ABSTRACT
In wireless sensor networks, the adversary may inject false reports to exhaust network
energy or trigger false alarms with compromised sensor nodes. In response to the problems of
existing schemes on the security resiliency, applicability and filtering effectiveness, this Project
proposes a scheme, referred to as Grouping-enhanced Resilient Probabilistic En-route Filtering
(GRPEF). In GRPEF, an efficient distributed algorithm is proposed to group nodes without
incurring extra groups, and a multiaxis division based approach for deriving location-aware keys
is used to overcome the threshold problem and remove the dependence on the sink immobility
and routing protocols. Compared to the existing schemes, GRPEF significantly improves the
effectiveness of the en-route filtering and can be applied to the sensor networks with mobile
sinks while reserving the resiliency.
Existing System
These schemes adopt a general en-route filtering framework to protect data authenticity,
detect and filter out false reports. This framework assumes that an event can be detected by more
than T sensors. To protect the report authenticity, a legitimate report is collaboratively endorsed
with T (T > 1) distinct Message Authentication Codes (MACs) from the nodes detecting the
event simultaneously. To filter the false reports, the nodes in the routing path share the
authentication keys for the report endorsement. As a result, an invalid report that has less than T
MACs or any incorrect MAC can be detected and dropped by the forwarding nodes or the sinks.
There are two ways to share the authentication keys for the report endorsement, that are, routingspecific way and probabilistic way.
In the routing-specific key sharing schemes such as IHA, DEFS, and LEDS, the
authentication keys of sensor nodes are shared with the forwarding nodes in the routing path by
pairwise key establishment or key dissemination. Since the probabilistic key sharing schemes do
not need periodic node association and key dissemination, they are superior to the routingspecific key sharing schemes and are preferred by the resource-constrained WSNs. However, the
existing probabilistic schemes have their shortages.
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Introduction
In many monitoring applications, wireless sensor networks (WSNs) are usually deployed
in a hostile environment, and an adversary can easily capture and compromise sensor nodes due
to their low cost and unattended nature. Once a node is compromised, the adversary can easily
launch false data injection attack by the compromised nodes for forging bogus event reports to
the base station. This attack may not only trigger false alarms but also drain out the limited
resources of the forwarding nodes in the routing paths. Thus, it is critical for WSNs to defend
such attack from two aspects of protecting report authenticity and filtering bogus reports. These
schemes adopt a general en-route filtering framework to protect data authenticity, detect and
filter out false reports. There are two ways to share the authentication keys for the report
endorsement, that are, routing-specific way and probabilistic way. In the routing-specific key
sharing schemes such as IHA , DEFS , and LEDS , the authentication keys of sensor nodes are
shared with the forwarding nodes in the routing path by pairwise key establishment or key
dissemination . IHA and DEFS require periodic maintenance of node association or key
dissemination along the routing paths to the sink, which incur great energy cost because of
frequent routing changes in WSNs. In the probabilistic key sharing schemes such as SEF and
LBRS , the sensor nodes are divided into n(n > T) groups according to the key distribution
before deployment. The nodes in the same group share common authentication keys with a
probability. A legitimate report is endorsed with T MACs each of which is generated by a
detecting node from different group, which is referred to as T-group authentication. Since the
probabilistic key sharing schemes do not need periodic node association and key dissemination,
they are superior to the routing-specific key sharing schemes and are preferred by the resourceconstrained WSNs.
Contact: 040-23344332, 8008491861
Email id: info@projectgenie.in , www.projectgenie.in
Proposed System
In the probabilistic key sharing schemes such as SEF and LBRS , the sensor nodes are
divided into n(n > T) groups according to the key distribution before deployment. The nodes in
the same group share common authentication keys with a probability. A legitimate report is
endorsed with T MACs each of which is generated by a detecting node from different group,
which is referred to as T-group authentication. The extra n _ T groups are introduced to enable
T-group authentication to work for events in as large area as possible. A random key
predistribution approach is adopted in SEF . A global key pool is evenly divided into n partitions.
Each node randomly picks k keys from one partition and the nodes holding keys from the same
partition form a group. In LBRS, each node is preloaded with one of n master secrets, and the
nodes having the same master secret form a group. The authentication keys are derived based on
the locations of cells in the terrain. All the nodes in the routing paths to the sink shares the
authentication keys with a probability.
Comparing with SEF and LBRS, GRPEF has the following advantages.
1. In GRPEF, an efficient distributed algorithm is proposed to divide sensor nodes into
exact T groups. It can guarantee that any location in the monitored area is covered
simultaneously by T nodes from distinct groups with a high probability. The removal of the extra
groups significantly improves the enrooting filtering effectiveness, as shown by our formal
analysis. GRPEF achieves the same coverage percentage of T-group authentication as SEF and
LBRS without requiring more than T groups.
2. To tackle the threshold limitation of SEF, a novel location-aware key derivation technique
based on multiaxis division is proposed without assuming the sink immobility and specific
routing models. As a result, GRPEF achieves the resiliency against node compromise while
being applicable to the networks with mobile sinks and various routing protocols. Our theoretical
analysis shows that GRPEF achieves much higher resiliency than SEF.
Contact: 040-23344332, 8008491861
Email id: info@projectgenie.in , www.projectgenie.in
Module List
 Login
 Sensor node
 Mobile Sink
 Monitoring and Reporting Phase
 False Data Injection
 En-Route Filtering
Module Description
Login
In this module the user can get in to the system by enter the username and password. The user
can register them self in the particular Sensor Node. Therefore we can easily identify a Mobile
Sink, where it is resident.
Sensor Node
In this module, the sensor node requests the mobile sink and then mobile sink response to the
sensor node. Mobile sink provides the Message Authentication Code (MAC) to the sensor node
.Each sensor node use this MAC and then actual data is send to the sensor node-2.Sensor node-2
may inject the false data .Finally send to the mobile sink.
Mobile sink:
The mobile sink receives the data from the all nodes in network which may be false data or
integrity data. After receiving data, it will identify the false inject data by enroute-filtering.
Monitoring and Reporting Phase:
When an event occurs in partition. All detecting nodes are organized into a cluster and
collaboratively generate the event report E with the event location. The message authentication
code of report E generated with a symmetric key. The detecting node in group computes MAC
where k is the endorsement key bound with the partition. Then the detecting node sends a tuple
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to the cluster head CH. When CH collects MAC from distinct groups, it sends
out the report with the endorsement to the sink.
False Data Injection
In this module focus on the false data injection attack, in which the compromised nodes inject
forged event reports to trigger false alarms or to deplete the limited resources of nodes in the
routing paths. Our problem is to design a scheme that can detect and filter false reports such that
false reports is detected and dropped as early as possible, the threshold limitation of the solutions
is overcome, graceful performance degradation is achieved when more and more nodes are
compromised, and the scheme should be independent of routing protocols and applicable to the
WSNs with mobile sinks.
En-route filtering
 Every forwarding node verifies the MAC computed by its lower association node, and
then removes that MAC from the received report.
 If the verification succeeds, it then computes and attaches a new MAC based on its
pairwise key shared with its upper associated node.
 Finally, it forwards the report to the next node towards the BS.
Contact: 040-23344332, 8008491861
Email id: info@projectgenie.in , www.projectgenie.in
System Requirement Specification:
Software Requirements:
Front End/GUI Tool
: Microsoft Visual studio 2008
Operating System
: Windows family
Language
: C#.NET
Technology
: ASP.NET 3.5
Hardware Requirements:
Processor
: Pentium dual core
RAM
: 1 GB
Hard Disk Drive
: 80 GB
Monitor
: 17” Color Monitor
Contact: 040-23344332, 8008491861
Email id: info@projectgenie.in , www.projectgenie.in