ensuring data storage security in cloud computing

ENSURING DATA STORAGE SECURITY IN CLOUD COMPUTING

Submitted By:Sheth M.Ovesh

Under the Guidance of:

Asist.Prof. Ajay Kumar Sharma M.Tech

A Working Definition of Cloud Computing

• Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.

5 Essential Cloud Characteristics

• On-demand self-service • Broad network access• Resource pooling–Location independence

• Rapid elasticity• Measured service

Cloud Objectives

-Correctness -Integrity -Flexibility -Maintainability -Accessibility -Availability

SYSTEM ARCHITECTURE

Existing System Traditional cryptographic primitives for the purpose of data

security protection can not be directly adopted due to the users’ loss control of data under Cloud Computing.

Therefore, verification of correct data storage in the cloud must be conducted without explicit knowledge of the whole data.

The data stored in the cloud may be frequently updated by the users, including insertion, deletion, modification, appending, reordering, etc. To ensure storage correctness under dynamic data update is hence of paramount importance.

None of the distributed schemes is aware of dynamic data

operations. As a result, their applicability in cloud data storage can be drastically limited.

Proposed System we propose an effective and flexible distributed scheme with

explicit dynamic data support to ensure the correctness of users’ data in the cloud.

We rely on ensure correcting code in the file distribution preparation to provide redundancies and guarantee the data dependability.

By utilizing the homomorphic token with distributed verification

of ensure-coded data, our scheme achieves the storage correctness insurance as well as data error localization.

Unlike most prior works for ensuring remote data integrity, the new scheme supports secure and efficient dynamic operations on data blocks, including: update, delete and append.

Windows Azure• Windows Azure is a foundation of Microsoft’s Cloud

Platform for Developers • Operating System for the Cloud

– Runs applications in the cloud– Provides Storage– Application Management– Developer SDK

• Windows Azure ideal for applications needing– Scalability– Availability– Fault Tolerance

Windows Azure Storage• Storage in the Cloud– Scalable, durable, and available– Anywhere at anytime access– Only pay for what the service uses

• Exposed via RESTful Web Services– Use from Windows Azure Compute– Use from anywhere on the internet

• Various storage abstractions– Tables, Blobs, Queues, Drives

Windows Azure Service Architecture

StorageTables

LB

Blobs

Worker Service

Worker Service

Worker Role

Managed Interface Call

Web Site(ASPX, ASMX,

WCF)

Web Site(ASPX, ASMX,

WCF)

Web Role

IIS as Host

Queues

Windows Azure Data Center

LBL

B

The InternetThe Internet via TCP or HTTP

Windows Azure Storage Abstractions

• Blobs – Simple named files along with metadata for the file.

• Tables – Structured storage. A Table is a set of entities; an entity is a set of properties

• Queues – Reliable storage and delivery of messages for an application

Blob Storage Concepts

BlobContainerAccount

user

images

PIC01.JPG

videos VID1.AVI

Pages/Blocks

Block/Page

Block/Page

PIC02.JPG

Table Storage Concepts

EntityTableAccount

user

customers

Name =…Email = …

Name =…EMailAdd= …

photos

Photo ID =…Date =…

Photo ID =…Date =…

Queue Storage Concepts

MessageQueueAccount

order processing

customer ID order ID http://…

customer ID order ID http://…

user

Cloud Computing Security

Security is the Major Issue

Key Server

Server

Message=Message + Key

K1

K2

Msg=Msg-Key

Client

Client

Module1:Ensuring Cloud Data Storage

RC4 Algorithm• RC4 is a stream cipher, symmetric key algorithm. The same algorithm is

used for both encryption and decryption as the data stream is simply XORed with the generated key sequence. The key stream is completely independent of the plaintext used.

• Stream cipher is one of the simplest methods of encrypting data where each bit of the data is sequentially encrypted using one bit of the key

Keystreamgenerator

Kc

Ciphering Key

Kc[i]m[i]

C[i]

One bit of cipher text

One bit of Plain textOne bit of Ciphering Key

The steps for RC4 encryption algorithm is as follows:• Get the data to be encrypted and the selected key.• Create two string arrays.• Initiate one array with numbers from 0 to 255.• Fill the other array with the selected key.• Randomize the first array depending on the array of the key.• Randomize the first array within itself to generate the final

key stream.• XOR the final key stream with the data to be encrypted to

give cipher text.

Steps of RC4 Algorithm

Initial with numberFrom 0 to 255

Fill with chosen key

Sbox1 Sbox2

Systematic Randomization

Final Key Stream

XOR Plain/Cipher TextCipher/Plain Text

Systematic Randomization

Error

ClientServer

Encoding Decoding

Module 2:Correctness Verification and Error Localization

CRC Algorithm for Encoding and Decoding

• The cyclic redundancy check, or CRC, is a technique for detecting errors in digital data, but not for making corrections when errors are detected.

• It is used primarily in data transmission. In the CRC method, a certain number of check bits, often called a checksum, are appended to the message being transmitted. The receiver can determine whether or not the check bits agree with the data, to ascertain with a certain degree of probability whether or not an error occurred in transmission.

• If an error occurred, the receiver sends a “negative acknowledgement” (NAK) back to the sender, requesting that the message be retransmitted.

Encoder and decoder for simple cyclic Redundancy Check

insert

update

view Server

Module3:Providing Dynamic Data Operation Support

CONCLUSION To ensure the correctness of users’ data in cloud data storage,

we proposed an effective and flexible distributed scheme with explicit dynamic data support, including block update, delete, and append.

By utilizing the homomorphic token with distributed verification of erasure coded data, our scheme achieves the integration of storage correctness insurance and data error localization, i.e., whenever data corruption has been detected during the storage correctness verification across the distributed servers, we can almost guarantee the simultaneous identification of the misbehaving server(s).

THANK YOU FOR

YOUR TIME