1. Ensuring data storage security in cloud computing
Submitted By:
Sheth M.Ovesh
Under the Guidance of:
Asist.Prof. Ajay Kumar Sharma
M.Tech

2. 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.

3. 5 Essential Cloud Characteristics
On-demand self-service
Broad network access
Resource pooling
Location independence
Rapid elasticity
Measured service
1.On-Demand Self-Service:
->Completely automated
->Users abstracted from the implementation
->Near real-time delivery (seconds or minutes)
->Services accessed through a self-serve web interface
2.Broad Network Access:
->Open standards and APIs
->Almost always IP, HTTP, and REST
->Available from anywhere with an internet connection
3.Shared / Pooled Resources:
->Resources are drawn from a common pool
->Common resources build economies of scale
->Common infrastructure runs at high efficiency
4.Scalable and Elastic:
->Resources dynamically-allocated between users
->Additional resources dynamically-released when needed
->Fully automated
5.Metered by Use:
->Services are metered, like a utility
->Users pay only for services used
->Services can be cancelled at any time

4. Cloud Objectives -Correctness -Integrity -Flexibility -Maintainability
-Accessibility
-Availability

5. SYSTEM ARCHITECTURE

6. 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.

7. 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.

8. 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
This should be a recap as this session will dig deeper into the services.

9. 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
This should be a recap as this session will dig deeper into the services.

10. Windows Azure Service Architecture
The Internet
The Internet via TCP or HTTP LB LB LB
Web Site
(ASPX, ASMX, WCF)
Web Role
IIS as Host
Storage
Queues
Worker Service
Worker Role
Managed Interface Call
Slide Objective
Understand at a high level how the Windows Azure Platform maps into the high scale archetype
Speaker Notes
Key points here are
that all external connections come through a load balancer THIS INCLUDES STORAGE.
If you are familiar with the previous model, you will notice that two new features are diagrammed here as well, namely inter-role communication (notice there is no load balancer) and TCP ports directly to Worker Roles (or Web Roles).
We will still use the storage to communicate async and reliably via queues for a lot of options.
However, inter-role communication fills in when you need direct synchronous comm.
The load balancers are a key to Windows Azure.
Tables
Blobs
Windows Azure Data Center

11. 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
Slide Objectives
Understand each of the storage types at a high level
Speaker Notes
The Windows Azure storage services provide storage for binary and text data, messages, and structured data in Windows Azure. The storage services include:
The Blob service, for storing binary and text data
The Queue service, for storing messages that may be accessed by a client
The Table service, for structured storage for non-relational data
Windows Azure drives, for mounting an NTFS volume accessible to code running in your Windows Azure service
Programmatic access to the Blob, Queue, and Table services is available via the Windows Azure Managed Library and the Windows Azure storage services REST API
Notes

12. Blob Storage Concepts Pages/ Blob Blocks Account Container images
PIC01.JPG
images
Block/Page
PIC02.JPG
user
Slide Objectives
Understand the hierarchy of Blob storage
Speaker Notes
The Blob service provides storage for entities, such as binary files and text files.
The REST API for the Blob service exposes two resources:
Containers
Blobs.
A container is a set of blobs; every blob must belong to a container.
The Blob service defines two types of blobs:
Block blobs, which are optimized for streaming.
Page blobs, which are optimized for random read/write operations and which provide the ability to write to a range of bytes in a blob.
Blobs can be read by calling the Get Blob operation. A client may read the entire blob, or an arbitrary range of bytes.
Block blobs less than or equal to 64 MB in size can be uploaded by calling the Put Blob operation.
Block blobs larger than 64 MB must be uploaded as a set of blocks, each of which must be less than or equal to 4 MB in size.
Page blobs are created and initialized with a maximum size with a call to Put Blob.
To write content to a page blob, you call the Put Page operation. The maximum size currently supported for a page blob is 1 TB.
Notes
Using the REST API for the Blob service, developers can create a hierarchical namespace similar to a file system. Blob names may encode a hierarchy by using a configurable path separator. For example, the blob names MyGroup/MyBlob1 and MyGroup/MyBlob2 imply a virtual level of organization for blobs. The enumeration operation for blobs supports traversing the virtual hierarchy in a manner similar to that of a file system, so that you can return a set of blobs that are organized beneath a group. For example, you can enumerate all blobs organized under MyGroup/.
Block/Page
videos
VID1.AVI

13. Table Storage Concepts
Account
Table
Entity
Name =…
= …
customers
Name =…
Add= …
Slide Objectives
Understand Tables
Speaker Notes
The Table service provides structured storage in the form of tables.
The Table service supports a REST API that is compliant with the ADO.NET Data Services REST API.
Developers may also use the .NET Client Library for ADO.NET Data Services to access the Table service.
Notes
user
Photo ID =…
Date =…
photos
Photo ID =…
Date =…

14. Queue Storage Concepts
Account
Queue
Message
customer ID order ID
user
order processing
Slide Objectives
Understand Queues
Speaker Notes
The Queue service provides reliable, persistent messaging within and between services. The REST API for the Queue service exposes two resources: queues and messages.
Notes
customer ID order ID

15. Cloud Computing Security

16. Security is the Major Issue

17. Module1:Ensuring Cloud Data Storage
Key Server K1
Msg=Msg-Key
Message=Message + Key
Server
Client K2
Client

19. 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
One bit of Plain text
One bit of Ciphering Key
m[i]
Kc[i]
Keystream
generator Kc
C[i]
Ciphering Key
One bit of cipher text

20. Steps of RC4 Algorithm
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.

21. Systematic Randomization
Initial with
number
From 0 to 255
Fill with
chosen key
Sbox1
Sbox2
Systematic Randomization
Systematic Randomization
Final Key Stream
XOR
Cipher/Plain Text
Plain/Cipher Text

22. Module 2:Correctness Verification and Error Localization
Encoding
Decoding
Client
Server

23. 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.

24. Encoder and decoder for simple cyclic Redundancy Check

26. Module3:Providing Dynamic Data Operation Support
insert
update
view
Server

27. 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).

28. THANK YOU
FOR
YOUR TIME 