 Open Access
 Total Downloads : 251
 Authors : L. Muralidaran, T. Vidhya, K. Swathy, K. Kanimozhi
 Paper ID : IJERTV2IS121109
 Volume & Issue : Volume 02, Issue 12 (December 2013)
 Published (First Online): 27122013
 ISSN (Online) : 22780181
 Publisher Name : IJERT
 License: This work is licensed under a Creative Commons Attribution 4.0 International License
Ensures Data Security and Message Integrity in Cloud using Hibernation
L. Muralidaran1 T. Vidhya2 K. Swathy3 K. Kanimozhi4
Assistant Professor, Dept. of CSE, Christ college of Engineering & technology, Puducherry.
U.G Student, Dept. of CSE, Christ college of Engineering & technology, Puducherry.
U.G Student, Dept. of CSE, Christ college of Engineering & technology, Puducherry.
U.G Student, Dept. of CSE, Christ college of Engineering & technology, Puducherry
Abstract
Cloud computing where users can remotely store their data into the cloud so as to enjoy the on demand high quality applications and services from a shared pool of configurable computing resources, so that users can resort to an external audit party to check the integrity of outsourced data when needed. Here we present a technique for distributing trust needing computation onto insecure networks, while providing probabilistic guarantees that malicious agents that compromise parts of the network cannot learn private data. As security is concerned, We implies Elliptic Curve Cryptography (ECC) algorithm along with hashing technique for ensuring security for the message to be sent along with acknowledge.
Keywords: Cloud computing, data privacy, ECC, hibernation, hashing.

Introduction
Cloud Computing has been envisioned as the nextgeneration architecture of IT enterprise, due to its long list of unprecedented advantages in the IT history: ondemand selfservice, ubiquitous network access, location independent resource pooling, rapid resource elasticity, usagebased pricing and transference of risk. As a disruptive technology with profound implications, Cloud Computing is transforming the very nature of how businesses use information technology. One fundamental aspect of this paradigm shifting is that data is being centralized or outsourced into the Cloud. While these advantages of using clouds are unarguable, due to the opaqueness of the Cloudas separate administrative entities, the internal operation details of cloud service providers (CSP) may not be known by cloud users
data outsourcing is also relinquishing users ultimate control over the fate of their data. As a result, the correctness of the data in the cloud is being put at risk due to the following reasons.
Fig 1: Network Architecture for the Cloud Users
We provide secure and privacypreserving access control to users, which guarantees any member in a group to anonymously utilize the cloud resource. And also we provide rigorous security analysis, and perform extensive simulations to demonstrate the efficiency of our scheme in terms of storage and computation overhead. The security and confidentiality for our document is provided by ECC algorithm. The discrete problem on elliptic curve groups is believed to be more difficult to trace when compared to other algorithms. Using the finite fields we can form an Elliptic Curve Group where we also have a DLP problem which is harder to solve so that
the intruder cannot find the traces easily, which provides a high level of security.

"Elliptic" is not elliptic in the sense of a "oval circle".

"Curve" is also quite misleading if we're operating in the field Fp. The drawing that many pages show of a elliptic curve in R is not really what you need to think of when transforming that curve into Fp. Rather than a real "curve" (i.e. a notstraight line), it is more like a cloud of points in the field — these points are not connected. The ECC equation is

Plotting multiple things is done by adding plots in Sage. Consequently we will be able to use the sum function to plot all points
Fig 2: Plotted points along with subgroups
We provide secure and privacypreserving access control to users, which guarantees any member in a group to anonymously utilize the cloud resource. And also we provide rigorous security analysis, and perform extensive simulations to demonstrate the efficiency of our scheme in terms of storage and computation overhead.

In precise, our proposed system includes the concept of Elliptical Curve Cryptography Algorith(ECC) to provide the high level of security by using graphical plots or curves. This is done since discrete logarithm problem on elliptic curve groups is believed to be more difficult than the corresponding problem in (the multiplicative group of nonzero elements of) the underlying finite field.
Then it is followed by hashing concept which is used here as a tool to identify the intruders trying to decrypt our entire system. Then comes hibernate which maintains our database persistent and reduces the number of hits.
1.1 ECC Algorithm
Alice
Private key dA, Public key QA=dAP.
Signature generation

Select a random k from [1, n1]

Compute kP=(x1,y1) and r=x1mod n. if r=0 goto step 1

Compute e=H(m), where H is a hash functon, m is the message.

