International Journal of Computer Engineering and Applications,

Transcription

1 International Journal of Computer Engineering and Applications, Volume XI, Issue IX, September 17, ISSN DATA INTEGRITY CHECK IN CLOUD COMPUTING: A FRAMEWORK Neha Thakur 1, Aman Kumar Sharma 2 1 Department of Computer Engineering 2 Department of Computer Science Engineering Himachal Pradesh University Shimla, India ABSTRACT: Cloud computing is defined as Distributed computing on internet or delivery of computing services over the network. Cloud computing has potential to primordially change the ethos of Information and communication Technology [ICT] provision in the public service and significantly alleviate cost. The traditional storage techniques require high costs of data storage devices as well as the acute rate at which data is being generated, cloud computing vindicate expensive for enterprise and individual users to regularly update their hardware. Apart from reducing the cost cloud computing also minimize the maintenance efforts. In cloud computing data and program is moved to a remotely located cloud server, from where users can access the data at anytime and from anywhere through thin clients and mobile devices using internet. This brings many advantages such as data ubiquity, flexibility of access and resilience. However it also increase the threat of data integrity, cloud faithfully stores the data and return back to the owner whenever needed, but it doesn t guarantee that the data stored in cloud is secured and not altered by the cloud and TPA [1].In order to overcome the threat of integrity a mechanism is proposed where owner may verify the correctness of data without much hassles. Keywords: Data owner, Secret Key, Data Integrity, Proof of Reliability, Cloud Service Provider [1] INTRODUCTION Neha Thakur, Aman Kumar Sharma 38

2 DATA INTEGRITY CHECK IN CLOUD COMPUTING: A FRAMEWORK Cloud computing is the latest paradigm that involves delivering hosted services over the internet based on pay as you go approach. Cloud computing is a technology that uses the internet and central remote servers to maintain data and applications. It is a marketing term for technologies that provide computation, software, data access and storage services that do not require end-user knowledge of the physical location and configuration of the system that delivers the services. Cloud enhances collaboration, agility, scaling, and availability, and provides the potential for cost reduction through optimized and efficient computing. Cloud computing allows consumers and businesses to use applications without installation and access their personal files at any computer with internet access. Cloud computing is broken down into three segments: "application" "storage" and "connectivity." Each segment serves a different purpose and offers different products for businesses and individuals around the world [2]. Cloud computing environments are likely to suffer from a number of known vulnerabilities, enabling attackers either to obtain computing services for free (attack against cloud providers), steal information from cloud users (attack against cloud customers data), or penetrate the infrastructure remaining in client premises through cloud connections (attack against cloud customer infrastructures). Typical examples of these attacks today are VoIP free calls, SQL injection, and drive by downloads [3]. Cloud networking will not change the fact that vulnerabilities will continue to exist and that attackers will continue to exploit them. Big IT giants like Google, Amazon, and salesforce.com are providing computing facility like storage, computation and application by pay as per usage through Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) cloud service models. Since cloud computing supports distributed service oriented architecture, multi users and multi-domain administrative infrastructure, it s more prone to security threats and vulnerabilities. Security issues are of more concern to cloud service providers who are actually hosting the services. [2] CLOUD COMPUTING ARCHITECTURE Cloud computing architecture refers to the components and subcomponents required for cloud computing. These components typically consist of a front end platform (fat client, thin client, mobile device), back end platforms (servers, storage), a cloud based delivery, and a network (Internet, Intranet, Intercloud). Combined, these components make up cloud computing architecture. [2.1] CLOUD COMPUTING SERVICE DELIVERY MODELS Cloud Computing can be broadly classified into three categories, i.e., three layers of Cloud Stack, also known as Cloud Service Models or Service Platform Infrastructure [SPI] Service Model. The three main cloud service delivery models are: Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS) [4]. Neha Thakur, Aman Kumar Sharma 39

3 International Journal of Computer Engineering and Applications, Volume XI, Issue IX, September 17, ISSN SAAS SAAS is a software model provided by the vendor through an online service. It provides networkbased access to commercially available software. User interface powered by "thin client" applications; cloud components; communication via (Application Program Interfaces (APIs); stateless; loosely coupled; modular; semantic interoperability. This will avoid capital expenditure on software and development resources; reduced Return On Investment (ROI) risk; streamlined and iterative updates. On the contrary, Centralization of data requires new/different security measures. Examples of SaaS include Netflix, Intuit QuickBooks Online, Gmail, and Google Docs [5]. The four major advantages of SaaS are:- Increased speed of deployment Increased user adoption Reduced support requirements Lowered cost of implementation and upgrades PAAS PaaS enables companies to develop applications more quickly and efficiently in a cloud environment using programming languages and tools supported by the provider. The defining factor that makes PaaS unique is that it lets developers build and deploy web applications on a hosted infrastructure. It consumes cloud infrastructure. All centralized system requires new/different security measures. Common examples of platforms include Windows, Apple Mac OS X, and Linux for operating systems; Google Android, Windows Mobile, and Apple ios for mobile computing; and Adobe AIR or the Microsoft.NET Framework for software frameworks[6][7]. IAAS This is the base layer of the cloud stack. It serves as a foundation for the other two layers, for their execution. The keyword behind this stack is Virtualization. Usually platform-independent; infrastructure costs are shared and thus reduced; service level agreements (SLAs); pay by usage; selfscaling. Avoid capital expenditure on hardware and human resources; reduced ROI risk; low barriers to entry; streamlined and automated scaling but disadvantages are Business efficiency and productivity largely depends on the vendor's capabilities; potentially greater long-term cost; centralization requires new/different security measures. With, a company can rent fundamental computing resources for deploying and running applications or storing data. IaaS enables fast deployment of applications, and improves the agility of IT services by instantly adding computing processing power and storage capacity when needed[8][9]. [2.2] CLOUD DEPLOYMENT MODELS Regardless of the service model utilized (SaaS, PaaS, or IaaS) there are four deployment models for cloud services [10][11][12]: Public Cloud: The cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services. Means where the infrastructure resides totally outside of the tenant /enterprises? Neha Thakur, Aman Kumar Sharma 40

4 DATA INTEGRITY CHECK IN CLOUD COMPUTING: A FRAMEWORK Private Cloud: The cloud infrastructure is operated solely for a single organization. It may be managed by the organization or a third party, and may exist on-premises or off premises. IT services are mounted on top of large-scale accumulated and virtualized infrastructure within enterprise firewall and consumed in per transaction basis. Community Cloud: The cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, or compliance. considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises. Hybrid Cloud: The cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds). Here, the infrastructure and business processes reside partly within the enterprise and partly consumed from third party. Figure: 1. cloud computing architecture [1] [3] DATA INTEGRITY Integrity, in terms of data security, is the guarantee that data can only be accessed or modified by those authorized to do so, in simple word it is process of verifying data. Data Integrity is very important among the other cloud challenges. As data integrity gives the guarantee that data is of high quality, correct, unmodified. After storing data to the cloud, user depends on the cloud to provide more reliable services to them and hopes that their data and applications are in secured manner. But that hope may fail sometimes the user s data may be altered or deleted. Sometimes, the cloud service providers may be dishonest and they may discard the data which has not been accessed or rarely accessed to save the storage space or keep fewer replicas than promised [2]. Moreover, the cloud service providers may choose to hide data loss and claim that the data are still correctly stored in the Cloud. As a result, data owners need to be convinced that their data are correctly stored in the Cloud. So, one of the biggest concerns with cloud data storage is that of data integrity verification at untrusted servers. In order to Neha Thakur, Aman Kumar Sharma 41

