ENHANCING PRIVACY AND AUTHORIZATION CONTROL SCALABILITY IN THE GRID THROUGH ONTOLOGIE
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13-01-2010, 07:43 AM


ENHANCING PRIVACY AND AUTHORIZATION CONTROL SCALABILITY IN THE GRID THROUGH ONTOLOGIES--INFORMATION TECHNOLOGY IN BIOMEDICINE

The use of data Grids for sharing relevant data has proven to be successful in many research disciplines. However, the use of these environments when personal data are involved (such as in health) is reduced due to its lack of trust. There are many approaches that provide encrypted storages and key shares to prevent the access from unauthorized users. However, these approaches are additional layers that should be managed along with the authorization policies. We present in this paper a privacy-enhancing technique that uses encryption and relates to the structure of the data and their organizations, providing a natural way to propagate authorization and also a framework that fits with many use cases. The paper describes the architecture and processes, and also shows results obtained in a medical imaging platform.

Technology to use:JAVA
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09-04-2010, 03:29 PM


.pptx   Enhancing Privacy and Authorization Control.pptx (Size: 989.95 KB / Downloads: 181)


Enhancing Privacy and Authorization Control Scalability in the Grid Through Ontology

Data Security and Privacy
Authorization through Virtual Organization
Grid Service through Ontology
DES Algorithm used for encryption and decryption of data

Objectives

To propose an on-the-fly cryptographic infrastructure to protect privacy from users with administrative privileges.
To provide a flexible architecture for organizing key management for long-term storage of encrypted data.
To propose a model applicable in different environments, compatible with current Grid middleware.
To provide an access control mechanism for encryption keys based on ontological groups and roles.


Security Model
Grid Architecture
Grid Security Infrastructure
VO Management and Ontology
Information Object Storage
Encryption and Decryption of Data

Access control relation among ontology-VO groups”information objects storage
Storage and Management Of Encrypted Data
Reconstruction of the decryption key
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vigneshprabhu88
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#3
14-05-2010, 07:03 PM

Hi can any buddy help me to find report and ppt of the project and implimentation topic Enhancing Privacy and Authorization Control
Scalability in the Grid Through Ontologies...........if u have the document plz mail it to my e-id vignesh.prabhu20@gmail.com
Hi, can u help me to find report and ppt of the project and implimentation topic:: Enhancing Privacy and Authorization Control Scalability in the Grid Through Ontologies...........if u have the document plz mail it to my e-id vignesh.prabhu20@gmail.com
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vigneshprabhu88
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14-05-2010, 07:14 PM

Hi,do u have report of the project and implimentation topic:: Enhancing Privacy and Authorization Control Scalability in the Grid Through Ontologies...........if u have the document plz mail it to my e-id vignesh.prabhu20@gmail.com
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Sidewinder
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#5
17-05-2010, 08:16 AM

Hi,
the ppt of this topic is posted in the second post of this thread. The full report pdf is available in ieee xplore:
ieeexplore.ieeeXplore/login.jsp?reload=true&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F4233%2F4358869%2F04588359.pdf%3Farnumber%3D4588359&authDecision=-203

you will have to login to the ieee xplore site using your institution's subscription or probably of your friend.
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Venkat Raman1
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#6
19-12-2010, 11:46 PM

hi,

I'm doing M.Sc, and doing Project in this topic. If you have document pls send it to my email - id (srivenkatraman02@gmail.com). Thank you...
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seminar surveyer
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#7
20-12-2010, 09:27 AM

hi
previous page containing a ppt file. please download it
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annushika
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#8
11-03-2011, 12:07 PM

hi,
Can you please send the report of the project and implimentation"ENHANCING PRIVACY AND AUTHORIZATION CONTROL SCALABILITY IN THE GRID THROUGH ONTOLOGIES" to sekar.s32@gmail.com if you have....
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vigneshprabhu88
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#9
11-03-2011, 02:48 PM

Hi have a look on this report n if any changes plz update it....Smile


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.zip   Report_V1.1.zip (Size: 887.88 KB / Downloads: 25)
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annushika
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24-03-2011, 02:14 PM

hi,
Can you please send the implementation of the project and implimentation"ENHANCING PRIVACY AND AUTHORIZATION CONTROL SCALABILITY IN THE GRID THROUGH ONTOLOGIES" to sekar.s32[at]gmail.com if you have....


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annushika
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24-03-2011, 02:29 PM

hi,
Can you please send the implementation of the project and implimentation"ENHANCING PRIVACY AND AUTHORIZATION CONTROL SCALABILITY IN THE GRID THROUGH ONTOLOGIES" to sekar.s32[at]gmail.com if you have....
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#12
30-04-2011, 03:41 PM

hi
you can refer this page to get the details on enhancing privacy and authorisation control scalability in grid through ontologies


topicideashow-to-enhancing-privacy-and-authorization-control-scalability-in-the-grid-through-ontologie
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smart paper boy
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24-08-2011, 02:45 PM


.pptx   Enhancing Privacy and Authorization Control.pptx (Size: 217.12 KB / Downloads: 58)
Enhancing Privacy and Authorization Control Scalability in the Grid through Ontologies
Objective and Scope:

In this paper a privacy-enhancing technique that uses encryption and relates to the structure of the data and their organizations, providing a natural way to propagate
authorization and also a framework that fits with many use cases is discussed.
In this paper a privacy-enhancing technique that uses encryption and relates to the structure of the data and their organizations, providing a natural way to propagate authorization and also a framework that fits with many use cases is discussed.
Data Grid depends on a set of widely distributed and untrusted storage nodes, therefore offering no guarantees about neither availability nor protection to the stored data
We propose a cryptographic protocol able to fulfill the storage security requirements related with a generic Desktop Data Grid scenario, which were identified after applying an analysis framework extended from our previous research on the Data Grid’s storage services.
Theoretical Background:
EXISTING SYSTEM:

One of the challenges for biomedical application is to provide efficient high-level interfaces, depending on the applications that enable access to Grids for nonexperts, ensuring transparent access to medical resources through services compatible with medical practice. As part of the interfaces, a flexible architecture for the management of the privacy of data is needed, compatible with medical practice and with preexisting Grid security systems are complex enough to be considered an obstacle in the successful Grid adoption.
Proposed System:
1) To propose an on-the-fly cryptographic infrastructure to protect privacy from users with administrative privileges.
2) To provide a flexible architecture for organizing key management for long-term storage of encrypted data.
3) To propose a model applicable in different environments, Compatible with current Grid middleware’s.
4) To provide an access control mechanism for encryption keys based on ontological groups and roles.
Definition of problem:
In existing there is no absolute protection guarantee for stored data .
Compatibility with various fields is not possible.
The nonexpert users are unable to use the interfaces.
The key Management is also a problem.
System Requirements:
Problem formulation:

User Login checking for authorization process. To avoid unauthorized person.
Applying Cryptography concept with DES Algorithm to solve Encryption and Decryption concept.
File Storage using Virtual Organization (VO) to choose lot of clients to avoid interruption process.
System Architecture:
Use case:
CLASS DIAGRAM:
Data Flow Diagram:
Modules:
GROUP CONSTRUCTION

