International Journal of Advanced Information in Arts, Science & Management Vol.1,No.1, October 2014
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Framework of Dynamic Data Access of Storage and Retrieval Processing in Cloud Environment G.J.Rathanam
[email protected] Abstract - Cloud users remotely store their data and attain high quality services from cloud for various real world applications. Quality of services provided to the end users from the cloud storage zone is the most critical issue. The conventional encryption and decryption mechanism for the privacy maintenance in cloud zone incurs additional processing time. The recent schemes were not being researched to improve the quality of services with horizontal level of privacy on cloud services. Besides, the cloud services failed to provide information to the end users with high quality of trust path (i.e., confidentiality rate). The recent cloud service implementation also reveals that the storage data access patterns through queries in the cloud did not explore effective confidentiality on information retrieval process. This work studies the problem of ensuring privacy preserving on the cloud data storage zone using Modified Shamir‟s Key Distribution based Confidentiality (MSKDC) scheme. In particular MSKDC consider the task of maintaining confidentiality of data storage and information retrieval process from cloud through query patterns. Initially, Shamir‟s Key Distribution uses the polynomial interpolation with the objective of achieving higher percentage of confidential rate on storing the client information on cloud. Keywords: Shamir‟s Key Distribution, Query Processing, Matrix Form, Confidentiality, Polynomial Interpolation, Information Retrieval, Cloud Zone 1.
INTRODUCTION
Cloud Storage is gaining higher popularity rate for the outsourcing of day-to-day data management. Confidentiality is used on accessing the set of cloud database information with high security level. Integrity monitoring of data in cloud storages (CDS) is as essential for any data center, to avoid any data corruption. Many research works have focused their concentric efforts on providing confidentiality and privacy of cloud users‟ data. Trusted Third Party Model (TTPM) [1] provided security through horizontal level of service using public key infrastructure. TTPM though ensures the authentication, integrity and confidentiality of involved data and communications but failed on maintain higher percentage of confidential rate on the horizontal level of privacy cloud services. A Trusted hardware-based DataBase (TrustedDB) [2] built and runs on actual hardware for different stages of query processing by achieving confidential rate. But it did not secure the query parsers result for generating efficient query plans. MSKDC scheme on cloud storage create a polynomial degree with secret key as a first coefficient and the remaining coefficients such as size, multiple storage information from multiple users helps in attaining the objective of improving the privacy preserving level. While prior works on ensuring vertical level of privacy, but lacks the support of horizontal level of privacy, this paper achieves both using the matrix-structural form query processing method. We first identify the complications and prospective privacy issues of
direct extensions with horizontal level of privacy from prior works and then show how to construct an elegant query efficiency scheme for the seamless integration of these two salient features in our work. MSKDC scheme ensures the query efficiency using matrix form with row (i.e.,) horizontal and column (i.e.,) vertical accesses. Experiment is conducted on factors such as quality of service on cloud data storage zone, query processing efficiency rate on dealing with cloud information and latency. Cheaper and more powerful processors, integrated “software as a service” (SaaS) framework are converting the data centers into pools of computing service on an enormous scale. Third Party Auditor (TPA) with the construction of Merkle Hash Tree (MHT) [3] was designed with the objective of providing integrity for dynamic data storage in cloud. However, multiple auditing tasks remained unaddressed. Providing trust for sensitive data was ensured in [4] through hybrid cloud computing architecture. Data coloring and software watermarking techniques was introduced in [5] provided means for multi-way authentication to the cloud users. An object centered approach was designed in [6] to enhance the control of the users that provided insight into distributed accountability for data sharing in cloud through automated logging mechanism. However, it lacked security policies. The increasing significant impact of cloud computing technology has resulted in many organizations and institutions to make a shift from IT to operate entirely or partially in the cloud environment.
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International Journal of Advanced Information in Arts, Science & Management Vol.1,No.1, October 2014 DeepSky [7] provided means for data integrity and confidentiality of information stored in the cloud through Quorum protocols. However, the maintenance cost increased with the increase in the cloud users‟ data. Secure cloud maintenance was addressed in [8] by extending the infrastructure of cloud architecture through privilege levels. Though security and confidentiality was addressed, validation of confidentiality was not ensured. A Secure and Privacy preserving Keyword Searching (SPKS) scheme was introduced in [9] that provided mechanisms for user data and user query privacy through randomized time polynomial algorithm. With the objective of providing access control and key sharing a method was introduced in [10] using Chinese Remainder Theorem. Although there are many complications faced by researchers, it is well believed that providing high confidentiality can be of vital importance to the practical application of quality of service for outsourcing services. In view of the key role of providing confidentiality and ensuring privacy, we present an efficient framework for the seamless integration of these two components in this work. Our contribution can be summarized as follows: a. Multi levels (horizontal and vertical) of privacy requirements in Cloud Computing initiated to develop a proposal method, matrix-structural form query processing for supporting both horizontal and vertical level of privacy, especially to provide quality of service. b. Extend proposal scheme to support privacy preserving on the cloud storage zone using Modified Shamir‟s Key Distribution based Confidentiality (MSKDC). In particular, MSKDC achieves confidentiality of data storage and information retrieval process from cloud through query patterns. c. Prove the confidentiality of MSKDC proposed scheme using polynomial interpolation and justify the performance with empirical implementation and comparisons with the state of the art works. The remainder of this paper is organized as follows. Section 2 reviews related work on maintaining confidentiality and privacy preserving in cloud. Section 3 proposes our Modified Shamir‟s Key Distribution based Confidentiality (MSKDC) scheme. Section 4 presents the experimental setup and an empirical evaluation is presented in Section 5. Section 6 concludes with the concluding remarks.
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RELATED WORKS
One of the rapid growing internet based technology is cloud computing that provides the users to use the services with the aid of huge resources from the cloud environment without installation of any software. However, confidentiality being the key issues was addressed in [11] by adapting encryption techniques. But, privacy remained the major concern that had to be addressed. An effective TPA was introduced in [12] with the objective of providing privacy preserving for the storage of data in cloud through MAC-based solution. Another proxy encryption scheme introduced in [13] provided an insight into confidentiality and data forwarding through more secured cryptographic keys. Single round access privacy on cloud was designed in [14] on the purview of restricting attacks from the attackers minimizing the latency. The cloud computing environment works on the principle that, task performed on the client side can be shifted to certain unseen resources on the Internet. However, the Internet is not an ideal location where the clients have complete control over it. A novel data security model was designed in [15] based on several category layers to ensure security. Another mechanism to improve security called as homomorphic encryption mechanism was introduced in [16] that efficiently executed the operations by encrypting the data but without efficient decryption. But, security with hardware aspects was not covered. Protecting the data from both software and hardware aspects were introduced in [17] by constructing trust between cloud providers and cloud users. With the increasing popularity of the cloud services, securing the data in cloud environments has become the most critical issues. A new algorithm, Effective Privacy Preserving Algorithm (EPPA) [18] was designed to increase the confidentiality of user data in cloud environment. A Secure Cloud Storage System (SCSS) [19] was designed with the objective of providing availability of the data in cloud and security of data. Another method in [20] addressed the maintaining confidentiality of data in cloud through effective service providers. 3.
MODIFIED SHAMIR’S KEY DISTRIBUTION BASED CONFIDENTIALITY ON CLOUD DATA STORAGE AND QUERY PROCESSING
In this section, we formulate the problem of Modified Shamir‟s Key Distribution based Confidentiality (MSKDC) scheme for maintaining high confidentiality and providing privacy to the cloud users. This section provides the necessary
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International Journal of Advanced Information in Arts, Science & Management Vol.1,No.1, October 2014 background regarding confidentiality maintenance and the proposed method, Modified Shamir‟s Key Distribution based Confidentiality scheme. The two components involved in the design of SDKC scheme are (i) cloud storage data confidentiality and (ii) privacy preservation based on query processing. Privacy level maintenance on cloud data storage and query processing is the main objective in the proposed work. The cloud data storage in our model stores the data and maintains the security using the Shamir‟s Key Distribution model. Maintaining higher confidentiality level is the serious concern in cloud which is addressed through Shamir‟s Key Distribution model. Data confidentiality is one of the most significant security (i.e., privacy) concerns that are achieved in our proposed work that helps in safeguarding the client‟s information from the attackers. The steps involved in the design of confidentiality via Shamir‟s Key Distribution are shown in Figure 1.
Figure 1 Modified Shamir‟s Key Distribution based Confidentiality processing Shamir‟s Key Distribution achieves higher percentage of confidentiality by residing in the cloud data. The MSKDC scheme uses polynomial interpolation and matrix-structural form to provide data storage confidentiality on storage and data storage confidentiality on query processing respectively. MSKDC scheme create polynomial degree coefficients to improve the security (i.e., privacy preserving) level. In the matrix-structural representation, the horizontal and vertical form is used to easily access the pattern and fetch the result for the user query from cloud infrastructure. The horizontal (i.e., row) form information are used to improve the quality of services on processing the query. The vertical (i.e., column) form handles different types of queries among varying group of clients simultaneously to fetch the accurate query result with minimal processing time. The proposed Modified Shamir‟s Key Distribution based
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Confidentiality (MSKDC) architecture is shown in Figure 2. Figure 2 shows the proposed Modified Shamir‟s Key Distribution based Confidentiality architecture for different cloud users. Cloud computing is a model for enabling convenience ondemand network access for cloud users. Initially, the user requested information for cloud data storage is carried out using polynomial interpolation. MSKDC scheme create a polynomial of degree with the secret key as the first coefficient and the remaining coefficients to improve the privacy preserving level on cloud infrastructure. The „k‟ is the key hidden from the public cloud users that helps in improving the confidentiality rate. Shamir‟s Key Distribution supports batch auditing where multiple user requests for data auditing is placed concurrently with the objective of providing higher confidentiality rate.
Figure 2 Proposed Modified Shamir‟s Key Distribution based Confidentiality architecture MSKDC scheme handles query processing using the matrix-structure form. The horizontal and vertical level of privacy cloud data service query processing uses the matrix form. MSKDC scheme ensures query efficiency using matrix row (i.e.,) horizontal and column (i.e.,) vertical accesses. As a result, MSKDC scheme ensures high confidentiality on cloud data storage query processing. The horizontal row is used to improve the privacy preserving whereas the vertical column access multiple user queries. 3.1
Cloud Storage Data Confidentiality
In this section, the first component cloud storage data confidentiality with the objective of achieving higher confidentiality is discussed in detail. The design of cloud storage data confidentiality using SDKC scheme proceeds in such a way that if a client wants to store the information in the cloud, a distributed key is send to the cloud server. The storage of information on cloud server with user‟s
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International Journal of Advanced Information in Arts, Science & Management Vol.1,No.1, October 2014 authentication supports for effective data forwarding. Once the system has been designed, the next step is to convert the designed form into the actual implementation in MSKDC scheme using the polynomial interpolation. 3.1.1 Polynomial Interpolation Modified Shamir‟s Key Distribution based Confidentiality on cloud data storage uses the polynomial interpolation points. The purpose of using polynomial is to obtain the different curves (i.e., sizes) of the user information in the cloud server. The cloud storage zone uses the lookup table and interpolates it between those information points of different users. Let us assume a set of information points „ ‟ obtain from multiple cloud users „ ‟ to store in the cloud with the polynomial property described as given below, (1)
