Security and Privacy Support for Data-Centric Sensor Networks
Abstract

demand for efficient data dissemination/access techniques to find relevant data from within a sensor network has led to the development of Data-Centric Sensor (DCS) networks where the sensor data instead of sensor nodes are named based on attributes such as event type or geographic location.

However, saving data inside a network also creates security problems due to the lack of tamper resistance of the sensor nodes and the unattended nature of the sensor network.

For example, an attacker may simply locate and compromise the node storing the event of his interest.

To address these security problems, we present pDCS, a privacy-enhanced DCS network which offers different levels of data privacy based on different cryptographic keys.

pDCS also includes an efficient key management scheme to facilitate the management of multiple types of keys used in the system.

In addition, we propose several query optimization techniques based on euclidean Steiner Tree and keyed Bloom Filter (KBF) to minimize the query overhead while preserving query privacy.

Finally, show that the KBF scheme can significantly reduce the message overhead with the same level of query delay and maintain a very high level of query privacy

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PDCS: SECURITY AND PRIVACY SUPPORT FOR DATA-CENTRIC SENSOR NETWORKS
ABSTRACT
The demand for efficient data dissemination/access techniques to find relevant data from within a sensor network has led to the development of Data-Centric Sensor (DCS) networks, where the sensor data instead of sensor nodes are named based on attributes such as event type or geographic location. However, saving data inside a network also creates security problems due to the lack of tamper resistance of the sensor nodes and the unattended nature of the sensor network. For example, an attacker may simply locate and compromise the node storing the event of his interest. To address these security problems, we present pDCS, a privacy enhanced
DCS network which offers different levels of data privacy based on different cryptographic keys. pDCS also includes an efficient key management scheme to facilitate the management of multiple types of keys used in the system. In addition, we propose several query optimization techniques based on euclidean Steiner Tree and keyed Bloom Filter (KBF) to minimize the query overhead while preserving query privacy. Finally, detailed analysis and simulations show that the KBF scheme can significantly reduce the message overhead with the same level of query delay and maintain a very high level of query privacy.
1.INTRODUCTION
SENSOR networks are envisioned to be extremely useful for a broad spectrum of emerging civil and military applications, such as remote surveillance, habitat monitoring, and collaborative target tracking. Sensor networks scale in size as time goes on, so does the amount of sensing data generated. The large volume of data coupled with the fact that the data are spread across the entire network creates a demand for efficient data dissemination/access techniques to find the relevant data from within the network. This demand has led to the development of Data-Centric Sensor (DCS) networks . DCS exploits the notion that the nature of the data is more important than the identities of the nodes that collect the data. Thus, sensor data as contrasted to sensor nodes are “named,” based on attributes such as event type (e.g.,elephant sightings) or geographic location. According to their names, the sensing data are passed to and stored at corresponding sensor nodes determined by a mapping function such as Geographic Hash Table (GHT). As the sensing data with the same name are stored in the same location, queries for data of a particular name can be sent directly to the storing nodes using geographic routing protocols such as GPSR, rather than flooding the query throughout the network.A DCS-based sensor network to monitor the activities or presence of animals in a wild animal habitat. The sensed data can be used by zoologists to study the animals or by an authorized hunter to locate certain types of animals (e.g., boars and deers) for hunting. With DCS, all the sensing data regarding one type of animals are forwarded to and stored in one location. As a result, a zoologist only needs to send one query to the right location to find out the information about that type of animals. Similarly, a soldier can easily obtain enemy tank information from storage sensors through a DCS-based sensor network in the battlefield.
1.1 PROJECT DESCRIPTION
The project entitled as “pDCS: Security and Privacy Support forData-Centric Sensor Networks
” developed using Java Modules display as follows.
• Login/Registration
• Node Analysis
• Finding shortest path.
• Server Message.
MODULES DESCRIPTION:
1) Login / Registration:
This is a module mainly designed to provide the authority to a user in order to access the other modules of the project. Here a user can have the accessibility authority after the registration.
2) Node Analysis
There will be a cluster of node analyzing which is efficient node.
3) Finding the shortest path
The process of finding which is shortest path to hunt the destination
4) Server Message
Server send which are the permitted node to hunt.
2.SYSTEM STUDY
2.1 FEASIBILITY STUDY
The feasibility of the project is analyzed in this phase and business proposal is put forth with a very general plan for the project and some cost estimates. During system analysis the feasibility study of the proposed system is to be carried out. This is to ensure that the proposed system is not a burden to the company. For feasibility analysis, some understanding of the major requirements for the system is essential.
Three key considerations involved in the feasibility analysis are
• ECONOMICAL FEASIBILITY
• TECHNICAL FEASIBILITY
• SOCIAL FEASIBILITY
ECONOMICAL FEASIBILITY
This study is carried out to check the economic impact that the system will have on the organization. The amount of fund that the company can pour into the research and development of the system is limited. The expenditures must be justified. Thus the developed system as well within the budget and this was achieved because most of the technologies used are freely available. Only the customized products had to be purchased.
TECHNICAL FEASIBILITY
This study is carried out to check the technical feasibility, that is, the technical requirements of the system. Any system developed must not have a high demand on the available technical resources. This will lead to high demands on the available technical resources. This will lead to high demands being placed on the client. The developed system must have a modest requirement, as only minimal or null changes are required for implementing this system.
SOCIAL FEASIBILITY
The aspect of study is to check the level of acceptance of the system by the user. This includes the process of training the user to use the system efficiently. The user must not feel threatened by the system, instead must accept it as a necessity. The level of acceptance by the users solely depends on the methods that are employed to educate the user about the system and to make him familiar with it. His level of confidence must be raised so that he is also able to make some constructive criticism, which is welcomed, as he is the final user of the system.
2.2 EXISTING SYSTEM
 Privacy is not sufficient
 Maximum query overhead
2.3 PROPOSED SYSTEM
 Privacy support for DCS networks
 KBF scheme can significantly reduce the message overhead with the same level of query delay