if packets meet in the middle of
transfer, conflicts will occur and the transfer itself will fail which can be a major
problem in providing security.
• Latency - The multi-hop routing, network congestion, and node processing can
lead to the latency of the network, thus make it difficult to achieve the
synchronization among sensor nodes . The synchronization issues can be
critical to sensor security.
3.1.3 Unattended Operation
The sensor nodes may be left unattended for long periods of time for a particular sensor
network. There are three main caveats to unattended sensor nodes as describe follow.
Exposure to Physical Attacks - The sensor may be deployed in an environment
open to adversaries, bad weather, and so on. These sensors may suffer a physical
attack in such an environment.
Managed Remotely - Remote management of a sensor network makes it virtually
impossible to detect physical tampering and physical maintenance issues. The
longer that a sensor is left unattended the more likely that an adversary has
compromised the node.
3.2 Security Requirements
A sensor network also poses unique requirements of its own as well as shares some
commonalities with a typical computer network. The factors related to the security of a
sensor network are divided in primary and secondary goals and they are :
The primary goals are:
• Data Confidentiality
A sensor network should not leak it data to its neighbors. In many applications
nodes communicate highly sensitive data, e.g., key distribution. It is very important to
build a secure channel in a wireless sensor network. The standard approach for keeping
sensitive data secret is to encrypt the data with a secret key.
• Data Integrity
The adversary may modify the transmitting data, e.g. add some fragments or
decrees the data within a packet. This new packet can then be sent to the original
receiver. Data integrity ensures that any received data has not been modified in transit.
• Data Freshness
Data freshness suggests that the data is recent, and it ensures that no old data is
re-transmitted. This requirement is especially important when there are shared-key
strategies employed in the design. It is also disrupt the normal work of the sensor. To
solve this problem a time-related counter can be added into the packet to make ensure
An adversary can change the whole packet stream by injecting additional
packets. So the receiver needs to ensure that the data is sent by the original sender. On
the other hand, when constructing the sensor network, authentication is necessary for
many administrative tasks (e.g. network reprogramming or controlling sensor nodes
Adjusting the traditional encryption algorithms to fitting in the wireless sensor
network is not free, and will introduce some extra costs. Moreover, additional
computation consumes additional energy. If no more energy exists, the data will no
longer be available . The requirement of security is highly important in maintaining
the availability of the whole network.
The Secondary goals are:
• Data Freshness
Even if confidentiality and data integrity are assured, there is a need to ensure
the freshness of each message. Informally, data freshness  suggests that the data is
recent, and it ensures that no old messages have been replayed. To solve this problem a
nonce, or another time-related counter, can be added into the packet to ensure data
A wireless sensor network is a typically an ad hoc network, which requires every
sensor node be independent and flexible enough to be self-organizing and self-healing
according to different situations. There is no fixed infrastructure available for the
purpose of network management in a sensor network. This inherent feature brings a
great challenge to wireless sensor network security. If self-organization is lacking in a
sensor network, the damage resulting from an attack or even the risky environment may
• Time Synchronization
Most sensor network applications rely on some form of time synchronization.
Furthermore, sensors may wish to compute the end-to-end delay of a packet as it travels
between two pairwise sensors. A more collaborative sensor network may require group
synchronization  for tracking applications.
• Secure Localization
Often, the utility of a sensor network will rely on its ability to accurately and
automatically locate each sensor in the network. A sensor network designed to locate
faults will need accurate location information in order to pinpoint the location of a fault.
Unfortunately, an attacker can easily manipulate not secured location information by
reporting false signal strengths, replaying signals.
3.3 Attacks on Wireless Sensor Network
Wireless Sensor networks are vulnerable to security attacks due to the broadcast nature
of the transmission medium. Furthermore, wireless sensor networks have an additional
vulnerability because nodes are often placed in a hostile or dangerous environment
where they are not physically protected. Basically attacks are classified as active attacks
and passive attacks. Figure1 shows the classification of attacks under general categories
and Figure 3.1 shows the attacks classification on WSN.
Fig 3.1 Classifications of Security Attacks in WSN
Many sensor network routing protocols are quite simple and therefore facing multiple
types of attacks as described below:
3.3.1 Passive Attacks
The monitoring and listening of the communication channel by unauthorized attackers
are known as passive attack. The Attacks against privacy is passive in nature.
Attacks against Privacy: The main privacy problem is not that sensor networks
enable the collection of information. In fact, much information from sensor networks
could probably be collected through direct site surveillance. Rather, sensor networks
intensify the privacy problem because they make large volumes of information easily
available through remote access. Hence, adversaries need not be physically present to
maintain surveillance. They can gather information at low-risk in anonymous
manner. Some of the more common attacks  against sensor privacy are:
Monitor and Eavesdropping: This is the most common attack to privacy. By
snooping to the data, the adversary could easily discover the communication
contents. When the traffic conveys the control information about the sensor
network configuration, which contains potentially more detailed information
than accessible through the location server, the eavesdropping can act effectively
against the privacy protection.
Traffic Analysis: Even when the messages transferred are encrypted, it still
leaves a high possibility analysis of the communication patterns. Sensor
activities can potentially reveal enough information to enable an adversary to
cause malicious harm to the sensor network.
Camouflage Adversaries: One can insert their node or compromise the nodes to
hide in the sensor network. After that these nodes can copy as a normal node to
attract the packets, then misroute the packets, conducting the privacy analysis
3.3.2 Active Attacks
The unauthorized attackers monitors, listens to and modifies the data stream in the
communication channel are known as active attack. The following attacks are active in
1) Routing Attacks in Sensor Networks
The attacks which act on the network layer are called routing attacks. The following are
the attacks that happen while routing the messages.
Spoofed, altered and replayed routing information
• An unprotected ad hoc routing is vulnerable to these types of attacks, as every
node acts as a router, and can therefore directly affect routing information.
• Create routing loops
• Extend or shorten service routes
• Generate false error messages
• Increase end-to-end latency
A malicious node can selectively drop only certain packets. Especially effective
if combined with an attack that gathers much traffic via the node. In sensor networks it
is assumed that nodes faithfully forward received messages. But some compromised
node might refuse to forward packets, however neighbors might start using another
Attracting traffic to a specific node in called sinkhole attack. In this attack, the
adversary’s goal is to attract nearly all the traffic from a particular area through a
compromised node. Sinkhole attacks typically work by making a compromised node
look especially attractive to surrounding nodes. 
A single node duplicates itself and presented in the multiple locations. The Sybil
attack targets fault tolerant schemes such as distributed storage, multipath routing and
topology maintenance. In a Sybil attack, a single node presents multiple identities to
other nodes in the network. Authentication and encryption techniques can prevent an
outsider to launch a Sybil attack on the sensor network.
In the Wormhole attack, an adversary tunnels messages received one part of the
network over a low latency link and replays them in a different part. Wormholes can be
used to convince two distant nodes that they are neighbors by relaying packets between
the two of them. These attacks can be combined with selective forwarding or
HELLO Flood Attacks:
An attacker broadcasting routing or other information with large enough
transmission power could convince every node in the network that the adversary is its
neighbor. An adversary can re broadcast overhead packets with enough power to be
received by every node. HELLO floods can be considered as one-way broadcast
wormholes and uses a single hop broadcast to transmit a message to a large number of
nodes unlike the traditional definition of flooding denoting epidemic-like propagation of
a message to every node in the network .
An adversary can spoof link layer acknowledgements for overheard packets
addressed to the neighboring nodes. A sender can be convinced that a weak link is
strong or a dead or disabled node is alive . Since packets sent along weak or dead
links are lost, an adversary can effectively mount a selective forwarding attack using
acknowledgment spoofing by encouraging the target node to transmit more packets on
those weak links.