FILE ENCRYPTION AND DECRYPTION
KEY DISTRIBUTION
VIRTUAL ORGANIZATION
GROUP CONSTRUCTION
Grid user must signup before login to give his\her details, the servers performing all the authentication and authorization processes for involved entities (users and resources). Based on the signup details user must use both username and password to login. User’s information is stored in database side to maintain separate server. User without login they can’t access any information for any sort of service every login information must protect by the data server as well as authentication. This process is maintained by grid service
FILE ENCRYPTION AND DECRYPTION
Encryption is the manipulation of data, based on a password (also known as a key), for security purposes. Once your data has been encrypted, a person can not make sense of your data without knowing the password.
Encryption  is a  process of coding information which could either be a file or  mail message  in into text  a form unreadable without a decoding key in order to prevent anyone except the intended recipient from reading that data.
Decryption is the reverse process of converting encoded data to its original un-encoded form, plaintext.
The most widely used symmetric key cryptographic method is the Advanced Encryption Standard (AES) is used in this process.
The algorithm is best suited to implementation in hardware, probably to discourage implementations in software, which tend to be slow by comparison.
AES is the most widely used symmetric algorithm in the world, despite claims that the key length is too short.(128 bits)
The two components required to encrypt data are an algorithm and a key.
KEY DISTRIBUTION  
The file is send to decryption process to get original file.
File system are usually managed in units called blocks or clusters.
When a file system is created, there is free space to store file blocks together contiguously. This allows for rapid sequential file reads and writes.
AES is the most widely used symmetric algorithm in the world, despite claims that the key length is too short. Ever since AES was first announced, controversy has raged about whether 128 bits is long enough to guarantee security. Key Distribution maintain the process to share the key from authorized users which is located in group distribution.
Virtual organisation:
Virtual computing (also called “peer-to-peer computing” or “global computing”) uses computers volunteered by the general public to do distributed.
Virtual computing uses Internet-connected computers, volunteered by their owners, as a source of computing power and storage.
Here VO is act as desktop it is used to maintain the files into various parts to protect and to return exact user who registered in grid service.
The common architecture of desktop grids consists of one or more central servers and a large number of clients.
ALGORITHM USED:[AES]
Data encryption is the mechanism of converting a message (plain text) into some other text (called ciphertext) however some authorized party can understand that ciphertext using the method called Decryption which converts the ciphertext into original message. As many software applications store sensitive personal data in databases, encryption has become a must. Ideally nobody (including the software developers) should not be able to view these user specific real data.
Implementation:
User Login checking for authorization process through group formation. To avoid unauthorized person.
Applying Cryptography concept with AES Algorithm to solve Encryption and Decryption concept.
File Storage using Virtual Organization (VO) to choose lot of clients to avoid interruption process.
ENHANCEMENT MAINTENANCE:
Now we applied only in Data Grid security. In future we can apply at any sort of business application to produce absolute development and with security enhancement.
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02-11-2012, 03:33 PM

Enhancing Privacy and Authorization Control Scalability in the Grid Through Ontologie


.doc   Enhancing Privacy.doc (Size: 1 MB / Downloads: 19)

INTRODUCTION

Project Description

The use of data Grids for sharing relevant data has proven to be successful in many research disciplines. However, the use of these environments when personal data is involved (such as in bank account details) is reduced due to lack of trust. There are many approaches that provide encrypted storages and key shares to prevent the access from unauthorized users. However, these approaches are additional layers that should be managed along with the authorization policies. The main purpose of this project and implimentation is to protect data in Grid based storage service. Which are faced while performing data storage and we propose a cryptographic and fragmentation able to fulfill the storage security requirements related with a generic Data Grid scenario. The Data Grid is a specific type of distributed system, where shared resources (processor or storage) are provided in a volunteer fashion by the participants. These environments potentially provide commodity resources not only for CPU-intensive tasks, but also for applications that require significant amounts of memory, disk space and network through put. Data Grid depends on a set of widely distributed and untrusted storage nodes, therefore offering no guarantees either of availability or protection of the stored data.
These security challenges must be carefully managed before fully deploying Data Grids in sensitive environments. We propose a cryptographic protocol which is able to fulfill the storage security requirements related with a generic Desktop Data Grid scenario, which were identified after applying an analysis framework extended over previous Data Grid’s storage services.

Problem statement

Data security is a key requirement for Grid based storage applications. Dealing with the different Grid regulations and procedures accepted by the medical community requires a careful approach.
One of the challenges for biomedical application is to provide efficient high-level interfaces, depending on the applications that enable access to Grids for nonexperts, ensuring transparent access to medical resources through services compatible with medical practice. As part of the interfaces, a flexible architecture for the management of the privacy of data is needed, compatible with medical practice and with preexisting medical information systems.

Scope of the study

This study reveals the about a privacy-enhancing technique that uses encryption and relates to the structure of the data and their organizations, providing a natural way to propagate authorization and also a framework that fits with many use cases.

