![In past different scheme have been proposed for
filtering false data in wireless sensor networks
where the data is transferred in a environment
where the sensor nodes are scattered. For example
inStatisticalEnroute Filtering Scheme[1],Interleaved
Hop-by-Hop Schemes[2] have the limitation of
node compromising where the false data can be
injected in order to generate the false reports.
In the paper we discuss about the
compromise resilient enroute filtering scheme
where the sensor nodes are organized into the form
of clusters. And the data is transferred to Base
station (sink) with the help of forwarding nodes
which act as an intermediate between the cluster
and the base station.
The rest of the paper is organized as follows:
1) a brief survey on existing filtering schemes.
overview of compromise resilient enroute filtering
scheme in cluster based environment in WSN. 2) a
survey on compromised resilient enroute filtering
scheme in WSN.3) Then, a detailed literature
survey on enroute filtering devised for WSNs is
provided along with comments on their prominent
and lacking feature.
II.RELATED WORKS
We discuss about existing filtering schemes,
which make use of MAC(message authentication
Codes) for transferring the data.
a) Statistical Enroute Filtering (SEF)[1] is the
most basic mechanism in which dense deployment
of large sensor networks takes place. To prevent
any single compromised node from breaking down
the entire system, SEF sends only limited of
amount of security information assigned to each
node, and depends on the collective decisions of
multiple sensors for false report detection. As a
report is forwarded through multiple hops toward
the sink, each intermediate node verifies the
correctness of the MACs carried in the report and
drops the report if an incorrect MAC is detected.
The disadvantage of SEF is probability of detecting
incorrect MACs increases with the number of hops
the report travels. SEF[1] and IHA[4] have the T-
threshold limitations. That is, if the adversary
compromises T nodes from different groups, they
could inject false data to generate the false report.
To overcome the threshold limitation and to
reduce the increasing number of compromised
nodes which we have seen in SEF. We come up
with LBRS
b) Location-Based Resilient Security (LBRS)[2]
approach which make use of two techniques:
location-binding keys and location-based key
assignment. In location based resilient scheme the
location of the sensors and sink is stationary by
which it can assign fixed key values for the sensor
in order to provide security. Based on its location, a
node stores one key for each of its local
neighboring cells and a few randomly chosen
remote cells. LBRS provides a solution to this
security problem, but it depends on the stationary of
the sink and the fixed routing model such that it
cannot work with mobile sinks and various routing
protocols. The disadvantage of LBRS is it relies on
special data dissemination protocol to confirm a
bean model.
c) Grouping-Based Resilient Statistical Enroute
Filtering (GRSEF)[4]scheme for filtering false
data. The GRSEF does not depend on sink
stationary. It improves the filtering efficiency by
dividing the sensor nodes into certain number of
groups(e.g.: T-groups) and assigns authentications
to the groups. GRSEF employees a multi-axis
division technique to overcome the threshold
limitation problem that we have seen in SEF[1] and
IHA[4]. In GRSEF, the Redundancy is increased to
achieve the robustness against this attacks but the
disadvantage of GRSEF is it has no resilience to the
selective forwarding attack and report disruption
attack .
All the early proposed scheme have the
disadvantage of T-threshold limitations, this
schemes does not adopt to dynamic topology, takes
long time for a network to become stable, sensor
nodes are scattered in a wireless networks were
there is no security for the transmission of data,
Requires node localization and takes a long time to
be stable. Inorder to overcome the disadvantages
our survey has come up with formation of clusters
in wireless sensor network where the sensor nodes
are grouped to form clusters.
Proceedings of International Conference on Developments in Engineering Research
ISBN NO : 378 - 26 - 13840 - 9
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![e) System model of proposed system:
FS1, FS2 - Forward Sensor Nodes
C1, C2, C3 - Clusters
CH - Cluster Head
S1, S2, S3 - Sensor Nodes
f) Algorithms used in Enroute Filtering:
Type Of Algorithm Algorithm Usage Advantages
1. Kar and Banerjee’s
algorithm
2. Greedy algorithm
Sensor-deployment in a network 1. Achieve Coverage
2. Achieve Connectivity
Distributed algorithm
Compute Support Weight(SW)
between the sensor nodes in a
network.
1. Construct Local Neighborhood Graph.
2. Construct Best Support Path
Veltri et al. algorithm Distributed localized algorithm
1. To find an approximate minimal
exposure path.
2. Linear programming formulation for
minimal- and maximal-exposure paths is
obtained.
Kanan et al. algorithm Polynomial time algorithms
1. compute the maximum vulnerability of a
sensor deployment to attack by intelligent
adversary .
2. To compute optimal deployments with
minimal vulnerability.
Clustering Algorithm 1. LEACH – C Algorithm
2. Efficient Cluster Head Selection
Scheme For Data Aggregation
[EECHSSDA]
3. Hybrid Energy- Efficient
Distributed Clustering
Cluster Head Selection takes place based on
following clustering algorithm.
Greedy base-station
algorithm
1. For unidirectional antennas
2. For omnidirectional antennas
Forwarding of data to the base station
FS1
C2 CH
S2 S3
C1 CH
S1 S2
SINK
FS1
C3 CH
S1 S3
C2 CH
S2 S3
FS2
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Iaetsd a survey on enroute filtering scheme in
- 1. A Survey on Enroute Filtering Scheme in Wireless Sensor Networks P.Pritto Paul, K.Thejaswi, Asst Professor, Velammal Engg. College, PG-Student, Velammal Engg. College, Anna University, Chennai. Anna University, Chennai. [email protected] [email protected] Abstract— Wireless Sensor Networking is one of the most prominent technology that is used in almost all real time applications. WSN is used in the estimation of temperature in Cyber Physical Network System(CPNS) where the sensor nodes are deployed in hostile environment. In this environment the sensor nodes sense the data and forward the report to the base station. When the report is being forwarded to the base station the attacker may forge the data or may inject false data into the report by compromising the sensor nodes in the network this leads the base station to generate false decision. The solution to overcome the False Data Injection Attack is to implement the Enroute Filtering Scheme in WSN. The Enroute Filtering is used to check the correctness of the data before it is being forwarded to the base station. In this paper some of the most efficient Enroute Filtering Schemes for filtering false data have been discussed with their advantages and disadvantages. And also forwarding and filtering of data in Cluster based environment which provides high security than other filtering schemes have been discussed. I. Introduction WIRELESS sensor networks are expected to interact with the physical world at an unprecedented level to enable various new applications. However, a large-scale sensor network may be deployed in a potentially adverse or even hostile environment and potential threats can range from accidental node failures to intentional tampering. Due to their relatively small sizes and unattended operations, sensor nodes have a high risk of being captured and compromised. False sensing reports can be injected through compromised nodes, which can lead to not only false alarms but also the depletion of limited energy resource in a battery powered network. The false data injection in a cyber physical network system can be overcome by the formation of clusters where the neighbor sensor node with nearly similar properties will be organized into the form of clusters. In the hierarchical network structure each cluster has a leader, which is also called the cluster head (CH). The sensor nodes periodically transmit their data to the CH nodes.CH nodes aggregate the data and transmit them to the base station (BS) either directly or through the intermediate communication with other CH nodes. The BS is the data processing unit for the data received from the sensor nodes.The Base Station is fixed at a place in a stationary manner which is far away from the all the sensor nodes .The function of each CH,is to perform common functions for all the nodes in the cluster, like aggregating the data before sending it to the BS. In some way, the CH is the sink for the cluster nodes, and the BS is the sink for the CHs. The advantages of cluster based environment is: 1) supporting network scalability and decreasing energy consumption through data aggregation 2) It can localize the route setup within the cluster and thus reduce the size of the routing table stored at the individual node. . The main parameters included in clustering are: Number of clusters, Nodes and CH mobility, Nodes types and roles, Cluster formation methodology, Cluster-head selection. Proceedings of International Conference on Developments in Engineering Research ISBN NO : 378 - 26 - 13840 - 9 www.iaetsd.in INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT 7
- 2. In past different scheme have been proposed for filtering false data in wireless sensor networks where the data is transferred in a environment where the sensor nodes are scattered. For example inStatisticalEnroute Filtering Scheme[1],Interleaved Hop-by-Hop Schemes[2] have the limitation of node compromising where the false data can be injected in order to generate the false reports. In the paper we discuss about the compromise resilient enroute filtering scheme where the sensor nodes are organized into the form of clusters. And the data is transferred to Base station (sink) with the help of forwarding nodes which act as an intermediate between the cluster and the base station. The rest of the paper is organized as follows: 1) a brief survey on existing filtering schemes. overview of compromise resilient enroute filtering scheme in cluster based environment in WSN. 2) a survey on compromised resilient enroute filtering scheme in WSN.3) Then, a detailed literature survey on enroute filtering devised for WSNs is provided along with comments on their prominent and lacking feature. II.RELATED WORKS We discuss about existing filtering schemes, which make use of MAC(message authentication Codes) for transferring the data. a) Statistical Enroute Filtering (SEF)[1] is the most basic mechanism in which dense deployment of large sensor networks takes place. To prevent any single compromised node from breaking