Periodic Auditing of Data in Cloud Using Random Bits

INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY VOLUME 5 ISSUE 2 – MAY 2015 - ISSN: 2349 - 9303

Periodic Auditing of Data in Cloud Using Random Bits K.Devika 1, 1

K.S.R Institute for Engineering and Technology, Computer Science and Engineering Email: devikannandk@gmail.com

M.Jawahar2 2

K.S.R Institute for Engineering and Technology, Computer Science and Engineering Email: devikannandk@gmail.com

Abstract─ Cloud storage is a service that moves user‟s data into large data centers. Here datas are remotely located, maintained, managed and backed up through internet. Cloud provides the way for check the integrity of user‟s data if he can‟t access the data physically. In this paper we provide the proof of retrievability (POR) scheme to ensure the data integrity in cloud based on SLA (service level agreement). In addition we provide a dynamic audit service for verifying the integrity of outsourced and untrusted storage of data by using method based on probabilistic query and periodic verification for improving the performance of audit services.

Index Terms─ Cloud Storage, Data Integrity, POR, Dynamic Audit, Audit Service.

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The cloud storage archives was prevented from misrepresenting or modifying the data stored at cloud without the consent of the data owner by using frequent checks of verification systems on the storage archives.

The frequent checks must allow the data owner to quickly, efficiently, securely and frequently verify that the cloud archive is not cheating as that the storage archive might delete some of the data or may modify some of the data of the owner.

INTRODUCTION

The owner (client) of the data moves its data to a third party cloud storage server which is supposed to presumably for a fee - faithfully store the data with it and provide it back to the owner whenever required.

Whenever additional data is created as data generation is far outpacing data storage it proves costly for small firms to frequently update their hardware and maintaining the storages can be a difficult task. By reducing the costs of storage, maintenance and personnel, storage outsourcing of data to cloud storage helps such firms.

By keeping multiple copies of the data thereby reducing the chance of losing data by hardware failures, it can also assure a reliable storage of important data on cloud. It provides a reliable solution to the problem of avoiding local storage of data. In this paper implementing a protocol for obtaining a proof of data possession in the cloud referred to as Proof of retrievability (POR). The data that is stored by a user at remote data storage in the cloud (called cloud storage archives or simply archives) is not modified by the archive and thereby the integrity of the data is assured by using this protocol to obtain and verify a proof of data.

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RELATED WORK

For the Purpose of developing proofs for data possession at untrusted cloud storage servers, we are often limited by the resources at the cloud server as well as at the client. Accessing the entire file can be expensive in I/O costs to the storage server, while that the data sizes are large and are stored at remote servers and transmitting the file across the network to the client can consume heavy bandwidths.

Storing of user data in the cloud need to be extensively investigated for making it a reliable solution to the problem of avoiding local storage of data, and despite its advantages has many interesting security concerns. Whenever additional data is created the data generation is far outpacing data storage and it proves costly for small firms to frequently update their

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INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY VOLUME 5 ISSUE 2 – MAY 2015 - ISSN: 2349 - 9303 hardware and also can be a difficult task for maintaining the storages. It transmitting the file across the network to the client for that it can consume heavy bandwidths.

The owner of the data may be a small device, like a PDA (personal digital assist) or a mobile phone, The problem is further complicated by the fact which have limited power of CPU and battery and have limited communication bandwidth.

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archive prove the data integrity of users data by response to the verifiers challenge.

Our scheme was developed to reduce the computational and storage overhead of the client as well as to minimize the computational overhead of the cloud storage server and also minimized the size of the proof of data integrity so as to reduce the network bandwidth consumption. Compared to all other schemes, the storage at the client is very much minimal hence proves advantage to thin clients. Generally consumes a large computational power has to be consumed for the operation of encryption of data. Thereby In this scheme saving on the computational time of the client, the encrypting process is very much limited to only a fraction of the whole data. In many of the schemes the archive requires to generate the proof of data integrity to perform tasks that need a lot of computational power.

