Secured Medical Information Transmission Using Chaos Through Cloud Computing

Transcription

1 Middle-East Journal of Scientific Research 23 (10): , 2015 ISSN IDOSI Publications, 2015 DOI: /idosi.mejsr Secured Medical Information Transmission Using Chaos Through Cloud Computing I. Bremnavas Department of Computer Engineering and Networks, College of Computer Science and Information Systems, Jazan University, Jazan, Saudi Arabia Abstract: The next generation platform cloud provides virtualization, dynamic resource pools and high availability. The user enables e cloud storage remotely to store eir data and enjoy e on-demand service and such a service also leaving users physical control of eir outsourced data. This problem can be addressed by achieving a secure and dependable cloud storage service. The proposed system uses e secured medical information transmission using chaotic technique rough e cloud computing system. Key words: Cloud storage Chaos Cloud computing Chaotic random key generation INTRODUCTION providers such as Microsoft SkyDrive, Amazon, Dropbox, Apple icloud and Google Drive are all services initiated Cloud computing is e new era of internet based few years back. The cloud computing models and computing system, which provides to user working characteristics are shown in Figure 1. wi e cloud applications in simple and customizable. The rapid development of cloud computing is It offers to store and access e cloud data from anywhere increasing severe security concern. Lack of security is by connecting e cloud application using internet [1]. e problem in widespread adoption of cloud Users are able to store eir local data in e remote server computing [3]. It bounded various security issues such as using e cloud service [2]. In is service oriented securing e data, virtualization and examining e computing environment, e cloud computing have utilization by e cloud computing dealers. Various progressed as a most popular paradigm which resolves security and privacy concern are in e unique cloud e infrastructures are delivered as a service. Most environment [4]. commonly used cloud service is data storage among oer services, where end users can outsource any data to Shared and Extensible Responsibility: Shared and cloud servers, to enjoy and access e hardware/software extensible responsibility is compromised between resources virtually wiout investment. A set of cloud customers in different delivery models. computing services such as Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a Outsourcing: Cloud providers should have appropriate Service (IaaS) can be accessed by e cloud computing mechanisms to prevent e control of users data lose. model. In SaaS services are provided rough e service providers and customers to run applications on a cloud Heterogeneity: Security and privacy mechanism has infrastructure. It can be accessed rough web browsers. satisfied different cloud providers which may access e In PaaS services are a mode to rent hardware, operating different approaches, us generating integration system, storage and capacity of network over e internet. challenges. In IaaS services e consumer is provided wi storage management and network, power to control process and Multi-Tenancy: Policies, protection, data access and oer fundamental computing resources which are helpful deployment of application must be e considered as to manage arbitrary software. The popular cloud service major issues of a secure multi-tenant environment. Corresponding Auor: I. Bremnavas, Department of Computer Engineering and Networks, College of Computer Science and Information Systems, Jazan University, Jazan, Saudi Arabia. 2552

2 Fig. 1: Cloud computing NIST (National Institute of Standard and Technology) Definition The tremendous technical advantage of e cloud, Cloud Based Medical Information System: Businesses, security and privacy concern has been major problem organizations, medical information system and e preventing its adoption. Cloud users store e sensitive consumers are adopting cloud technologies. Nowadays, and privacy information in cloud instances. From security e serious problem in e-heal care environment is and privacy concerns, cloud providers need to ensure e medical information security. The security tool can protect confidentiality of e service. Any cloud service, user is medical information from attackers. L.M. Vaquero et al. supposed to know e risk associated wi e data focused only on e-heal security and privacy protection security, e.g., user data loss and data eft. in e cloud [12]. Cryptographic algorim like Rivest Auentication, data encryption, integrity, recovery and Shamir Adleman (RSA) and Data Encryption Standard user protection are all e important components to cover (DES) were used for medical information security. But it is e data security model in cloud. To avoid unauorised not effective for medical information security because of person access of e data, applying encryption e high data capacity and correlation among pixels. mechanism on data, at data is totally unusable. Chaos have been explored in last two decades for medical Encryption is always a powerful scheme whenever storing information security, it has some suitable intrinsic features e sensitive and privacy information. To confirm e of medical image processing. Chaos can be well applied in basic security model components like confidentiality, cryptography [13, 14]. Because it has many characteristics integrity and availability (CIA), e cloud storage which can be connected wi e confusion and diffusion provider need to include a security scheme to ensure at property in cryptography, such as sensitive dependence e shared storage environment safeguards for e data on initial conditions and parameters, broadband power [5]. This survey have been discussed some security spectrum, randomness in e time domain and ergodicity issues in cloud computing. E.M. Mohamed et al. [6] etc. discussed e data security model of cloud computing Cloud based medical information system is and also implemented data security model for cloud becoming more predominant in medicine. Still, in e-heal computing. care environment some medical information systems M. Balduzzi et al and C. Rong et al. [7, 8] presented have concerns about transferring eir data storage, e security issues review of e cloud computing. Akhil computing capacity to e cloud providers. Behl [9] has discussed e exiting security approaches Collaboration among e hospitals and medical society is and security issues related to e cloud environment. required for sharing patient medical data and images. E.Maisen [10] presented few key security issues of Patient medical data stored in virtual environment are cloud computing. Sabahi [11] focussed e security easily accessible by different healcare providers, us issues, reliability and availability for cloud computing and e advantage of process is facilitating sharing of data also given some solutions for security issues. and considerably reducing local storage requirements. 2553