Existing System

One of the challenges for general grid application is to provide efficient high-level interfaces, depending on the applications that enable access to Grids for non-experts, ensuring transparent access to resources through services compatible with legal practice. As part of the interfaces, a flexible architecture for the management of the privacy of data is needed, compatible with practice and with preexisting Grid security systems are complex enough to be considered an obstacle in the successful Grid adoption. In existing there is no absolute protection guarantee for stored data.

Disadvantages

In existing there was no absolute protection guarantee for stored data.

Proposed System

The main objective of this paper is to provide Grid middleware’s such as TRENCADIS, with efficient and reliable privacy protection for sensitive data. This project and implimentation presents a model for long-term storage and management of encrypted data in distributed environments. Furthermore, the project and implimentation outlines how this model is implemented to preserve the privacy of patient information in Grid-based collaborative computational infrastructures for biomedical applications. This project and implimentation delineates a dependable security framework in overextended organizations. Throughout the assembly of this framework, organizations will encounter different degrees of data integrity and confidentiality.

LITERATURE SURVEY

Open Grid Services Architecture (OGSA)

Open Grid Services Architecture (OGSA) The Open Grid Services Architecture (OGSA) describes an architecture for a service-oriented grid computing environment for business and scientific use. OGSA is a distributed interaction and computing architecture based around services, assuring interoperability on heterogeneous systems so that different types of resources can communicate and share information. OGSA has been described as a refinement of the emerging Web Services architecture, specifically designed to support Grid requirements.

Virtual Organization (VO)

Virtual Organization (VO) refers to a dynamic set of individual or group defined around a set of resource-sharing rules and conditions. All these virtual organizations share some commonality among them, including common concerns and requirements, but may vary in size, scope, duration and structure.

Ontology

Ontology is a model for describing the world that consists of a set of types, properties, and relationship types. There is also generally an expectation that there be a close resemblance between the real world and the features of the model in an ontology. Ontology engineering is a computer science field, which studies the methods and methodologies for building ontologies i.e. formal representations of a set of concepts within a domain and the relationships between these concepts.

DES encryption standard

DES encrypts and decrypts data in 64-bit blocks, using a 64-bit key (although the effective key strength is only 56 bits, as explained below). It takes a 64-bit block of plaintext as input and outputs a 64-bit block of ciphertext. Since it always operates on blocks of equal size and it uses both permutations and substitutions in the algorithm, DES is both a block cipher and a product cipher.
DES has 16 rounds, meaning the main algorithm is repeated 16 times to produce the ciphertext. It has been found that the number of rounds is exponentially proportional to the amount of time required to find a key using a brute-force attack. So as the number of rounds increases, the security of the algorithm increases exponentially.

JAVA Swings

The Java Swing provides the multiple platform independent APIs interfaces for interacting between the users and GUIs components. All Java Swing classes imports from the import javax.swing.*; package. Java provides interactive features for design the GUIs toolkit or components like: labels, buttons, text boxes, checkboxes, combo boxes, panels and sliders etc. All AWT flexible components can be handled by the Java Swing. The Java Swing supports the plugging between the look and feel features. The look and feel that means the dramatically changing in the component like JFrame, JWindow, JDialog etc. for viewing it into the several types of window.

ODBC

Microsoft Open Database Connectivity (ODBC) is a standard programming interface for application developers and database systems providers. Before ODBC became a de facto standard for Windows programs to interface with database systems, programmers had to use proprietary languages for each database they wanted to connect to. Now, ODBC has made the choice of the database system almost irrelevant from a coding perspective, which is as it should be. Application developers have much more important things to worry about than the syntax that is needed to port their program from one database to another when business needs suddenly change.
Through the ODBC Administrator in Control Panel, you can specify the particular database that is associated with a data source that an ODBC application program is written to use. Think of an ODBC data source as a door with a name on it. Each door will lead you to a particular database. For example, the data source named Sales Figures might be a SQL Server database, whereas the Accounts Payable data source could refer to an Access database. The physical database referred to by a data source can reside anywhere on the LAN.