Compute s=k1(e+dAr) mod n. If s=0 go to step 1. (r, s) is Alices signature of message m
Bob
Signature verification

Verify that r, s are in the interval [1,n1]

Compute e=H(m), where H is a hash functon, m is the message.

Compute w=s1 mod n

Compute u1=ew mod n and u2=rw mod n. 5.Compute X=u1P+u2QA=(x1,y1) 6.Compute v=x1 mod n

Accept the signature if and only if
v=r m, r ,s

An elliptic curve over a field K is a nonsingular cubic curve in two variables, f(x,y) =0 with a rational point (which may be a point at infinity).
2
2

Elliptic curves groups for cryptography are examined with the underlying fields of Fp (where p>3 is a prime) and F m (a binary representation with 2m elements).

Any application where security is needed but lacks the power, storage and computational power that is necessary for our current cryptosystems

Fig 3: Entire proposed system architecture

Related Work
In [1] compared the different schemes in the Cloud computing field. However, concerns of sensitive information on cloud potentially causes privacy problems. In this model, Data encryption protects data security to some extent, but at the cost of compromised efficiency. Searchable symmetric encryption (SSE) allows retrieval of encrypted data over cloud. For the first time, they formulated the privacy issue from the aspect of similarity relevance and scheme robustness. And observed that server side ranking based on orderpreserving encryption (OPE) inevitably leaks data privacy. To eliminate the leakage, they proposed a tworound searchable encryption (TRSE) scheme that supports topk multikeyword retrieval. In TRSE, we employ a vector space model and homomorphic encryption. The vector space model helps to provide sufficient search accuracy, and the homomorphic encryption enables users to involve in the ranking while the majority of computing work is done on the server side by
operations only on ciphertext. As a result, information leakage can be eliminated and data security is ensured. Thorough security and performance analysis show that this scheme guarantees high security and practical efficiency. The drawback of this scheme is as leakage of data is concerned they have not been able to completely overcome the problem.
Fig 4: Graphical Representation of SSE
In [2], data owners are motivated to outsource their complex data management sysems from local sites to commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data has to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in cloud, it is crucial for the search service to allow multikeyword query and provide result similarity ranking to meet the effective data retrieval need. Related works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely differentiate the search results.

System model
Cloud computing though provides a very dynamic and profitable structure; however it introduces significant concerns about privacy, security, data integrity, and intellectual property management, audit trails, and other issues. Because of the control that consumers of cloud services to providers, successful initiatives rely on a high degree of trust between a Client (Organization or university) and a supplier, including confidence in the providers long term viability.
Cloud Storage
Fig 6: Ecc operations
Hibernation for performance
Hibernation for performance
Publickey cryptography is based on the intractability of certain mathematical problems. Early publickey systems are secure assuming that it is
E
E
S difficult to factor a large integer composed of two or
V
V
R more large prime factors. For ellipticcurvebased
Elliptic Curve Cryptography Algorithm for Security
Elliptic Curve Cryptography Algorithm for Security
Hashing Algorithm For Integrity
Hashing Algorithm For Integrity
R
R
E protocols, it is assumed that finding the discrete logarithm of a random elliptic curve element with respect to a publicly known base point is infeasible this is the "elliptic curve discrete logarithm problem" or ECDLP. The entire security of ECC depends on the ability to compute a point multiplication and the inability to compute the multiplicand given the original and product points. The size of the elliptic curve determines the difficulty of the problem. The primary benefit promised by ECC is a smaller key
size, reducing storage and transmission requirements,
i.e. that an elliptic curve group could provide the
Client
Client
Client
Client Client
same level of security afforded by an RSAbased system with a large modulus and correspondingly
Fig 5: Cloud service architecture
Elliptic curve cryptography (ECC) is an approach to publickey cryptography based on the algebraic structure of elliptic curves over finite fields. Elliptic curves are also used in several integer factorization algorithms that have applications in cryptography, such as Lenstra elliptic curve factorization.
larger key e.g., a 256bit ECC public key should provide comparable security to a 3072bit RSA public key (see key sizes below). How we use hashing technique in ECC algorithm, this is done by applying some mathematical function to the key to generate a number in the range of record numbers.

Key Generation
Fig 7: Ecc vs SSE/TRSE comparison graph

Security Policy Control
For the cloud computing to go main stream, it must offer IT organizations the ability to enforce corporate policy. This policy control ranges from the simple daily policy issues (like enforcing rules to ensure strong passwords) to the more complex (like conducting security related forensics). Many cloud providers fail to offer the kind of tough policy control that many organizations require. These services are provided and maintained secure by ECC and hashing technique.

Multitenancy Trusted Computing Model
Cloud computing is a bilateral service model in which there are two entities: CSP and customers. Customers rent for software, platform or infrastructure services from CSP.
CSP can be selfinterested, untrustworthy and possibly malicious. Firstly, they are owned by CSP and organized to provide cloud services to customers, so they should be managed by CSP to satisfy the service level agreement (SLA) between CSP and customers. Secondly, as they are the platforms that customers store their data in or run their businesses on, they should supply customers with proper mechanisms to manage and secure their data or applications. In other words, they should be designed to accept and enforce the security policies from customers, which must not
be tampered by CSP or other customers. From this perspective, cloud computing should have the capability to compartmentalize each customer and CSP and support security duty separation. The key point compartmentalization and security duty separation between CSP and customers is to define clear and seamless security responsibility boundaries for CSP and customers.
From the perspective of data security, which has always been an important aspect of quality of service, Cloud Computing inevitably poses new challenging security threats for number of reasons. Firstly, traditional cryptographic primitives for the purpose of data security protection cannot 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. Considering various kinds of data for each user stored in the cloud and the demand of long term continuous assurance of their data safety, the problem of verifying correctness of data storage in the cloud becomes even more challenging.
Secondly, Cloud Computing is not just a third party data warehouse. 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. Thus this is provided efficiently by ECC.
Key generation is an important part where we have to generate both public key and private key. The sender will be encrypting the message with receivers public key and the receiver will decrypt its private key.
Now, we have to select a number d within the range of n. Using the following equation we can generate the public key
Q = d * P
d = The random number that we have selected within the range of ( 1 to n1 ). P is the point on the curve.
Q is the public key and d is the private key.

Encryption
Let m be the message that we are sending. We have to represent this message on the curve. This have in depth implementation details. All the advance research on ECC is done by a company called certicom.
Conside m has the point M on the curve E.
Randomly select k from [1 – (n1)].
Two cipher texts will be generated let it be C1 and
C2.
C1 = k*P
C2 = M + k*Q
C1 and C2 will be send.

Decryption
We have to get back the message m that was send to us,
M = C2 d * C1
M is the original message that we have send.
Proof
How does we get back the message, M = C2 d * C1
M can be represented as C2 d * C1
C2 d * C1 = (M + k * Q) d * ( k * P ) ( C2 =
M + k * Q and C1 = k * P )
= M + k * d * P d * k *P ( canceling out k * d * P )
= M ( Original Message ).


Elliptical curve Domain parameters
Apart from the curve parameters a and b, there are other parameters that must be agreed by both parties involved in secured and trusted communication using ECC. These are domain parameters. Generally the protocols implementing the ECC specify the domain parameters to be used.
For efficient implementation of ECC, it is important for the point multiplication algorithm and the unerlying field arithmetic to be efficient. There are different methods for efficient implementation point multiplication and field arithmetic suited for different hardware configurations. Implementation of ECC using projective coordinates has shown considerable improvement in efficientcy compared to the affline coordinate implementation. This improvement in efficiency is due to the elimination
of multiplicative inverse operation inpoint addition and doubling that would otherwise cost considerable processor cycles.
If the irreducible polynomial in binary field implementation is chosen to be trinomial or pentanomial the implementation of ECC on binary field implementation is chosen to be trinomial or pentanomial the implementation of ECC on binary field can be made efficient than the prime field implementation.
Conclusion
It is clear that although the use of cloud computing has rapidly increased; cloud computing security is still considered the major issue in the cloud computing environment. Customers do not want to lose their private information as a result of malicious insiders in the cloud. In addition, the loss of service availability has caused many problems for a large number of customers recently. Furthermore, data intrusion leads to many problems for the users of cloud computing. The purpose of this work is to provide security for both single and multi cloud environment. Implemeting ECC using projective coordinates has shown considerable improvement in efficiency compared to other cryptographic algorithms. It also provides a reduced key size. And hibernate concept is uised to provide persistent datas. And also the intruders can be identified by using Hashing technique. From these we propose a secure sharing scheme without any leakage.. Anyuser in the group can securely share data with others in the cloud. The encryption complexity and size of cipher text are independent. The proposed scheme guarantees the full efficiency.
Symmetric algorithm
(bit)
RSA and DH (bit)
ECC
(bit)
56
512
112
80
1024
160
112
2048
224
128
3072
256
192
7680
384
256
15360
521
Table 1. Comparison of key size

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