2) Denial of Service
Denial of Service (DoS) is produced by the unintentional failure of nodes or
malicious action. DoS attack is meant not only for the adversary’s attempt to subvert,
disrupt, or destroy a network, but also for any event that diminishes a network’s
capability to provide a service. In wireless sensor networks, several types of DoS attacks
in different layers might be performed. At physical layer the DoS attacks could be
jamming and tampering, at link layer, collision, exhaustion and unfairness, at network
layer, neglect and greed, homing, misdirection, black holes and at transport layer this
attack could be performed by malicious flooding and de-synchronization. The
mechanisms to prevent DoS attacks include payment for network resources, pushback,
strong authentication and identification of traffic .
3) Node Subversion
Capture of a node may reveal its information including disclosure of
cryptographic keys and thus compromise the whole sensor network. A particular sensor
might be captured, and information (key) stored on it might be obtained by an
4) Node Malfunction
A malfunctioning node will generate inaccurate data that could expose the
integrity of sensor network especially if it is a data-aggregating node such as a cluster
5) Node Outage
Node outage is the situation that occurs when a node stops its function. In the
case where a cluster leader stops functioning, the sensor network protocols should be
robust enough to mitigate the effects of node outages by providing an alternate route .
6) Physical Attacks
Sensor networks typically operate in hostile outdoor environments. In such
environments, the small form factor of the sensors, coupled with the unattended and
distributed nature of their deployment make them highly susceptible to physical attacks,
i.e., threats due to physical node destructions. Unlike many other attacks mentioned
above, physical attacks destroy sensors permanently, so the losses are irreversible. For
instance, attackers can extract cryptographic secrets, tamper with the associated
circuitry, modify programming in the sensors, or replace them with malicious sensors
under the control of the attacker.
7) Message Corruption
Any modification of the content of a message by an attacker compromises its integrity.
8) False Node
A false node involves the addition of a node by an adversary and causes the
injection of malicious data. An intruder might add a node to the system that feeds false
data or prevents the passage of true data. Insertion of malicious node is one of the most
dangerous attacks that can occur. Malicious code injected in the network could spread to
all nodes, potentially destroying the whole network, or even worse, taking over the
network on behalf of an adversary.
9) Node Replication Attacks
Conceptually, a node replication attack is quite simple; an attacker seeks to add a
node to an existing sensor network by copying the node ID of an existing sensor node.
A node replicated in this approach can severely disrupt a sensor network’s performance.
Packets can be corrupted or even misrouted. This can result in a disconnected network,
false sensor readings, etc. If an attacker can gain physical access to the entire network
he can copy cryptographic keys to the replicated sensor nodes. By inserting the
replicated nodes at specific network points, the attacker could easily manipulate a
specific segment of the network, perhaps by disconnecting it altogether .
10) Passive Information Gathering
An adversary with powerful resources can collect information from the sensor
networks if it is not encrypted. An intruder with an appropriately powerful receiver and
well-designed antenna can easily pick off the data stream. Interception of the messages
containing the physical locations of sensor nodes allows an attacker to locate the nodes
and destroy them. Besides the locations of sensor nodes, an adversary can observe the
application specific content of messages including message IDs, timestamps and other
fields. To minimize the threats of passive information gathering, strong encryption
techniques needs to be used .
VARIOUS SECURE ROUTING PROTOCOLS
4.1. Cluster Based Algorithm
This algorithm is used to provide efficient energy consumption by reducing
the data transmission distance of sensor nodes in network by using the uniform
clustering concepts. Cluster head CH is selected by number of nodes is it covering
and amount of energy it can communicate with all of them and base station. The main
hand-outs of this paper are as follows.
Considering a multi-hop network which consists of a source node, a destination node
and setting up the sensor environment for finding disjoint path and weight
Assignment of relay node and construction of the topology to formalize Cooperative
multipath routing under bandwidth constraint.
