AN ADVANCED DATA SECURITY METHOD IN WSN

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International Journal of Advanced Research in Engineering and Technology (IJARET)
Volume 10, Issue 2, March-April 2019, pp. 263-270. Article ID: IJARET_10_02_026
Available online at http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=10&IType=02
ISSN Print: 0976-6480 and ISSN Online: 0976-6499
© IAEME Publication
AN ADVANCED DATA SECURITY METHOD IN
WSN
Syeda Kausar Fatima,
Research Scholar Jntuh, Prof., Dcet, Hyderabad, Principal Nsakcet,
Prof., Ece Dept. Jntuh, India.
Dr. Syeda Gauhar Fatima,
Dr. Syed Abdul Sattar
Dr. Anita Sheela
ABSTRACT
Recently, WSNs have drawn a lot of attention due to their broad applications in both
military and civilian domains. Data security is essential for success of WSN
applications, exclusively for those mission-critical applications working in unattended
and even hostile environments which may be exposed to several attacks. This inspired
the research on Data security for WSNs. Attacks due to node compromise include Denial
of service (DoS) attacks such as selective forwarding attacks and report disruption
attacks. Nearby many techniques have been proposed in the literature for data security.
Hop-hop security works well when assuming a uniform wireless communication pattern
and this security designs provides only hop-hop security. Node to sink communication
is the dominant communication pattern in WSNs and hop-hop security design is not
sufficient as it is exposed to several attacks due to node compromise. Location aware
end-end data security (LEDS) provides end-end security.
Keywords-Data security, end-to-end, DoS attack, wireless sensor network
Cite this Article: Syeda Kausar Fatima, Dr. Syeda Gauhar Fatima Dr. Syed Abdul
Sattar, And Dr. Anita Sheela, An Advanced Data Security Method in Wsn, International
Journal of Advanced Research in Engineering and Technology, 10(2), 2019, pp. 263-
270.
http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=10&IType=2

An Advanced Data Security Method in Wsn
1. INTRODUCTION
A wireless sensor network (WSN) is a wireless network comprising of a large number of
spatially distributed sensor nodes. These sensor nodes can be easily established at planned
regions at a low cost. Provided with various types of sensors, sensor nodes cooperate with each
other to monitor physical or environmental conditions, such as temperature, vibration, sound,
image, pressure, motion or pollutants. Each sensor node is equipped with a radio transceiver or
other wireless communication device, a microprocessor, and an energy source (e.g., a battery).
However, providing satisfactory security protection in WSNs has ever been a challenging task
due to various network & resource constraints and malicious attacks.
The sensor nodes and the base stations are the major elements of WSN. These both can be
abstracted as the ‘sensing cells’ and the ‘brain’ of the network, respectively. Security
compromise of sensor nodes is one of the most severe security threats in WSNs due to their
lack of tamper resistance [1]. In WSNs, the attacker could compromise multiple nodes to obtain
their carried keying material and control them and thus is able to intercept data transmitted
through these nodes thereafter. As the number of compromised nodes grows, communication
links between uncompromised nodes might also be compromised through malicious
cryptanalysis. Thus, this type of attack could lead to severe data confidentiality compromise in
WSNs. Furthermore, the attacker may use compromised nodes to inject bogus data traffic in
WSNs.
2. WIRELESS SENSOR NETWORK
Wireless sensor networks composed of a large number of sensor nodes. Sensor nodes are
typically small, low cost, low power devices. Sensor nodes perform the functionality such as
sense/monitor its local environment, perform limited data processing, and communicate on
short distance. A WSN usually also contains a “sink” node(s) which collects data from sensor
nodes and connects the WSN to the outside world. Wireless sensor networks (WSNs) are
rapidly growing in their importance and relevance to both the research community and the
public at large. A distributed wireless sensor network is formed by a large number of tiny and
inexpensive sensor nodes. These nodes are typically resource constrained, with limited energy
lifetime, low-power micro sensors and actuators, slow embedded processors, limited memory,
and low bandwidth radios.
Figure 1 Sensor network architecture.
The following unique features of WSNs make it particularly challenging to protect
communication security in WSNs.
A. Resource Constraints
Small sensors only have limited communication and computation capabilities, which makes it
difficult to implement expensive security operations for WSNs. This precludes the direct
transplantation of the existing security designs aimed for traditional wireless networks, where

Syeda Kausar Fatima, Dr. Syeda Gauhar Fatima Dr. Syed Abdul Sattar and Dr. Anita Sheela
network nodes are much more powerful devices. Sensor nodes are battery-powered, having
only limited energy supply. This again requires the security design to be efficient regarding
both communication and computation overheads. In most cases, sensors only have very limited
memory spaces, which further narrows down the security design choices. All these resource
constraints require that the security design can only be efficient and lightweight; otherwise it
will not be practical for WSNs.
B. Network Constraints
WSNs use wireless open channel, therefore an adversary can easily eavesdrop all the network
communications, as well as arbitrarily injecting messages and launching jamming attacks at
different network layers. This means that the security design has to take into account both
passive and active attacks. WSNs are distributed in nature, therefore centralized security
solutions cannot be an option for WSNs. This also means that WSNs are vulnerable to various
DoS attacks. WSNs are often very large in scale, which in turn imposes scalability requirement
on the security design.
C. Malicious Attacks
Give the large scale of the WSNs, it is impractical to protect or monitor each individual sensor
node physically. In addition, sensors are also not tampering resistant. Therefore, the adversary
may capture and compromise a certain number of sensor nodes without being noticed and
obtain all the secrets stored on these sensors. The adversary is thus able to launch a variety of
malicious insider attacks against the network through these compromised nodes in addition to
outsider attacks. For example, the compromised nodes may report bogus observations in order
to mislead the network owner or users; they may also discard important messages such as data
reports in order to hide some critical events from being noticed. All these attacks could cause
severe results that may disable network functionality at least temporarily. Hence, it is highly
important for the security design to be robust against sensor compromise and against both
outsider and insider attacks.
Despite the importance, providing satisfactory security protection in WSNs has never been
an easy task. This is because sensor networks not only suffer from various malicious attacks;
but also, are subject to many resource and network constraints as compared to traditional
wireless networks. This motivates the research data security for WSNs.
3. DATA SECURITY
One of the most severe security threats in WSNs is security compromise of sensor nodes due
to their lack of tamper resistance. In WSNs, the attacker could compromise multiple nodes to
obtain their carried keying materials and control them, and thus is able to intercept data
transmitted through these nodes thereafter. As the number of compromised nodes grows,
communication links between uncompromised nodes might also be compromised through
malicious cryptanalysis. Hence, this type of attacks could lead to severe data confidentiality
compromise in WSNs. Furthermore, the attacker may use compromised nodes to inject bogus
data traffic in WSNs. In such attacks, compromised nodes pretend to have detected an event of
interest within their vicinity, or simply fabricate a bogus event report claiming a non-existing
event at an arbitrary location. Such insider attacks can severely damage network function and
result in the failure of mission-critical applications. Such attacks also induce network
congestion and wireless contention and waste the scarce network resources such as energy and
bandwidth, hence, severely affecting both data authenticity and availability. Lastly, the attacker
could also use compromised nodes to launch selective forwarding attack, in which case
compromised nodes selectively drop the going-through data traffic and thus data availability