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confidentiality rate. the information points after applying the polynomial interpolation form. The Shamir‟s key distribution is used on the information point‟s storage to improve the confidentiality level. Algorithm 1 gives the briefing about the cloud data storage for MSKDC scheme. In MSKDC cloud infrastructure, the data storage contains the entities such as cloud user and cloud service provider. With the application of Shamir‟s key distribution, cloud user stores large amount of data in the cloud server with lesser time taken for storage. The look up table is supported with array indexing operation to store the information points in the cloud infrastructure. The lookup table in MSKDC scheme is used extensively in processing the user query based on the cloud storage information and it is described briefly in section 3.2.1. The time being saved in terms of processing is the significant part in the proposed method. 3.2 Privacy preserving on Query processing
The polynomial property with different information points is then to be stored in the cloud infrastructure. With the application of Polynomial interpolation in MSKDC scheme even the complicated information is approximated and stored in the cloud infrastructure. The results of the cloud storage using the polynomial interpolation are obtained significantly with minimum processing time. The construction of the interpolation for all the cloud users using linear information is described as,
(2)
The user‟s information from points to points are stored in the cloud zone. The coefficient is used to embed the Shamir distributed key with the information points to improve the confidentiality result. MSKDC scheme on cloud storage create a polynomial degree with secret key as a first coefficient and the remaining coefficients with size. Multiple storage information from multiple users is also provided with high privacy rate in proposed method. Multiple users‟ information is embedded with the polynomial property. Shamir key is the hidden key embedded with the cloud storage information and it is shown as, (3) The Shamir key is embedded with the information points by the user to improve the
In this section, the second component privacy preserving on query processing is designed with the objective of increasing the confidentiality rate on query processing. The results of the query retrieval process in MSKDC scheme retrieve the result from the cloud infrastructure by using the look up table information. The original information are retrieved and provided to the authenticated users, provided they submit the accurate private key to the cloud server using the matrix-structure form. The resulting symbols and the coefficients are checked on the cloud zone to evaluate the privacy level measure. The cloud server heavily loaded with the multiple users is easily processed using this matrix-structure form. MSKDC scheme is used to extract the result for the range of the user queries with high privacy level. The tuple updates are performed in the look up table using the insertion and deletion operation. The user „ ‟ collects the query result from the cloud zone using the matrix-structure query processing or matrix-structure form which is detailed in the following section. 3.2.1 Matrix-Structure Form Matrix structure form in MSKDC scheme involves the information retrieval in proposed work with fast access of data. The matrix-structure form ensures query efficiency using matrix form with row (i.e.,) horizontal and column (i.e.,) vertical accesses. The Figure 3 given below shows the matrix-structure form that contains certain user information.
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International Journal of Advanced Information in Arts, Science & Management Vol.1,No.1, October 2014 The matrix-structure form consists of the information points and also the query terms with higher confidentiality rate using the MSKDC scheme. Each row with the MSKDC scheme consists of the user‟s information points whereas each column vector defines the query terms requested form the client side. MSKDC scheme ensures query efficiency using matrix-structure form with row (i.e.,) horizontal and column (i.e.,) vertical accesses. The query processing is improved by privacy rate in proposed method using the formulation as given below, (4)
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compared, which are Trusted Third Party model (TTPM) [1] tasked and Trusted Hardware based Database with Privacy and Data Confidentiality (TrustedDB) [2]. 5.1 Impact of confidentiality level The confidentiality level using MSKDC scheme is the amount of confidentiality provided by the cloud users to the cloud using Shamir‟s key distribution model through polynomial interpolation points. Higher the level of confidentiality more effective the scheme is said to be. Table 1 tabulation for confidentiality level
The user embeds the distributed key with the query to the cloud server for fetching the result from the stored information. The stored information points are processed and produce higher confidentiality results from the cloud infrastructure. This proposed MSKDC algorithmic step is efficient and strong in attaining the confidentiality while storing and retrieving the result through query processing. 4.