Implementation of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol.
Fig 4.1 System Architecture for the protocol
Attack on cluster heads and base station we concentrate the behaviour of two different
attacks had the impact on the life time of the sensor network.
It prevents different types of attacks on cluster heeds and base station, thereby
improving the life time of the sensor network.
It also provides a fair delivery ratio .
4.2. Multipath Data Transfer protocol (MDTP)
This protocol works in two phase that are set up phase and transmission phase.
The set up phase includes route discovery, transmission of Multipath Discovery and
Next Hop Discovery message.
1) Multipath Discovery message transmission: Source transmits MPD (Multipath
Discovery) to all next hop neighbours in Nh set; Nh is the set of all one hop
neighbours. The node can directly communicate with the nodes that are listed in this
set without using relay nodes.
2) Next Hop Discovery: Upon receiving the MPD message, the node sends Next Hop
Discovery message (NHD), if and only if the number of paths already established
through the node is less than the threshold and the residual energy of node is more
than the minimum energy, otherwise sends NACK (Negative Acknowledgement)
message. The relay node forwards NHD message to its neighbour. This process is
continued till the NHD reaches destination. After receiving NHD if destination node
is ready for reception of data, it transmits the Ok message to node that has sent NHD
3) After receiving OK message: Upon receiving OK message, the OK message is
forwarded by all relay nodes to their NHD/ MPD sender. When the source node
receives the OK message it adds ok message sender node ID to Mh set which contains
the nodes which are used as next hop nodes in the multipath transmission
In the data transmission phase we select a subset of Mh(m nodes) in order to transmit
the data in multiple paths. These m nodes are selected based on the residual energy in
the nodes (higher energy m nodes). For multipath transmission, the data is split into m
parts. The data is encoded to ensure the reliability of data. The encoding is based on
the Reed Solomon (RS) encoding. The encoded data is transmitted through the
established routes. At the receiving end, the process of encoding is repeated to check
the authenticity of the data, before passing to the upper layer.
MPDT has high delivery ratio and it consumes low energy but end to end delay is
very high as well as it does not provide any security to the network. .
4.3. Secure and Energy Efficient Disjoint Route (SEDR)
In this protocol messages are communicated by secret sharing, by way of
dividing them into packets and by random forwarding. As it is one of the effective
routing strategies to ensure the safety of information. This algorithm transmit packets
to the sink node by using least hop routing so, it also enhances the energy efficiency
of the network.
The concept of this paper is:
1) Formulation the secret-sharing-based disjoint multipath routing problem as an
optimization problem the objective is to deliver sliced packet shares along randomly
generated disjoint paths by the routing scheme, such that both the network security
and lifetime can be maximized.
2) By jointly considering the network security and lifetime, a three-phase routing
scheme called security and energy-efficient disjoint route (SEDR). First, packets are
sliced into shares by (T, M)-threshold secret-sharing algorithm, and our proposed
SEDR scheme disperses these shares in a certain region around the source node.
Second, shares are randomly forwarded along identical hop routes all over the whole
network. Finally, the SEDR algorithm transmits shares to the sink node by using least
Fig.4.2. Example of the SEDR scheme.
3) The security and lifetime performance of scheme is obtained in both single and
multiple-black-hole cases, and the minimal required size of the physically secured
area is derived. Analysis indicates that the network lifetime will not decrease if the
radius of the network is not less than four hops.
This protocol prevent network from black hole attack but the data delivery ratio is
satisfactory but it consumes high energy .
4.4. Data Centric Braided Multipath (DCBM)
In this technique the data is transmitted by using prior path information and
dismantling the loops. The nodes having low delivery rates are not included in the
path. A braided multipath is maintained throughout from source to sink. Reverse path
algorithms are used. The algorithm is designed to achieve and maintain route
resiliency through multiple interleaving routing paths, capable to cope with node
mobility. Simulations results show that the algorithm maintains a delivery ratio
similar to the previously suggested protocols, but requires significantly lower control
packet overhead. Two routing Directed Diffusion and with Directed Diffusion Sleep
wise Interest Retransmission are applied. DCBM reduces loop formation which
increases the delivery ratio and consumes less energy. .
4.5. Distributed Security Framework (DSF)
It works for known security threats and prepared to provide security for the
unknown threats. It works significantly under multiple attacks and is scalable in
nature. It works for both static and mobile attackers but have high use of energy to do
it. The network is divided into clusters.
Fig. 4.3 DFS with various attackers.
The number of clusters is the number of gateway nodes, and every gateway
node is the cluster head of its cluster. A regular sensor joins the nearest cluster which
is located by the cluster head. In a cluster, in order to communicate within a cluster,
the gateway node sends broadcast messages using a single hop to reach the regular
nodes while regular nodes communicate with the gateway node over multiple hops. A
gateway node communicates with other gateway nodes directly or through other
gateway nodes. The gateway nodes have a database component in memory which
maintains the records of various details regarding the previous threats/attacks as well
as regarding the possible oncoming threats/attacks and their respective detection and
defense schemes. DSF protocol protects sensor network from Sybil attack, selective
forwarding attack and worm hole with high delivery ratio but it consumes very high
4.6. Energy Efficient Secure Routing Protocol (EESRP):
This protocol makes uses the sink-oriented grid structure for providing better
delivery ratio. For energy efficiency it employs the farthest-highest energy
dissemination node search to find an efficient path from the source to the sink is
incorporated into our routing protocol and security is taken into protocol design. An
energy-efficient secure routing protocol for WSNs with a stationary sink is proposed
in this paper. Using the location information of the sink, the proposed routing protocol
builds the sink-oriented grids to ensure the path availability from the source to the
sink. Choosing the next hop dynamically by taking the advantage of the node location
and residual energy information, an energy-efficient path for data delivery is selected.
Based on the previously designed energy-efficient routing, the one-way hash chain,
message authentication code, and symmetric encryption are further incorporated into
our routing protocol to achieve secure data forwarding along the path from the source
nodes to the sink. With pre-shared secret keys, every new joining node in the network
is authenticated; neighbor information is built by nodes and the global network
information is collected by the sink.
EESRP prevents from Sybil attack, black hole and wormhole attack. It has a very
good delivery ratio energy consumption is satisfactory and end to end delay is low
4.7.Bio-inspired Self-Organized Secure Autonomous Routing Protocol
It is based on ant colony optimization for optimal route decision in which link
quality and energy factor are considered. It enhances secure real time load distribution
(SRTLD) by providing on demand routing rather than broadcast packets.
Fig.4.4. BIOSARP Design Approach
BIOSARP routing decisions depend on Improved Ant Colony Optimization (IACO).
IACO calculates the optimal routing based on the link packet reception rate (PRR),
end-to-end delay, and remaining battery power, which are acquired from
neighbouring nodes in the boot process. After calculation, the value is stored in a
neighbour table for onward data forwarding. The storing process under BIOSARP
helped to reduce the huge processing delay and traffic overhead. It provides high
throughput. BIOSARP provides very high delivery ratio and low end to end delay
with less energy consumption .
4.8. Sink Toroidal Region Routing (STAR):
This routing strategy addresses location privacy of the node by using unique
routing process and a unique ID to determine the location where the event happened.
It provide privacy for both local and global location of the source and sink nodes for
that every intermediate node which conveys the message to the sink will work as a
fake source node and it employs single path routing. When a normal node has a
message to transmit, the message will first be transmitted to the header node in the
grid. The header node will then forward this message to a randomly selected
intermediate node, within a pre-determined region around the SINK node. The
message is then forwarded to the SINK node from the intermediate node.
Fig. 4.5. Distribution of the STAR area
STAR protocol provides privacy for both local and global location of the nodes. It
uses satisfactory energy but have low delivery ratio and high end to end delay .
CONCLUSION AND FUTURE SCOPE
Wireless Sensor Networks represent a new generation of real-time embedded
systems with significantly different communication constraints. As these devices are
deployed in large numbers, they will need the ability to assist each other to
communicate data back to a centralized collection point. The integration of the sensor,
coupled with unceasing electronic miniaturization, will make it possible to produce
extremely inexpensive sensing device. In wireless sensor network, there are so many
challenges. The main challenges are how to provide maximum lifetime to network
and how to provide secure communication to network. As sensor network totally rely
on battery power, the main aim for maximizing lifetime of network is to conserve
battery power or energy with security considerations. In sensor network, the energy is
mainly consumed for three purposes: data transmission, signal processing, and
hardware operation. It is said in that 70 percent of energy consumption is due to data
transmission. So for maximizing the network lifetime and successful communication,
the process of data transmission should be optimized and adversary effects on the
security should be prevented. The data transmission can be optimized by using
efficient and secure routing protocols and effective ways of data aggregation and
protection. Routing plays a very important role in providing reliable and energy
efficient mechanism. Insufficient quality of data delivery may fail the application
deployed over the wireless sensor network, while an energy wasteful protocol may
significantly shorten the lifetime of the network.
Wireless sensor network is an emerging field and simultaneously security
threats of these networks are also increasing. Routing is prominently effected by the
attacks and this makes the network unreliable. So there is a vast scope for developing
simple yet efficient routing protocols which provide security against these threats.
These protocols may be used in the application where security is a main concern like
in military application real world application and surveillance and tracking. We are
proposing to design a new routing scheme in MATLAB simulator with primary idea
to reduce the data transmission distance of sensor nodes in WSN and later on to
provide a security mechanism for it.
 AV Prabu, Baburaokodavati, Edubilli Rambabu, T. Apparao Mohd. Firose Shaik
and R.Vetriselvan “Wireless Sensor Networks: Review article” VSRD International
Journal of Electrical, Electronics & Comm. Engg. Vol. 1 (1), 2011
 Vivek Katiyar, Narottam Chand, Naveen Chauhan “Recent advances and future
trends in Wireless Sensor Networks” International Journal of Applied Engineering
Research, Dindigul volume 1, No 3, 2010
Ian F. Akykildiz, Weilian Su, Yogesh Sankarasubramaniam, and Erdal Cayirci,
“A Survey on Sensor Networks”, IEEE Communication Magazine, 2002
 Nikolaos A. Pantazis, Stefanos A. Nikolidakis and Dimitrios D. Vergados,
“Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey” IEEE
Communications Surveys & Tutorials, Vol. 15, No. 2, Second Quarter 2013
 G. Padmavathi, D. Shanmugapriya “A Survey of Attacks, Security Mechanisms
and Challenges in Wireless Sensor Networks” (IJCSIS) International Journal of
Computer Science and Information Security, Vol. 4, No. 1 & 2, 2009
 R. V. Boppana and A. Mathur, “Analysis of the Dynamic Source Routing Protocol
for Ad Hoc Networks,” IEEE Workshop on Next Generation Wireless Networks
(WoNGeN), December 2005
Pathan, A.S.K.; Hyung-Woo Lee; Choong Seon Hong, “Security in wireless
sensor networks: issues and challenges” Advanced Communication Technology
(ICACT), Page(s):6, 2006
 Tahir Naeem, Kok-Keong Loo, “Common Security Issues and Challenges in
Wireless Sensor Networks and IEEE 802.11 Wireless Mesh Networks”, International
Journal of Digital Content Technology and its Applications, Page 89-90 Volume 3,
Number 1, 2009
 S. Roy, M. Conti, S. Setia, and S. Jajodia, “Secure data aggregation in wireless
sensor networks,” IEEE Trans. Inf. Forensics Security, vol. 7, no. 3, 2012.
. 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, Vol. 1(2), 2011.
 S. Dulman, J. Wu, P. Havinga, "An energy efficient multipath routing algorithm
for wireless sensor networks", IEEE International Symposium on Autonomous
Decentralized Systems 2003.
 T. Camilo, J. Sá Silva, F. Boavida, “Assessing the use of ad-hoc routing
protocols in Mobile Wireless Sensor Networks” in Proc.of Conference on Mobile and
Ubiquitous Systems, CMUS2006, Braga, June 2006.
 F. Ye, H. Luo, J. Cheng, S. Lu, and L. Zhang, “Dissemination protocols for large
sensor networks. Wireless sensor networks book contents”, in C.S. Raghavendra &
al., Wireless Sensor Networks, Kluwer, ISBN:1-4020-7883-8, 2004
 C. Intanagonwiwat, R. Govindan, D. Estrin, J. Heidemann, and F. Silva.
“Directed Diffusion for Wireless Sensor Networking” ACM/IEEE Transactions on
Networking, Volume 11, Issue 1, February, 2002.
 V. C. Giruka, M. Singhal, J. Royalty, and S. Varanasi, “Security in wireless
sensor networks,” Wireless Communication and Mobile Computing, vol. 8 , no. 1, pp.
1-24, Jan. 2008.
 K. Akkaya and M. Younis, “A survey on routing protocols for wireless sensor
networks,” Ad Hoc Networks, vol. 3, no. 3, pp. 325-349, May 2005.
 H. Cam, S. Ozdemir, D. Muthuavinashiappan and P. Nair, “Energy Efficient
Security Protocol for Wireless Sensor Networks,” Vehicular Technology Conference,
, vol. 5, pp. 2981-2984 ,2003.
 C. Karlof and D. Wagner, “Secure Routing in Wireless Sensor Networks:
Attacks and Countermeasures,” In Proceedings of the 1st IEEE International
Workshop on Sensor Network Protocols and Applications, Anchorage, AK, 2003.
 S.Anbuchelian, Selvamani.K, Chandarasekar.A” An Energy Efficient Multipath
Routing Scheme by Preventing Threats in Wireless Sensor Networks”. Anna
University, Anna University. 2014
 Shobha Poojary, Manohara “Multipath Data Transfer in Wireless Multimedia
Sensor Network” 2010. Pai Information and Communication Technology, Manipal
Institute of Technology.
 Anfeng Liu, Zhongming Zheng, Chao Zhang, Zhigang Chen, Member, IEEE,
and Xuemin (Sherman) Shen, “Secure and Energy-Efficient Disjoint Multipath
Routing for WSNs”. IEEE 2012.
 Alexander Aronsky and Adrian Segall “A Multipath Routing Algorithm for
Mobile Wireless Sensor Networks” Department of Electrical Engineering, Technion
IIT, Haifa, Israel.
 Himali Saxena, Chunyu Ai, Marco Valero, Yingshu Li, and Raheem Beyah
“DSF - A Distributed Security Framework for Heterogeneous Wireless Sensor
Networks” Military Communications Conference Cyber Security and Network
 Huei-Wen Ferng and Dian Rachmarini “A Secure Routing Protocol for Wireless
Sensor Networks with Consideration of Energy Efficiency” IEEE 2012.
 Kashif Saleem Norsheila Fisal, M. Ariff Baharudin “A Real-Time Empirical
Study of BIOSARP based Wireless Sensor Network Test bed” IEEE 2012.
 Leron Lightfoot, Yun Li, Jian Ren “Preserving Source-Location Privacy in
Wireless Sensor Network using STaR Routing” IEEE Globecom 2010.
LIST OF RESEARCH PAPER
 Rajat Soni, Deepak Sethi, P.P. Bhattacharya “Comparison of Various Secure
Routing Protocols in Wireless Sensor Network: Review” National Conference on
Computing and Informatics December 2015 (Communicated).