5 International Journal of Computer Engineering and Applications, Volume XI, Issue IX, September 17, ISSN solve the problem of data integrity checking, many researchers have proposed different systems and security models. [4] DATA INTEGRITY AUTHENTICATION TECHNIQUES AND THEIR CHALLENGES In Cloud computing the issue of data integrity is still carried out by many researchers. There is lot of research still going on in this field to provide secure and efficient data integrity in cloud computing. Researchers have given many solutions to focus on resolving the issues of data integrity. This paper provides analysis on the different techniques of data integrity and their advantages and disadvantages: Data Integrity Techniques Provable Data Possession PDP Scheme based on MAC Table1: Comparison of data integrity techniques[13] Methods used Advantages Limitations for data integrity Key Generation Algorithm Message Authenticatio n Code i. This technique gives a strong proof of data integrity. ii. Protection against small corruptions. iii. Allows public verifiability. i. Simple & Secure Technique. ii. Gives strong proof Integrity of Data. i. Lack of error correcting codes to address concerns of corruption. ii. iii. iv. Lack of privacy preservation. No dynamic support. Unbound no. of queries i. Limited number of verifications with limited number of secret keys. ii. The data owner has to retrieve the entire file of F from the server in order to compute new MACs, Which is not possible for large file. iii. Public auditability is not supported as the private keys are required for verification. Scalable PDP Cryptographic Hash function & symmetric key encryption i. It provides secure PDP by encryption. ii. Supports dynamic operations on outsourced data blocks iii. It is light weight PDP scheme as it supports i. Limited number of updates and challenges. ii. Does not perform block insertions anywhere only append-type insertions are possible. iii. Problematic for large files as each update Neha Thakur, Aman Kumar Sharma 42

6 DATA INTEGRITY CHECK IN CLOUD COMPUTING: A FRAMEWORK Dynamic PDP Proof of Retrievability POR based on keyed hash function hk POR for large files High Availability Integrity Layer (HAIL) POR Based on Selecting Random Bits in Data Blocks Rank-based authenticated skip list. Encryption Key Hash Function Sentinelbased scheme MAC, Pseudorando m function, Hash Function Generation of Meta Data homographic hash function. i. Offers fully dynamic operation. ii. Efficient integrity verification is made by querying and updating DPDP scenario. i. Reduces the computational and storage overhead of the client as well as CSP. ii. It also minimizes the size of the proof of data integrity as reduces the network. Bandwidth. i. Simple and easily implementable. i. Ensures both possession and retrievability of files on CSP i. Allow user to store data on multiple cloud. i. This technique is suitable for thin client. ii. Put minimum storage overhead on client and CSP. requires re-creating all the remaining challenges i. Client needs to perform extra computation. ii. Not suitable for thin client. iii. DPDP does not include provisions for robustness. i. It only works with static data sets. ii. It supports only a limited number of queries as a challenge since it deals with a finite number of check blocks. iii. A POR does not provide in prevention to the file stored on CSP. i. More number of keys for each check. ii. Requires high cost for computation. iii. Puts the computational burden on client as well as server. ii. Newly inserted sentinels and error correcting codes Put computational overhead. iii. Increases input/output and transmission cost across the network. iv. Works only with static data. i. This technique is only applicable for static data. ii. Not suitable for thin client i. This technique is only applicable for static data. ii. No Data Prevention mechanism is implemented in this technique. Neha Thakur, Aman Kumar Sharma 43

7 International Journal of Computer Engineering and Applications, Volume XI, Issue IX, September 17, ISSN [5] PROPOSED FRAMEWORK Traditional approach for checking data correctness is to retrieve entire file from the server and then verify the integrity of the file. Downloading the entire file from Cloud to verify the integrity increases cost on communication resources or hardware of the data owner. Also data can't be retrieved through thin clients or smart phones which have limited computation, battery power and bandwidth. In this study a solution is proposed wherein the owner does not need to retrieve the entire file to check the correctness of the file, the owner do this even without downloading a single bit of file thus reducing the hardware cost and time. This system is more suitable for users using thin clients or mobile devices, owner needs to store only a single secret key or metadata irrespective of the size of the data file. The verifier or owner before storing the file at the cloud pre-process the file and generate some metadata and store this metadata with them. At the time of verification the verifier uses this metadata to check the correctness of the data. It is important to know that proof of data integrity just check the integrity of data that is either the data has been illegally modified or deleted, it does not prevent the data from illegal accesses and modifications. This process of verifying the data stored in cloud storage follows following steps:- 1. Setup Phase a) In this phase before storing the file on cloud, we pre-process the file and divide it into M-size blocks shown in Figure2. b) k-bit is selected from each M-size blocks, where k-bit is user defined. c) Thus we generate secret key or metadata. Which store on owner side for verification process. Figure: 2. Generation of Secret Key 2. Verification Phase If verifier wants to verify the integrity of file, it requests cloud and asks for response. On the basis of response a decision is made whether the file is tampered or not. Every file contains N number of data blocks of M-size. From every data block K-bit position is selected for generating secret key or metadata. To check the integrity or obtaining the proof of reliability the data owner retrieves the particular k-bits from each M-size block instead of retrieving the whole file and then compare the value of these k-bits with the stored secret key or metadata. If both the values are matched with each other, it means data is safe or not modified by third party. If it is not, then data was modified or altered by third party. Neha Thakur, Aman Kumar Sharma 44

8 DATA INTEGRITY CHECK IN CLOUD COMPUTING: A FRAMEWORK [6] CONCLUSIONS & FUTURE WORK Every coin has two sides. Even though the cloud technology offers great potential to improve quality, optimize productivity and cost effective, it also includes many security challenges related to the data safety and accuracy. As the cloud is mainly used for storage purposes, data integrity is of primary concern to the user as the control over the data is relinquished from the user. The proposed system provides the proof of data integrity and the owner can check the integrity of their data in efficient manner. If any modification is done by the Third Party Auditor [TPA], owner can easily detect those changes. So privacy and data integrity is secured properly. It also reduces the cost for retrieving the file and bandwidth consumption across the network. The scheme proposed in this paper, works only for static data and not for dynamic data. So expanding the scope of this paper will be the future work. REFERENCES [1] Balachandra Reddy Kandukuri, Ramakrishna Paturi V, Dr. Atanu Rakshit, "Cloud Security Issues, Proceedings IEEE International Conference on Services Computing, September [2] P Schoo, V Fusenig, V Souza, M Melo, P Murray, H Debar, H Medhioub, and D Zeghlache, Challenges for Cloud Networking Security, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Volume 68, Part VII, [3] N Provos, M A Rajab, P Mavrommatis, Cybercrime 2.0: When the cloud turns dark, Queue, PP 46 47, [4] A Juels and B S Kaliski Jr, Proofs of Retrievability for Large Files, Proceedings of 14th ACM Conference Computer and Communication Security, [5] E Aguiar, Y Zhang and M Blanton, An overview of issues and recent developments in cloud computing and storage security in high performance cloud auditing and applications, Springer, PP 3 33, [6] K DBowers, A Juels, and A Oprea, HAIL: A high-availability and integrity layer for cloud storage, Proceedings of 16th ACM conference on Computer and communications security,ieee, [7] R Sravan kumar and Saxena, Data integrity proofs in cloud storage, Volume 4, Isssue 2, IEEE, [8] S Ramgovind, M M Eloff, and E Smith, The management of security in cloud computing, Information Security for South Africa (ISSA), IEEE, PP 1 7,2010. [9] F Sabahi, Cloud computing security threats and responses, Communication Software and Networks (ICCSN), IEEE 3rd International Conference on cloud computing security, PP , [10] X Wang, B Wang and J Huang, Cloud computing and its key techniques, Computer Science and Automation Engineering (CSAE), Volume 2, IEEE, PP , [11] S Subashini and V Kavitha, A survey on security issues in service delivery models of cloud computing, Journal of network and computer applications, Volume 34, PP 1 11, 2011 [12] J. Yang and Z. Chen, Cloud computing research and security issues, Computational Intelligence and Software Engineering (CiSE), IEEE, PP 1 3, [13] Neha Thakur, Aman Kumar Sharma, Data integrity techniques in cloud computing: an analysis, International journal for advance research in computer science and software engineering (IJARCSSE), Volume 7 Issue 8, Neha Thakur, Aman Kumar Sharma 45