can be severely damaged. The existence of aforementioned attacks, together with the inherent
constraints of sensor nodes, makes it rather challenging to provide satisfying data security in
WSNs with respect to all its three aspects, i.e., confidentiality, authenticity and availability.
Recent research has seen a growing body of work on security designs for WSNs [2], [3], [4],
[6], [7], [8], [10]. Due to the resource constraint, most of the proposals are based on
symmetric cryptography and only provide data authenticity and/or confidentiality in a hop-by-
hop manner. End-to-end encryption/ authentication is considered less feasible, particular in a
WSN consisting of a large number of nodes. However, lack of the end-to-end security
guarantee could make WSNs particularly vulnerable to the aforementioned attacks in many
applications, where nodeto-sink communication is the dominant communication pattern. This
could give the attacker the advantage to obtain/manipulate its desired data at a much less
effort without having to compromise a large number of nodes. To make things worse, existing
security designs are highly vulnerable to many types of DoS attacks, such as report disruption
attacks and selective forwarding attacks.
Figure 2 Node injects false report in various locations and that false report cause false alarms. In
delivering false reports energy and bandwidth could be wasted. The user may also miss a real event.
A. Data Security Requirements In WSN
Data should be accessible only to authorized entities (usually the sink in WSNs). It should be
genuine and should be always available upon request to the authorized entities. More specially,
the below three requirements can be further elaborated in WSNs as follows:
Data Confidentiality
Confidentiality is required in sensors environment to protect information traveling among the
sensor nodes of the network or between the sensors and the base station from disclosure.
Confidentiality is an assurance of authorized access to information. In the context of
networking, confidentiality means that the information about communications should be kept
in secret from anyone without authorized access permission. In WSNs, data of interest, which
may vary depending on different applications and usually appears as event reports sent by the
sensing nodes from event happening area via multichip paths to the sink.
Data Authenticity
Authenticity is an assurance of the identities of communicating nodes. Every node needs to
know that a received packet comes from a real sender. Otherwise, the receiving node can be
cheated into performing some wrong actions. Authentication in sensor networks is essential for
each sensor node and base station to have the ability to verify that the data received was really
sent by trusted sender or not. Data reports collected by WSNs are usually sensitive and even
critical, such as in military applications. Hence, it is important to assure data authenticity in
addition to confidentiality.

Data Availability
Availability is an assurance of the ability to provide expected services as they are designed in
advance. It is a very comprehensive concept in the sense that it is related to almost every aspect
of a network. Any problem in a network can result in the degradation of the network
functionality and thus compromise the network availability, leading to the DoS. As
compromised nodes are assumed to be existing in WSNs, it is important to prevent or be tolerant
to their interference as much as possible to protect data availability.
B. Security Threats In WSN
•In WSNs, the attacker could compromise multiple nodes to obtain their carried keying
materials and control them. This type of attack could lead to severe data confidentiality
compromise in WSNs.
•The attacker may use compromised nodes to inject bogus data traffic in WSNs. This type
of attack could lead to severe both data authenticity and availability.
•Lastly, the attacker could also use compromised nodes to launch a selective forwarding
attack, in which case compromised nodes selectively drop the going-through data traffic and,
thus, data availability can be severely damaged.
4. RELATED WORK
Wireless sensor network is used in a wide range of environments. They are vulnerable to more
attacks than the conventional networks, due to the various inherent characteristics of wireless
communication. Most critical is to achieve authentication and data confidentiality. Some of the
papers reviewed to get an idea of the different systems existing in WSN are as follows:
An interleaved hop-by-hop authentication scheme for filtering of injected false
data in sensor networks, 2004
S. Zhu, S. Setia, S. Jajodia, and P. Ning [3] proposed a scheme called interleaved hop-by-
hop authentication (IHA) and is one of the first works in data authentication for wireless sensor
networks. In this scheme, the sensor nodes are organized into clusters. The collaboration of a
minimum number of nodes inside a cluster is generated a appropriate report. Every cluster has
a representative that is called the cluster head (CH). The CH is responsible for collecting enough
number of message authentication code (MAC) values generated by the collaborating nodes,
generating a report, and forwarding it to the sink. The forwarding path from every node to the
sink is discovered at the initialization phase. The authenticity of the report is verified at every
hop of the forwarding path to the sink by the aid of the MAC values. For this purpose,
authentication chains are discovered, and authentication keys are established both at the
initialization phase of the network operation. A report with even one unverified MAC is
regarded as bogus and dropped enroute. Therefore, a malicious node injecting noise to the
network always causes these messages to be dropped. The other drawback of IHA is the
association maintenance that introduces high communication overhead.
Statistical en-route filtering of injected false data in sensor networks, 2005
F. Ye, H. Luo, S. Lu, and L. Zhang [4] have proposed a Statistical En-route Filtering (SEF)
mechanism that is very similar to IHA. The main difference is that associated nodes are not
manually determined at the initialization phase. In contrast to IHA, the associated nodes are
discovered by a probabilistic approach. In SEF, every node is pre-distributed with the keying
material that are used to establish the authentication keys after the network deployment. The
key pre-distribution parameters are selected to guarantee, with a high probability, that any CH
is able to establish many authentication keys. The SEF provides data availability similar to

IHA. Because of the probabilistic nature of SEF, every node is required to store many keys to
guarantee the existence of a minimum number of authentication keys. Therefore, two other
drawbacks of SEF are the requirement forlarge storage memory and the possibility of
revealing many authentication keys by compromising only a few nodes.
Toward resilient security in wireless sensor networks, 2005
H. Yang, F. Ye, Y. Yuan, S. Lu, and W. Arbaugh[6] employed to achieve graceful
performance degradation to an increasing number of compromised keys, the locationbinding
keys and location-based key assignment than both previous schemes (IHA and SEF) have a
threshold property, i.e., an adversary has to compromise a minimum number of authentication
keys to forge a report. The proposed scheme, called location-based resilient security (LBRS),
is conceptually very similar to the SEF. However, the data is forwarded toward the sink in a
hop-by-hop fashion. Thus, LBRS localizes the adversarial activities to only the area of the
network which is under attack. The LBRS inherits the disadvantages of the SEF except the
performance degradation behavior.
Existing security designs provide a hop-by-hop security paradigm only, which leaves the
end-to-end data security at high stake. Data confidentiality and authenticity is highly vulnerable
to insider attacks, and the multihop transmission of messages aggravates the situation.
Moreover, data availability is not sufficiently addressed in existing security designs, many of
which are highly vulnerable to many types of Denial of Service (DoS) attacks.
5. END-TO END VERSUS HOP-BY-HOP DESIGN
Recent research has seen a growing body of work on security designs for WSNs [3], [4], [6],
[8], [9]. Due to the resource constraint, most of the proposals are based on symmetric
cryptography and only provide data authenticity and/or confidentiality in a hop-by-hop manner.
End-to-end encryption/ authentication is considered less feasible, particularly in a WSN
consisting of a large number of nodes. However, lack of the end-to-end security guarantee could
make WSNs particularly vulnerable to the aforementioned attacks in many applications where
node-to-sink communication is the dominant communication pattern. This could give the
attacker the advantage to obtain/ manipulate its desired data using much less effort without
having to compromise a large number of nodes. To make things worse, existing security designs
are highly vulnerable to many types of Denial of Service (DoS) attacks such as report disruption
attacks and selective forwarding attacks.
In the past few years, many secret key predistribution schemes have been proposed [2], [8],
[9], [10]. By leveraging preloaded keying materials on each sensor node, these schemes Two
types of node compromise are considered: random node capture and selective node capture,
according to key distribution. Hop-by-hop security design works fine when assuming a uniform
wireless communication pattern in WSNs. However, in many applications’ node-to-sink
communication is the dominant communication pattern in WSNs, that is, data of interest are
usually generated from the event happening area and transmitted all the way to the sink. In this
case, hop-by-hop security design is not sufficient any more as it is vulnerable to communication
pattern-oriented node capture attacks. Data confidentiality can be easily compromised due to
lack of end-to-end security guarantee, since compromising any intermediate node will lead to
exposure of the transmitted data. At the meantime, as the attacker could decrypt the intercepted
data, it could therefore, freely manipulate them to deceive the sink and hence, severely affects
data availability. The lack of end-to-end security association also makes it hard, if not
impossible at all, to enforce data authenticity. We therefore conclude that end-to-end security
design is much more desirable for WSNs as compared to hop-by-hop design when node-to-sink

communication is the dominant communication pattern as it can offer a much higher security
resilience.
6. PROBLEM STATEMENT
A. System Model Wireless sensor nodes may be deployed into some target field to detect the
events occurring within the field. For example, in a military application, they may be deployed
to a battlefield to detect the activities of enemy forces. We assume that sensor nodes form a
number of clusters after deployment, each containing at least n nodes. In each cluster, one node
is randomly selected as the cluster head. To balance energy consumption, all nodes within a
cluster take turns to serve as the cluster-head. That means physically there is no difference
between a cluster-head and a normal node because the cluster-head performs the same sensing
job as the normal node.
Fig.3.illustrates the organization of sensing nodes in wireless sensor networks. In the figure CH
and BS denote Cluster-Head and Base Station respectively. u1~u5 are forwarding are
forwarding nodes, and v1~v8 are sensing nodes (they can also serve as the forwarding nodes
for other clusters). The black dots represent the compromised nodes, which are located either
in the clusters or en-route.
Figure 3 Sensor nodes are organized into clusters. The big dashed circles outline the regions of
clusters.
7. SIMULATION AND RESULTS
Figure 4 Randomly distributed nodes.

Figure 5 The network lifetime
REFERENCES
[1] H. Chan and A. Perrig, “Security and Privacy in Sensor Networks,” Computer, pp. 103-105,
Oct. 2003.
[2] H. Chan, A. Perrig, and D. Song, “Random Key Predistribution Schemes for Sensor
Networks,” Proc.IEEE Symposium Research inSecurity and Privacy”,May 2003.
[3] S. Zhu, S.Setia, S. Jajodia, and P. Ning, “An Interleaved Hop-By-Hop Authentication
Scheme for Filteringof Injected False Data in Sensor Networks”.Proc. IEEE Symp. Security
and Privacy, May 2004.
[4] F. Ye, H. Luo, S. Lu, and L. Zhang, “Stastical En-Route
[5] Filtering of Injected False Data in Sensor Networks,” In IEEE INFOCOM’04, Hong Kong,
China, Mar. 2004.
[6] A. Wood and J. Stankovic, “Denial of service in sensor networks”, IEEE Computer
Magazine, vol. 35, no. 10, Oct. 2002
[7] H. Yang, F. Ye, Y. Yuan, S. Lu, and W. Arbaugh, “Toward Resilient Security in Wireless
Sensor Networks,” in Proc. ACM Int. Symp. Mobile Ad Hoc Net. Comput-MobiHoc, 2005.
[8] W. Du, J. Deng, Y. Han, and P. Varshney, “A Pairwise Key Predistribution Scheme for
Wireless Sensor Networks,” ACM Trans. Information and System
[9] Security, vol. 8, no. 2, pp. 228-258, May 2005.
[10] W. Du, J. Deng, Y. Han, S. Chen, and P. Varshney, “A Key Management Scheme for
Wireless SensorNetworks
[11] Using Deployment Knowledge,” IEEE Trans.Dependable and Secure computing, vol. 3,
no. 2, pp. 62-77, Jan-Mar. 2006.
[12] S. Zhu, S. Xu, S. Setia, and S. Jajodia, “Establishing Pair-Wise Keys for Secure
Communication in Ad
[13] HocNetworks: A Probabilistic Approach,” Proc. IEEE Int’l Conf.Network Protocols
(ICNP’03), Nov. 2003.
[14] L. Eschenauer and V. Gligor, “A Key-Management Scheme for Distributed Sensor
Networks”, In ACM CCS, Washington, DC, Nov. 2002.

AN ADVANCED DATA SECURITY METHOD IN WSN

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