JDBC

In an effort to set an independent database standard API for Java, Sun Microsystems developed Java Database Connectivity, or JDBC. JDBC offers a generic SQL database access mechanism that provides a consistent interface to a variety of RDBMSs. This consistent interface is achieved through the use of “plug-in” database connectivity modules, or drivers. If a database vendor wishes to have JDBC support, he or she must provide the driver for each platform that the database and Java run on.
To gain a wider acceptance of JDBC, Sun based JDBC’s framework on ODBC. As you discovered earlier in this chapter, ODBC has widespread support on a variety of platforms. Basing JDBC on ODBC will allow vendors to bring JDBC drivers to market much faster than developing a completely new connectivity solution.
JDBC was announced in March of 1996. It was released for a 90 day public review that ended June 8, 1996. Because of user input, the final JDBC v1.0 specification was released soon after.

Functional Requirements

Functional requirements capture the intended behavior of the system. This behavior may be expressed as services, tasks or functions the system is required to perform.
In product development, it is useful to distinguish between the baseline functionality necessary for any system to compete in that product domain, and features that differentiate the system from competitors’ products, and from variants in your company’s own product line/family. Features may be additional functionality, or differ from the basic functionality along some quality attribute (such as performance or memory utilization).
One strategy for quickly penetrating a market, is to produce the core, or stripped down, basic product, adding features to variants of the product to be released shortly thereafter. This release strategy is obviously also beneficial in information systems development, staging core functionality for early releases and adding features over the course of several subsequent releases.

Non-Functional Requirements

Non-Functional Requirements in Software Engineering presents a systematic and pragmatic approach to `building quality into' software systems. Systems must exhibit software quality attributes, such as accuracy, performance, security and modifiability. However, such non-functional requirements (NFRs) are difficult to address in many project and implimentations, even though there are many techniques to meet functional requirements in order to provide desired functionality. This is particularly true since the NFRs for each system typically interact with each other, have a broad impact on the system and may be subjective. To enable developers to systematically deal with a system's diverse NFRs, this book presents the NFR Framework. Structured graphical facilities are offered for stating NFRs and managing them by refining and inter-relating NFRs, justifying decisions, and determining their impact. Since NFRs might not be absolutely achieved, they may simply be satisfied sufficiently (`satisficed'). To reflect this, NFRs are represented as `softgoals', whose interdependencies, such as tradeoffs and synergy, are captured in graphs. The impact of decisions is qualitatively propagated through the graph to determine how well a chosen target system satisfices its NFRs. Throughout development, developers direct the process, using their expertise while being aided by catalogues of knowledge about NFRs, development techniques and tradeoffs, which can all be explored, reused and customized.

SYSTEM OVERVIEW:

Computational Grids offer a number of benefits and opportunities to biomedicine, healthcare, and other biomedical domain areas. Several recent systems focused on new health-related applications are analyzed.
The Medical Data Manager (MDM) is a data management service designed to handle medical images on Grids, strongly based to the gLite middleware. The MDM aims at guaranteeing patient’s privacy by keeping private data in acquisition centers. However, this approach comes along with higher complexity in the specification and maintenance of the access policies. Granting full access right to information objects (both image data and header attributes from a DICOM file) requires achieving a number of capabilities kept by different services in the form of access control lists (ACLs). This approach has deficiencies in systems where the potential users will not be known beforehand. The higher flexibility of attribute-based approaches enables the model presented in this paper to deal efficiently with these requirements.

Grid Architecture:

Most of the current Grid middlewares are based on Web services protocols. The Open Grid Services Architecture (OGSA) is a specification in progress that aims at defining a standard and open architecture for Grid-based applications.
The Globus Toolkit is a realization of OGSA, which can be used to develop Grid applications. Globus Toolkit Version 4 (GT4) provides services implemented on top of the Web Service Resource Framework (WSRF), a specification that extends Web services with stateful services and other features. The services of the architecture presented in this paper are all based on OGSA/WSRF.
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