3 Fig. 2: Cloud computing general architecture Ultimately what system allows physicians to build characterized by sensitive dependence on initial networks for storing e high volume of patient medical conditions and similarity to random behaviour. information and open platform for sharing and accessing Here, we consider one dimensional chaotic logistic of patient medical information. map. It is a simple model which yields chaos, can be The proposed system uses e secured patient written as: medical information transmission using chaotic map over to cloud computing system. The first process is to x n+1 = a x n (1-x n) ( n=0, 1, 2 ) where 0<=a<=4 provide e security for patient medical data using chaos and sharing and exchanging wi e available "Cloud". This is a discrete time map which receives a real The patient medical information will be available in e number between 0 and 1 and returns a real number in cloud, which can provide e required details to e [0, 1]. n denotes a discrete time step and x n denotes doctors and e patient can seek e treatment in oer a data at n. Time series x n (n=0, 1, 2 ) is deterministic. branch hospital, reduce e computational resource Using e above simulator, we can get ese sequences x0, maintenance in e hospital. The cloud computing general x 1, x 2... dramatically and a is e control parameters architecture is shown in Figure 2. governing e chaotic behavior. In e above logistic difference equation initial key Secured Medical Information Transmission Using a = 0.3 as e user perception. The difference equation is Chaotic Map in Cloud: From security perspective, for evaluated to generate a sequence of random numbers secure communication e encryption is a better which are sorted and eir index value is used. This value mechanism. Better to secure e data before storing in a 0.3 acts as an encryption key K for e encryption cloud server. User can give e permission to eir process. The image pixel in e one dimensional array members such at data can be easily accessed by em. format is being encrypted wi e pseudo random In a public cloud, users are sharing medical information numbers generated by e logistic map as e key in e wi oer medical hospitals. In a shared pool outside e chaotic region i.e., a value 0 and 4. It has been applied to hospitals, users don t have any knowledge or control of security and increases e hiding capacity of e where e resources are located. Because users share e embedding positions. This proposed algorim has been medical environment in e cloud, may put your data at put forward for Least Significant Bit (LSB) based image risk of seizure. Data integrity is assurance at e data is steganography in which e last bits of e cover image consistent and correct. Ensuring e integrity of e data are replaced by e bits of e message image which is really means at it changes only in response to encrypted using index based logistic chaotic map. auorized transactions. Now e image is encrypted in e chaotic region and it is The dynamic nonlinear system is chaos, has ready to send across e transmission channels wi more brought out e consideration of ese facts such as number of attackers. Figure 3 is e proposed flow low-dimensional dynamical systems are capable of diagram of secured medical image transmission using handling complex and unpredictable behaviour. Chaos chaos in distributed cloud environment. Figure 4 is e seems to be a good technique for encryption algorim, flow diagram of proposed embedding algorim. 2554

4 SENDERSIDE Medical Information System Database Medical Image Information (I) Chaotic signal is generated (CS) Chaos signal in to medical image information (CSI) Encrypted Medical Image Information wi respective index key (ES) Cloud Storage Medical Information System Database Extracted Medical Image Information (I) Chaotic s ignal is extracted Chaos signal in to medical image information (CSI) Encrypted Medical Image Information wi respective index key (ES) RECEIVER Fig. 3: Secured medical image transmission using chaos in distributed cloud environment Input medical image information (I) Embedding chaos signal in to medical image information (CSI) Output medical image information wi chaos signal (ES) Fig. 4: Embedding Process The medical information system has a patient medical x n+1 = ax n (1- x n) database, where n number of patient medical information in e database. It extracts e features from Step 3: The medical image information I is medical information and generates a key. To protect what e sensitive patient medical information are encrypted embedded wiin e chaotic signal S using e following steps before outsourcing to e cloud server. During e encryption process, e unique index key value is assigned for each patient medical data. Then, e encrypted query is submitted to e cloud server. Finally, e auorized user decrypts e received medical information. Working example of sender side encryption process is shown in Figure 5. Proposed Embedding Algorim: I/P and O/P: Medical image information, I: Encrypted Signal, ES Step 1: Load an medical image information from e database and store an image in one-dimensional array named as I. Step 2: Generate e chaotic signal S using logistic equation. Fix e covered boundary region based on e size of an medical image information I. The signal is assumed to be generated from e starting position of e boundary region. Set a key value K dynamically as user perception wiin e boundary region for representing e initial position. The medical image information value I is embedded wi chaotic signal S from K. The sort actual indexes of e sorted key values should be stored. Step 4: The Encrypted signal (ES) is transferred along wi e key value K. (The key value is embedded in a standardized position of e signal ES). 2555