EXPERIMENTAL EVALUATION
Modified Shamir‟s Key Distribution based Confidentiality (MSKDC) scheme is developed to improve the privacy level using the Amazon Simple Storage Service (Amazon S3) dataset. This dataset based on confidentiality maintenance is experimented using the JAVA coding. The Amazon S3 is a reliable, fast, inexpensive data storage infrastructure for efficient query processing. Amazon S3 stores data objects redundantly on multiple devices diagonally on multiple services and permit simultaneous read and write access. The read, write access to these data objects helps to easily recover the needed information. Amazon S3 based storage of files are discussed and used in our experimental discussions to identify the result percentage. MSKDC Scheme compares the existing work with the Trusted Third Party model (TTPM) [1] tasked with assuring specific security characteristics and A Trusted Hardware based Database with Privacy and Data Confidentiality (TrustedDB) [2]. Experiment is conducted on factors such as confidentiality level, quality of service on cloud data storage zone, query processing efficiency rate on dealing with cloud information. 5.
RESULTS ANLAYSIS OF MSKDC SCHEME
To evaluate the confidentiality and privacy performance with Modified Shamir‟s Key Distribution based Confidentiality (MSKDC) scheme, two well-known privacy schemes are
No. of Users (U) 3 6 9 12 15 18 21
Confidentiality level (%) MSKDC TTPM TrustedDB 58.35 61.45 68.33 62.89 71.35 69.88 80.25
46.32 49.42 56.30 50.86 59.32 57.85 68.22
38.28 41.38 48.26 42.82 51.28 49.81 60.182
The MSKDC scheme is analyzed against Trusted Third Party model (TTPM) [1] and Trusted Hardware based Database with Privacy and Data Confidentiality (TrustedDB) [2]. Each method has its own respective confidentiality level. The existing and proposed result is analyzed by providing several features in JAVA coded with cloudsim platform using the values provided in the table and graph points. Table 1 tabulates the confidentiality level with respect to the number of users who issued queries to the cloud and comparison of our scheme MSKDC is made with TTPM and TrustedDB.
Figure 4 Measure of confidentiality level A comparative analysis for confidentiality level with respect to different number of users is performed with the existing TTPM and Trusted DB is shown in Figure 4. The increasing users in the range of 3 to 21 are considered for experimental purpose for confidentiality for data storage and information
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International Journal of Advanced Information in Arts, Science & Management Vol.1,No.1, October 2014 retrieval is shown in Figure 4. As illustrated in figure, comparatively while considering higher number of users, the confidentiality level also increases, though betterment achieved using the proposed scheme MSKDC. We consider the experimental process for a subset of 21 users for experimental purpose, the simulation setup considered only 488 Hz to 1MHz. The measurement of confidentiality level is comparatively improved using the MSKDC scheme when compared to two other methods [1] [2]. This improvement in confidentiality level is because of the application of Shamir‟s Key Distribution model. With the application of Shamir‟s Key Distribution model, a distributed key is send to the cloud server whenever the cloud user wants to store certain amount of data. The Modified Shamir‟s Key Distribution based Confidentiality with polynomial interpolation points uses the look up table to interpolate between the information points of different users with polynomial property resulting in the increased confidentiality level by 16 – 27 % compared to TTPM. The interpolation with linear information and coefficient embedded using Shamir distributed key further helps to improve the confidentiality level by 28 – 47 % compared to TrustedDB. 5.2 Impact of quality of service on cloud data storage zone The quality of service on cloud data storage zone using MSKDC scheme is the amount of privacy handled by the cloud. The quality of service in terms of privacy using MSKDC scheme is the product of horizontal level of privacy and vertical level of privacy provided to the cloud users by the cloud. It is measured in terms of percentage (%). (5) Table 2 Tabulation for quality of service No. of Users(U) 3 6 9 12 15 18 21
Quality of Service (%) MSKDC TTPM TrustedDB 49.72 44.71 36.67 51.33 46.32 38.28 58.39 53.38 45.34 55.77 50.76 42.72 61.35 56.34 48.30 60.42 55.41 47.37 65.99 60.98 52.94
The quality of service on cloud data storage zone of our scheme MSKDC is presented in table 2. It is easy to find that the quality of service on cloud data storage zone for maintaining data confidentiality
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and information retrieval is increased using MSKDC scheme than the state-of-art methods. The second evaluation metric considered for evaluating the effectiveness of the scheme MSKDC is quality of service with respect to the number of users in cloud zone. An elaborate comparison is made with the existing two state-of-the-art methods. From the data values of this figure, MSKDC scheme deviates from TTPM [1] and TrustedDB method by more than 15 percent while performing confidentiality and ensuring privacy.
