Ensuring Data Storage Security in Cloud Computing

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ABSTRACT

Cloud computing has been envisioned as the next-generation architecture of IT enterprise. In contrast to traditional solutions, where the IT services are under proper physical, logical and personnel controls, cloud computing moves the application software and databases to the large data centers, where the management of the data and services may not be fully trustworthy. This unique attribute, however, poses many new security challenges which have not been well understood. In this article, we focus on cloud data storage security, which has always been an important aspect of quality of service. To ensure the correctness of users’ data in the cloud, we propose an effective and flexible distributed scheme with two salient features, opposing to its predecessors. By utilizing the homo-morphic token with distributed verification of erasure-coded data, our scheme achieves the integration of storage correctness insurance and data error localization, i.e., the identification of misbehaving server (s). Unlike most prior works, the new scheme further supports secure and efficient dynamic operations on data blocks, including: data update, delete and append. Extensive security and performance analysis shows that the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.

System Architecture:

Existing System:

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.

1 . Firstly, 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. 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.

2 . 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.

These techniques, while can be useful to ensure the storage correctness without having users possessing data, can not address all the security threats in cloud data storage, since they are all focusing on single server scenario and most of them do not consider dynamic data operations. As an complementary approach, researchers have also proposed distributed protocols  for ensuring storage correctness across multiple servers or peers. Again, none of these distributed schemes is aware of dynamic data operations. As a result, their applicability in cloud data storage can be drastically limited.

Proposed System:

In this paper, 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 erasure correcting code in the file distribution preparation to provide redundancies and guarantee the data dependability. This construction drastically reduces the communication and storage overhead as compared to the traditional replication-based file distribution techniques. By utilizing the homo-morphic token with distributed verification of erasure-coded data, our scheme achieves the storage correctness insurance as well as data error localization: whenever data corruption has been detected during the storage correctness verification, our scheme can almost guarantee the simultaneous localization of data errors, i.e., the identification of the misbehaving server(s).

1. Compared to many of its predecessors, which only provide binary results about the storage state across the distributed servers, the challenge-response protocol in our work further provides the localization of data error.

2. 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.

3. Extensive security and performance analysis shows that the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.

System Requirements:

Hardware Requirements:

•         System                        : Pentium IV 2.4 GHz.

•         Hard Disk                   : 40 GB.

•         Floppy Drive             : 1.44 Mb.

•         Monitor                       : 15 VGA Colour.

•         Mouse                          : Logitech.

•         Ram                             : 512 Mb.

Software Requirements:

•         Operating system        : – Windows XP.

•         Coding Language         : -JAVA,Swing,RMI,J2me(WirelessToolkit)

•         Tool Used                        : – Eclipse 3.3

Fuzzy Keyword Search over Encrypted Data in Cloud Computing

To get source code, video, ppt, documentation of this project please mail us:
info@ocularsystems.in

or visit us:
http://blog.ocularsystems.in/blog

Abstract:

                As Cloud Computing becomes prevalent, more and more sensitive information are being centralized into the cloud. Although traditional searchable encryption schemes allow a user to securely search over encrypted data through keywords and selectively retrieve files of interest, these techniques support only exact keyword search. In this paper, for the first time we formalize and solve the problem of effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy. Fuzzy keyword search greatly enhances system usability by returning the matching files when users’ searching inputs exactly match the predefined keywords or the closest possible matching files based on keyword similarity semantics, when exact match fails. In our solution, we exploit edit distance to quantify keywords similarity and develop two advanced techniques on constructing fuzzy keyword sets, which achieve optimized storage and representation overheads. We further propose a brand new symbol-based trie-traverse searching scheme, where a multi-way tree structure is built up using symbols transformed from the resulted fuzzy keyword sets. Through rigorous security analysis, we show that our proposed solution is secure and privacy-preserving, while correctly realizing the goal of fuzzy keyword search. Extensive experimental results demonstrate the efficiency of the proposed solution.

Algorithm / Technique used:

                         String Matching Algorithm

Algorithm Description:

    The approximate string matching algorithms among them can be classified into two categories: on-line and off-line. The on-line techniques, performing search without an index, are unacceptable for their low search efficiency, while the off-line approach, utilizing indexing techniques, makes it dramatically faster. A variety of indexing algorithms, such as suffix trees, metric trees and q-gram methods, have been presented. At the first glance, it seems possible for one to directly apply these string matching algorithms to the context of searchable encryption by computing the trapdoors on a character base within an alphabet. However, this trivial construction suffers from the dictionary and statistics attacks and fails to achieve the search privacy. An instance M of the data type string-matching is an object maintaining a pattern and a string. It provides a collection of different algorithms for computation of the exact string matching problem. Each function computes a list of all starting positions of occurrences of the pattern in the string.

System Architecture:

Existing System:

This straightforward approach apparently provides fuzzy keyword search over the encrypted files while achieving search privacy using the technique of secure trapdoors. However, this approaches serious efficiency disadvantages. The simple enumeration method in constructing fuzzy key-word sets would introduce large storage complexities, which greatly affect the usability.

For example, the following is the listing variants after a substitution operation on the first character of keyword

                       CASTLE:  {AASTLE, BASTLE, DASTLE, YASTLE, ZASTLE}.

Proposed System:

Main Modules:

            1. Wildcard – Based Technique

            2. Gram – Based Technique

            3. Symbol – Based Trie – traverse Search Scheme

1. Wildcard – Based Technique:

       In the above straightforward approach, all the variants of the keywords have to be listed even if an operation is performed at the same position. Based on the above observation, we proposed to use an wildcard to denote edit operations at the same position. The wildcard-based fuzzy set edits distance to solve the problems.

For example, for the keyword CASTLE with the pre-set edit distance 1, its wildcard based fuzzy keyword set can be constructed as

SCASTLE, 1 = {CASTLE, *CASTLE,*ASTLE, C*ASTLE, C*STLE, CASTL*E, CASTL*, CASTLE*}.

Edit Distance:

1. Substitution
2. Deletion
3. Insertion

a)      Substitution :  changing one character to another in a  word;

b)     Deletion :  deleting one character from a word;

c)      Insertion:  inserting a single character into a word.

2. Gram – Based Technique:

Another efficient technique for constructing fuzzy set is based on grams. The gram of a string is a substring that can be used as a signature for efficient approximate search. While gram has been widely used for constructing inverted list for approximate string search, we use gram for the matching purpose. We propose to utilize the fact that any primitive edit operation will affect at most one specific character of the keyword, leaving all the remaining characters untouched. In other words, the relative order of the remaining characters after the primitive operations is always kept the same as it is before the operations.

For example, the gram-based fuzzy set SCASTLE, 1 for keyword CASTLE can be constructed as

              {CASTLE, CSTLE, CATLE, CASLE, CASTE, CASTL, ASTLE}.

3. Symbol – Based Trie – traverse Search Scheme

             To enhance the search efficiency, we now propose a symbol-based trie-traverse search scheme, where a multi-way tree is constructed for storing the fuzzy keyword set over a finite symbol set. The key idea behind this construction is that all trapdoors sharing a common prefix may have common nodes. The root is associated with an empty set and the symbols in a trapdoor can be recovered in a search from the root to the leaf that ends the trapdoor. All fuzzy words in the trie can be found by a depth-first search.

In this section, we consider a natural extension from the previous single-user setting to multi-user setting, where a data owner stores a file collection on the cloud server and allows an arbitrary group of users to search over his file collection.

System Requirements:

Hardware Requirements:

•         System                     : Pentium IV 2.4 GHz.

•         Hard Disk                : 40 GB.

•         Floppy Drive          : 1.44 Mb.

•         Monitor                   : 15 VGA Colour.

•         Mouse                      : Logitech.

•         Ram                         : 512 Mb.

Software Requirements:

•         Operating system      : – Windows XP.

•         Coding Language       : DOT NET

•         Data Base                     : SQL Server 2005

Conclusion:

1. In this paper, for the first time we formalize and solve the problem of supporting efficient yet privacy-preserving fuzzy search for achieving effective utilization of remotely stored encrypted data in Cloud Computing.

2. We design two advanced techniques (i.e., wildcard-based and gram- based techniques) to construct the storage-efficient fuzzy keyword sets by exploiting two significant observations on the similarity metric of edit distance.

3. Based on the constructed fuzzy keyword sets, we further propose a brand new symbol-based trie-traverse searching scheme, where a multi-way tree structure is built up using symbols transformed from the resulted fuzzy keyword sets.

4. Through rigorous security analysis, we show that our proposed solution is secure and privacy- preserving, while correctly realizing the goal of fuzzy keyword search. Extensive experimental results demonstrate the efficiency of our solution.