Privacy- and Integrity-Preserving Range Queries in Sensor Networks

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.

ARCHITECTURE:

EXISTING SYSTEM:

In the existing system, 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.

PROPOSED SYSTEM:

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. we propose SafeQ, a novel and efficient protocol for handling range queries in two-tiered sensor networks in a privacy- and integrity- preserving fashion.

MODULES:

ü SafeQ

ü Integrity

ü Privacy

ü Range Queries

ü Sink

ü Storage Node

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.

SYSTEM CONFIGURATION:-

H/W SYSTEM CONFIGURATION:-

ü Processor                                          -    Pentium –III

ü Speed                                      -    1.1 Ghz

ü RAM                                       -    256  MB(min)

ü Hard Disk                                -   20 GB

ü Floppy Drive                           -    1.44 MB

ü Key Board                               -    Standard Windows Keyboard

ü Mouse                                     -    Two or Three Button Mouse

ü Monitor                                   -    SVGA

S/W SYSTEM CONFIGURATION:-

ü Operating System                             : Windows XP

ü Front End                                :   JAVA, RMI,SWING

ü Database                                 :   Microsoft Access 2003

ü Database Connectivity            :   JDBC.

REFERENCE:

Fei Chen and Alex X. Liu,” Privacy- and Integrity-Preserving Range Queriesin Sensor Networks”, IEEE/ACM TRANSACTIONS ON NETWORKING, 2012.