Figure 5 Measure of Quality of Service The quality of service on cloud data storage zone is improved by the integration of horizontal and vertical level of privacy. The horizontal level of privacy achieved through user polynomial property information whereas the vertical level of privacy is ensured by the accessing of information through queries. This integrated horizontal and vertical privacy helps in improving the quality of service by 7 – 10 % and 19 – 26 % compared to TTPM and TrustedDB respectively. 5.3 Impact of query processing efficiency The query processing efficiency rate on dealing with cloud information handles the number of successful queries handled by the cloud. Table 3 Tabulation for query processing efficiency No. of Queries 5 10 15 20 25 30 35
Query Processing Efficiency (%) MSKDC TTPM TrustedDB 0.6 0.55 0.48 0.7 0.62 0.52 0.86 0.78 0.71 0.8 0.79 0.73 0.84 0.81 0.78 0.93 0.83 0.80 0.91 0.85 0.81
Table 3 summarizes the three schemes that we experimented for data confidentiality and
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International Journal of Advanced Information in Arts, Science & Management Vol.1,No.1, October 2014 information retrieval using Amazon Simple Storage Service (Amazon S3) dataset. Figure 6 shows the query processing efficiency on dealing with cloud information with respect to 5 to 35 queries for experimental purposes. As depicted in the figure with the increase in the number of queries, the query processing efficiency is also increased. But when compared to the state-ofthe-art method, the query processing efficiency is increased in the proposed scheme MSKDC. The query processing efficiency improved owing to the fact that the proposed scheme uses matrix-structure form.
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Then, based on this measure, we proposed a matrixstructural form which reflects the linear information for effective confidentiality according to the horizontal and vertical data accesses. In addition, we also obtained the hidden key to be embedded with the cloud storage information by the user using the Shamir‟s key distribution model to improve the quality of service for multiple users. Through the experiments using Amazon Simple Storage Service (Amazon S3) dataset, we observed that our framework increased the query processing efficiency on dealing with cloud information compared to existing methods. In addition, our polynomial property effectively improved the polynomial interpolation rate and even significantly reduced the processing time. REFERENCES [1] Dimitrios Zissis., Dimitrios Lekkas., “Addressing cloud computing security issues,” Future Generation Computer Systems., Elsevier Journal., 2012
Figure 6 Measure of query processing efficiency With the application of matrix-structure form in MSKDC scheme, query efficiency is maintained with horizontal and vertical accesses improving the query processing efficiency of the cloud users by 3 – 11 when compared to TTPM. Moreover, each row vector in the MSKDC scheme includes the user‟s information points and each column vector defines the query terms requested form the client side. As a result by applying both, the query processing efficiency rate on dealing with cloud information is drastically increased in MSKDC by 8 – 25 % compared to Trusted DB.
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CONCLUSION
In this work, an effective Modified Shamir‟s Key Distribution based Confidentiality on the cloud zone is studied to maintain high confidentiality on cloud data storage and query processing. The goal of our scheme is to ensure privacy on the cloud data storage zone which significantly contributes to the relevance and in maintaining the confidentiality of data storage and information retrieval from cloud. To do this, we first devised a polynomial interpolation scheme to provide data storage confidentiality on storage and to determine the present state and whole history of cloud user query request to access information to improve the confidentiality level.
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