But in our scheme the archive just need to fetch and send few bits of data to the client.

ARCHITECTURE

One of the important concerns that need to be addressed is to assure the customer, correctness of his data in the cloud. The cloud provides a way to check if the integrity of the user data is maintained or is compromised while the data is physically not accessible to the user. In this paper we provide a scheme which gives a proof of data integrity in the cloud which the customer can employ to check the correctness of his data in the cloud and this proof can be agreed by both the customer and the cloud also this proof can be incorporated in the Service level agreement (SLA).

It is important to note that our proof of data integrity protocol just checks the integrity of data means if the data has been illegally modified or deleted.Apart from reduction in storage costs data outsourcing to the cloud also helps in reducing the maintenance .this scheme is used for Avoiding local storage of data. By reducing the costs of storage, maintenance and personnel, it can reduces the chance of losing data by hardware failures.

At the client, cloud storing its data file F and process it and also create suitable meta data for the file which is used in the verification of the data integrity at the cloud storage. The client queries the cloud storage for suitable replies based on which it concludes the integrity of its data stored in the client while checking for data integrity. The verifier needs to store only a single cryptographic key - irrespective of the size of the data file F- and two functions which generate a random sequence on using the data integrity protocol although the verifier does not store any data with it.

3.1 Dynamic Auditing of Data in Cloud We provide a dynamic audit service for verifying the integrity of outsourced and untrusted storage of data by using method based on probabilistic query and periodic verification for improving the performance of audit services. Our audit service are comprised of three processes for realize these functions.

i) Tag Generation: To preprocess a file the client (DO) uses a secret key sk . The file consists of a collection of n blocks.

Fig 2.Tag generation for audit file

DO generates a set of Public Verification Parameters (PVPs) and IHT then transmits the file and some verification tags to CSP(Cloud Service Provider), that are stored in TPA(Third Party Auditor), and may delete its local copy ( Fig. 2). ii) Periodic Sampling Audit: TPA issues a “random sampling� challenges to audit the integrity and availability of the outsourced data in terms of verification information (involving PVP and IHT(Index Hash Table)) stored in TPA By using an interactive proof protocol of retrievability (Fig. 3).

Figure 1 Architecture

The file to be pre-processed by the verifier before storing it at the archive and appends some meta data to the file and stores at the archive. Verifiers can verify the integrity of their data using the meta data and they can challenge the archive by using the meta data. The

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INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY VOLUME 5 ISSUE 2 – MAY 2015 - ISSN: 2349 - 9303 performance. An instance for this framework. An outsourced file F is split into n blocks{m1,m2…,mn} and each block mi is split into s sectors {mi,1,mi,2…,mi,s}the fragment framework consists of n block-tag pair where σi is a signature tag of a block m i generated by some secrets τ = τ1,τ2,…,τs. In the verification protocol, we can use tags and corresponding data to construct a response in terms of the TPA‟s challenges such that this response can be verified without raw data. A secure tag is that tag if a tag is unforgeable by anyone except the original signer, we call it. Finally, encrypted secrets (called as PVP) are in TTP and the block-tag pairs are stored in CSP. Storage of signature tags can be reduced with the increase of s although this fragment structure is simple and straightforward, but the file is split into n×s sectors and each block (s sectors) corresponds to a tag. Hence the extra storage for tags and improving the audit performance is reduced by this structure. There exist several schemes for the convergence of s blocks to generate a secure signature tag, e.g., MAC-based, ECC, or RSA schemes [6], [7]. The features of scalability, performance, and security are built from collision resistance hash functions and random oracle model support.

Fig 3. Periodic sampling audit

iii) Audit for Dynamic Operations: An AA(Authorized Applications) holds a DO‟s secret key sk. It can manipulate the outsourced data and update the associated IHT stored in TPA. By using the privacy of sk and the checking algorithm, AA ensure that the storage server cannot cheat the AAs and forge the valid audit records (Fig. 4).

B.Periodic Sampling Audit: While still achieves an effective detection of misbehaviors to realize the anomaly detection in a timely manner, a probabilistic audit on sampling checking is preferable as well as to rationally allocate resources. The fragment structure provides Probabilistic Audit as well: Given a randomly chosen challenge (or query) Q={(i,vi)}iЄI where I is a subset of the block indices and vi is a random coefficient, an efficient algorithm is used to produce a constant-size response (µ 1,µ2,µs,σ′) where µi comes from all {mk,i,vk}kЄI and σ′ is from all {σk,vk}kЄi.

Generally, this algorithm minimizes network communication costs and relies on homomorphic properties to aggregate data and tags into a constant-size response. We propose a periodic sampling approach to audit outsourced data, since the single sampling checking may overlook a small number of data abnormalities which is named as Periodic Sampling Audit. Table1 IHT with random values with this approach,

Fig .4 Dynamic data operations and audit

The AAs be a cloud application services inside clouds for various application purposes, must be specifically authorized by DOs for manipulating outsourced data. Any unauthorized modifications for data will be detected in audit processes or verification processes by AA that must present authentication information for TPA. CSP is trusted to guarantee the security of stored data based on this kind of strong authorization-verification mechanism. Therefore, TPA should be constructed in clouds and maintained by a CSP. TPA must be secure enough to resist mischievous attacks, and it should be strictly controlled to prevent unauthorized accesses even for internal members in clouds to ensure the trust and security. TPA in clouds should be mandated by a Trusted Third Party (TTP).

The TTP mechanism improves the performance of an audit service, also provides the DO with a maximum access transparency that stated DOs are entitled to utilize the audit service without additional costs. These processes involve some procedures: KeyGen, TagGen, Update, Delete, Insert algorithms, and an Interactive Proof Protocol of Retrievability.

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OUR CONTRIBUTION

A. Fragment Structure and Secure Tags: A general fragment structure for outsourced storages is introduced to maximize the storage efficiency and audit

Table 1 Index Hash Table

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INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY VOLUME 5 ISSUE 2 – MAY 2015 - ISSN: 2349 - 9303 A TPA merely needs to access small portions of files to perform audit in each activity and the audit activities are efficiently scheduled in an audit period.

Therefore, this method can reduce the sampling numbers in each audit and detect exceptions periodically.

all tags and the IHT should be renewed and reorganized periodically obviously, to improve the efficiency of updating the IHT we can replace the sequent lists with dynamically linked.

5 C.Index-Hash Table: We introduce a simple IHT to support dynamic data operations and to record the changes of file blocks and generate the hash value of each block in the verification process. File block allocation table in file systems is similar to that of the structure of our IHT. Generally, the IHT χ consists of block number, serial number, version number, and random integer (Table 1). To prevent the forgery of data blocks and tags we must assure all records in the IHT differ from one another. In addition to recording data changes, each record χi in the table is used to generate a unique hash value, which is used for the construction of a signature tag σi by the secret key sk. The relationship must be cryptographically secured between χi and σi, and we make use of it to design our verification protocol. To monitor the behavior of an untrusted CSP, the IHT provides a higher assurance and provide valuable evidence to computer forensics, due to the reason that anyone else cannot forge the valid χi (in TPA) and σi (in CSP) without the secret key sk.

CONCLUSIONS

In this paper, the outsourced data to be checked for ensuring the integrity of clients data. In addition, for untrusted and outsourced storages we presented a construction of dynamic audit services which is used to perform the dynamic operations done by the authorized user on data stored in cloud. We also enhance the performance of TPAs and storage service providers by presenting an efficient method for periodic sampling audit. Thus the scheme has a minimal constant amount of overhead, which minimizes communication and computation costs.

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