down the entire system, SEF sends only limited of amount of security information assigned to each node, and depends on the collective decisions of multiple sensors for false report detection. As a report is forwarded through multiple hops toward the sink, each intermediate node verifies the correctness of the MACs carried in the report and drops the report if an incorrect MAC is detected. The disadvantage of SEF is probability of detecting incorrect MACs increases with the number of hops the report travels. SEF[1] and IHA[4] have the T- threshold limitations. That is, if the adversary compromises T nodes from different groups, they could inject false data to generate the false report. To overcome the threshold limitation and to reduce the increasing number of compromised nodes which we have seen in SEF. We come up with LBRS b) Location-Based Resilient Security (LBRS)[2] approach which make use of two techniques: location-binding keys and location-based key assignment. In location based resilient scheme the location of the sensors and sink is stationary by which it can assign fixed key values for the sensor in order to provide security. Based on its location, a node stores one key for each of its local neighboring cells and a few randomly chosen remote cells. LBRS provides a solution to this security problem, but it depends on the stationary of the sink and the fixed routing model such that it cannot work with mobile sinks and various routing protocols. The disadvantage of LBRS is it relies on special data dissemination protocol to confirm a bean model. c) Grouping-Based Resilient Statistical Enroute Filtering (GRSEF)[4]scheme for filtering false data. The GRSEF does not depend on sink stationary. It improves the filtering efficiency by dividing the sensor nodes into certain number of groups(e.g.: T-groups) and assigns authentications to the groups. GRSEF employees a multi-axis division technique to overcome the threshold limitation problem that we have seen in SEF[1] and IHA[4]. In GRSEF, the Redundancy is increased to achieve the robustness against this attacks but the disadvantage of GRSEF is it has no resilience to the selective forwarding attack and report disruption attack . All the early proposed scheme have the disadvantage of T-threshold limitations, this schemes does not adopt to dynamic topology, takes long time for a network to become stable, sensor nodes are scattered in a wireless networks were there is no security for the transmission of data, Requires node localization and takes a long time to be stable. Inorder to overcome the disadvantages our survey has come up with formation of clusters in wireless sensor network where the sensor nodes are grouped to form clusters. Proceedings of International Conference on Developments in Engineering Research ISBN NO : 378 - 26 - 13840 - 9 www.iaetsd.in INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT 8
- 3. III. Preliminary a) The Basics of Enroute Filtering: The enroute filtering is technique used in wireless networks with which the intermediate nodes checks the correctness of the data that is being travelled along the route from source to the sink with the help of intermediate nodes present in the network. The intermediate node not only checks the correctness of the data but also can filter the false data effectively. The intermediate nodes after receiving the report checks whether it contain valid T-MAC. The report with less number of T-MAC will be dropped. If any false data which is not filtered by the intermediate nodes will be detected by the sink where it gets filtered. The sink acts as the final defense that catches false reports not filtered out by forwarding nodes. b) System model of Enroute Filtering: c) Security Model Of Enroute Filtering: We consider a large sensor network field where nodes are deployed. So after the network initialization phase the sensor nodes forms into groups and elect a cluster head based on different parameters like remaining energy etc. Whenever events of interest occurs in the terrain say if a tank moves, all the cluster members near to the event will sense the happening and report to their cluster heads. On receiving the reports cluster head aggregates them and sends a single copy of the valid report to the base station through selected report forwarding nodes. The selections of report forwarding nodes are up to the underlying routing protocol’s work . And also the selection parameters are independent of the application. We assume that there are attackers present within the terrain are capable of monitoring the communication pattern between the sensor members and the cluster head to guess the message from the reports if intercepted. We assume that each cluster contains at most t-1 compromised nodes, which may collaborate with each other to generate false reports by sharing their secret key information. The potential attacks which we consider in our work DoS attacks. DoS attacks include selective forwarding and report disrupt d) Proposed System for Enroute Filtering: The proposed system for enroute filtering is based on cluster environment where the sensor nodes are organized into groups(clusters).In cluster based sensor nodes makes use of two keys authentication key and check key instead of MAC used in the existing systems. The sensor nodes within the cluster are assigned with authentication key and the forward nodes are assigned with check key in order to provide additional security. The security keys for the sensing node and the forwarding node is assigned by the sink. Different nodes present in different clusters are assigned with different authentication keys. In this way a compromised node present in one cluster will not effect the nodes present in the other cluster. Therefore this scheme achieves better resilience to the increased number of compromised nodes. The main advantage of this scheme is that it does not depend on static routes and node localization. This scheme mainly consists of two principles: Management of authentication information: this is used to assign the key values to the nodes present in the network. Management of data security: this is used to detect and filter the false data. The report that is being forwarded from one cluster should contain: the encrypted measurement, cluster key, sensor node ID, local ID of the node from where it has been generated, authentication information of the measurement generated by the node. Sensor node sink Compromised node(injection of false data) Intermediate node should check for correct MAC Proceedings of International Conference on Developments in Engineering Research ISBN NO : 378 - 26 - 13840 - 9 www.iaetsd.in INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT 9
- 4. e) System model of proposed system: FS1, FS2 - Forward Sensor Nodes C1, C2, C3 - Clusters CH - Cluster Head S1, S2, S3 - Sensor Nodes f) Algorithms used in Enroute Filtering: Type Of Algorithm Algorithm Usage Advantages 1. Kar and Banerjee’s algorithm 2. Greedy algorithm Sensor-deployment in a network 1. Achieve Coverage 2. Achieve Connectivity Distributed algorithm Compute Support Weight(SW) between the sensor nodes in a network. 1. Construct Local Neighborhood Graph. 2. Construct Best Support Path Veltri et al. algorithm Distributed localized algorithm 1. To find an approximate minimal exposure path. 2. Linear programming formulation for minimal- and maximal-exposure paths is obtained. Kanan et al. algorithm Polynomial time algorithms 1. compute the maximum vulnerability of a sensor deployment to attack by intelligent adversary . 2. To compute optimal deployments with minimal vulnerability. Clustering Algorithm 1. LEACH – C Algorithm 2. Efficient Cluster Head Selection Scheme For Data Aggregation [EECHSSDA] 3. Hybrid Energy- Efficient Distributed Clustering Cluster Head Selection takes place based on following clustering algorithm. Greedy base-station algorithm 1. For unidirectional antennas 2. For omnidirectional antennas Forwarding of data to the base station FS1 C2 CH S2 S3 C1 CH S1 S2 SINK FS1 C3 CH S1 S3 C2 CH S2 S3 FS2 Proceedings of International Conference on Developments in Engineering Research ISBN NO : 378 - 26 - 13840 - 9 www.iaetsd.in INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT 10
- 5. IV. Literature Survey V. Conclusion The clustering scheme achieves not only high en-routing filtering probability but also high reliability for filtering the injected false data with multi-reports without depending on static routes and node localization. Due to the simplicity and effectiveness, the cluster based scheme could be applied to other fast and distributed authentication scenarios in wireless network. VI. References 1) F. Ye, H. Luo, S. Lu, and L. Zhang, “Statistical en-route filtering of injection false data in sensor networks,” IEEE Journal on 3) L. Yu and J. Li, “Grouping-based resilient statistical en-route filtering for sensor networks,” in Proc. of the 28th IEEE International Conference on Computer Communications (INFOCOM’09), 2009, pp. 1782–1790. 4) S. Zhu, S. Setia, S. Jajodia, and P. Ning, “An interleaved hop-byhop authentication scheme for filtering of injection false data in sensor networks,” ACM Transactions on Sensor Networks (TOSN), vol. 3, no data in sensor networks,” IEEE Journal on selected areas in communication,VOL.23, NO. 4, April 2005 2)” Toward Resilient Security in Wireless Sensor Networks” Hao Yang, Fan Ye, Yuan Yuan, Songwu Lu, William Arbaugh 5) N.Parashuram, Y.Sanjay sai raj, A.Sagar, B.Uma “An Active En-route Filtering Scheme for Secured Data Dissemination in Wireless Sensor Networks” IJCSET |April 2012| Vol 2, Issue 4,1102-1 Schemes for filtering false data Advantages Disadvantages Statistical Enroute Filtering Dynamic topology shared key mechanism Threshold problems No resilience to attacks. Location-Based Resilient Security Avoid threshold limitations Location-basedkey generation Not applied to dynamic topology Require node localization Grouping-Based Resilient Statistical Uses multi-axis division technique Avoid threshold limitations Require node localization Lower resilience to attacks. Proceedings of International Conference on Developments in Engineering Research ISBN NO : 378 - 26 - 13840 - 9 www.iaetsd.in INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT 11
- 6. 6) “Clustering in Wireless Sensor Networks” textbook Basilis Mamalis, Damianos Gavalas, Charalampos Konstantopoulos, and Grammati Pantziou. 7)“Algorithms For Wireless Sensor Networks” Sartaj Sahni and Xiaochun Xu Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611 {sahni,xxu}@cise.ufl.edu September 7, 2004 8)” A Random Perturbation-Based Scheme for Pairwise Key Establishment in Sensor Networks” Wensheng Zhang and Minh Tran Dept. of Computer Science, Iowa State University, Ames, IA 50014, USA 9) “Filtering Schemes for Injected False Data in Wsn” IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 13, Issue 6 (Jul. - Aug. 2013), PP 29-31. Proceedings of International Conference on Developments in Engineering Research ISBN NO : 378 - 26 - 13840 - 9 www.iaetsd.in INTERNATIONAL ASSOCIATION OF ENGINEERING & TECHNOLOGY FOR SKILL DEVELOPMENT 12