5 Medical Image Information (I) Generate e signal based on e logistic equations (CSI) Medical Information and chaos signal wi e cover region (ES) Fig. 5: Working example of sender side encryption process 2556

6 Medical image information wi chaos signal (ES) Extracting chaos signal (CS) Medical image information (I) Fig. 6: Extraction Process Medical Information and chaos signal wi e cover region (ES) Extracting e Chaotic signal (CS) Medical Image Information (I) Fig. 7: Working example of receiver side decryption process 2557

7 Figure 6 is e flow diagram of proposed extraction 3. Fernandes, D.AB., L.FB. Soares, J.V. Gomes, M.M. process. The encrypted image is received by e trusted Freire and P.R.M. Inacio, Security issues in receiver. The indexing key value and e key is also cloud environments: a survey, Int. J. Inform. Sec., embedded in e same cover region wi secret coding. 13(2): The receiver generates e random numbers using same 4. Takabi, H., J. Joshi and G.J. Ahn, Secure cloud: logistic equation. The encrypted logistic map is Towards a comprehensive security framework for subtracted from e raw logistic map ereby e image is cloud computing environments, In: Computer being retrieved from e encrypted source of information. Software and Applications Conference Workshops Working example of receiver side decryption process is in (COMPSACW), 2010 IEEE 34 Annual, pp: Figure Xiao, Z. and Y. Xiao, Security and privacy in cloud computing, IEEE Commun. Surveys Tutorials, Proposed Extraction Algorim: 15(2): Mohamed, E.M., Hatem S. Abdelkader, Sherif E.I. I/P : Encrypted signal, ES Etriby, Enhanced Data Security Model for O/P : Medical image information, I Cloud Computing, in: 8 International Conference on Informatics and Systems (INFOS), Cairo, pp: Step 1: Receive e encrypted signal, ES from e open 7. Balduzzi, M., J. Zaddach, D. Balzarotti, E. Kirda and communication channel. S. Loureiro, A Security analysis of amazon s Step 2: Retrieve e actual indexes of e stored key value elastic compute cloud service, in: Proceedings of e K from encrypted signal ES. 27 Annual ACM Symposiumon Applied Step 3: Generate e chaotic signal S using logistic Computings, pp: equation. 8. Rong, C., S.T. Nguyen and M.G. Jaatun, x n+1 = ax n (1- x n) Beyond lightning: a survey on security challenges in cloud computing, Comput. Electr. Engg., 39(1): Step 4: Subtract e received encrypted signal, ES wi 9. Akhil Bhel, Emerging Security Challenges in e raw logistic signal, S using e key value K, to obtain Cloud Computing. Information and Communication a one-dimensional array for medical image information, I Technologies, in: World Congress on, Mumbai, Step 5: The resultant medical image information, I from e pp: one-dimensional array. 10. Eystein Maisen, Security Challenges and Solutions in Cloud Computing, in: International CONCLUSION Conference on Digital Ecosystems and Technologies (IEEE DEST 2011), pp: In is work, we proposed a secured medical 11. Farzad Sabahi, Cloud Computing Security information transmission using chaotic map rough rd Threats and Responses, in: IEEE 3 International cloud computing system. The proposed meod considers Conference on Communication software and e techniques from chaos security and image processing Networks (ICCSN), pp: domains to perform secure medial information outsourcing 12. Abbas, A. and S.U. Khan, A Review on e problem. state-of-e-art privacy preserving approaches in e- healclouds, IEEE J. Biomed. Heal Inform. REFERENCES 13. Maniccam, S.S. and N.G. Bourbkis, Pattern Recognition, 37: Vaquero, L.M., L. Rodero-Merino, J. Caceres and 14. Kocarev, L., IEEE Circuits and System M. Lindner, A break in e clouds: towards a Magazine, 3: cloud definition, in: ACM SIGCOMM Computer Communication Review, pp: Mollah, M.B., K.R. Islam and S.S. Islam, Next generation of computing rough cloud computing technology, in: 25 IEEE Canadian Conference on Electrical Computer Engineering (CCECE), pp: