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PRIVACY- AND INTEGRITY-PRESERVING RANGE QUERIES IN SENSOR NETWORKS

Platform : java

IEEE Projects Years : 2012 - 13

PRIVACY- AND INTEGRITY-PRESERVING RANGE QUERIES

IN SENSOR NETWORKS

ABSTRACT:

The architecture of two-tiered sensor networks, where storage nodes serve as an intermediate tier between sensors and a sink for storing data and processing queries, has been widely adopted because of the benefits of power and storage saving for sensors as well as the efficiency of query processing. However, the importance of storage nodes also makes them attractive to attackers. In this paper, we propose SafeQ, a protocol that prevents attackers from gaining information from both sensor collected data and sink issued queries. SafeQ also allows a sink to detect compromised storage nodes when they misbehave. To preserve privacy, SafeQ uses a novel technique to encode both data and queries such that a storage node can correctly process encoded queries over encoded data without knowing their values. To preserve integrity, we propose two schemes—one using Merkle hash trees and another using a new data structure called neighborhood chains—to generate integrity verification information so that a sink can use this information to verify whether the result of a query  contains exactly the data items that satisfy the query. To improve performance, we propose an optimization technique using Bloom filters to reduce the   communication cost between sensors and storage nodes.

EXISTING SYSTEM

                 Existing Wireless sensor networks once sensor nodes have been deployed, there will be minimal manual intervention and monitoring. But, when nodes are deployed in a hostile environment and there is no manual monitoring.

PROPOSED SYSTEM

The proposed a scheme to preserve the privacy and integrity of range queries in sensor networks .This scheme uses the bucket-partitioning for database privacy. The basic idea is to divide the domain of data values into multiple buckets, the size of which is computed based on the distribution of data values and the location of sensors. In each time-slot, a sensor collects data items from the environment, places them into buckets, encrypts them together in each bucket, and then sends each encrypted bucket along with its bucket ID to a nearby storage node.

 

For each bucket that has no data items, the sensor sends an encoding number, which can be used by the sink to verify that the bucket is empty, to a nearby storage node. When the sink wants to perform a range query, it finds the smallest set of bucket IDs that contains the range in the query, and then sends the set as the query to storage nodes. Upon receiving the bucket IDs, the storage node returns the corresponding encrypted data in all those buckets. SafeQ also allows a sink to detect compromised storage nodes when they misbehave. The sink is the point of contact for users of the sensor network. Each time the sink receives a question from a user, it first translates the question into multiple queries and then disseminates the queries to the corresponding storage nodes, which process the queries based on their data and return the query results to the sink.

SYSTEM CONFIGURATION:-

H/W SYSTEM CONFIGURATION:-

      Processor               -    Dual Core

Speed                                -    2.1 Ghz

RAM                                 -    2GB

Hard Disk                          -   20 GB

Key Board                         -    Standard Windows Keyboard

Mouse                                -    Two or Three Button Mouse

Monitor                              -    SVGA

 S/W SYSTEM CONFIGURATION:-

Operating System            :           Windows XP

Front End                          :           JAVA, RMI, SWING

MODULE DESCRIPTION:

SAFEQ:

SafeQ is a protocol that prevents attackers from gaining information from both sensor collected data and sink issued queries. SafeQ also allows a sink to detect compromised storage nodes when they misbehave. To preserve privacy, SafeQ uses a novel technique to encode both data and queries such that a storage node can correctly process encoded queries over encoded data without knowing their values.

 

INTEGRITY:

The sink needs to detect whether a query result from a storage node includes forged data items or does not include all the data that satisfy the query. There are two key challenges in solving the privacy and integrity-preserving range query problem. First, a storage node needs to correctly process encoded queries over encoded data without knowing their actual values. Second, a sink needs to verify that the result of a query contains all the data items that satisfy the query and does not contain any forged data.

      

PRIVACY:

 

To preserve privacy, SafeQ uses a novel technique to encode both data and queries such that a storage node can correctly process encoded queries over encoded data without knowing their actual values.

 

RANGE QUERIES:

 

The queries from the sink are range queries. A range query “finding all the data items collected at time-slot in the range” is denoted as . Note that the queries in most sensor network applications can be easily modeled as range queries.

 

SINK:

 

The sink is the point of contact for users of the sensor network. Each time the sink receives a question from a user, it first translates the question into multiple queries and then disseminates the queries to the corresponding storage nodes, which process the queries based on their data and return the query results to the sink. The sink unifies the query results from multiple storage nodes into the final answer and sends it back to the user. sink can detect compromised storage nodes when they misbehave.

 

 

 

STORAGE NODE:

Storage nodes are powerful wireless devices that are equipped with much more storage capacity and computing power than sensors. The storage node collects all data from the sensor nodes. The storage node can’t view the actual value of sensor node data. If the storage node trying to view the sensor node data, sink detect misbehave of storage node.

CONCLUSION

We make three key contributions in this paper. First, we propose SafeQ, a novel and efficient protocol for handling range queries in two-tiered sensor networks in a privacy- and integrity- preserving fashion. SafeQ uses the   techniques of prefix membership verification, Merkle hash trees, and neighborhood chaining. In terms of security, SafeQ significantly strengthens the security of two-tiered sensor networks. Unlike prior art, SafeQ prevents a compromised storage node from obtaining a reasonable estimation on the actual values of sensor collected data items and sink issued queries. In terms of  efficiency, our results show that SafeQ significantly outperforms prior art for multidimensional data in terms of both power consumption and storage space. Second, we propose an optimization technique using Bloom filters to  significantly reduce the communication cost between sensors and storage nodes. Third, we propose a solution to adapt SafeQ for event-driven sensor networks.

 



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