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i-manager's Journal on Cloud Computing (JCC)

Current Issue Vol. 11 Issue 1

An OptiAssign-PSO Based Optimisation for Multi-Objective Multi-Level Multi-Task Scheduling in Cloud Computing Environment
Advanced Analytics for Disease Tracking & Remote Intravenous Injection Monitoring
DevKraft - Fueling Collaboration in Coding Challenges
Comparative Security and Compliance Analysis of Serverless Computing Platforms: AWS Lambda, Azure Functions, and Google Cloud Functions
Blockchain Healthcare Management using Patients

Most Cited

Volume 1 Issue 4 August - October 2014

Article

A Survey about Green Credential Cloud and its Security

T.Jenitha Arun Rejus*

PG Graduate, Department of Computer Science, Archana Institute of Technology, Krishnagiri, India.

Rejus, T. J. A. R. (2014). A Survey about Green Credential Cloud and its Security. i-manager’s Journal on Cloud Computing, 1(4), 1-10. https://doi.org/10.26634/jcc.1.4.3189

Abstract

In this paper, the green credentials and the security in cloud computing is elaborated in a way that covers security issues, concerns and challenges for Data Security in cloud. Cloud computing plays an important role in bringing the users closer to applications. Cloud computing is said to be a main form of modern computing due to its tremendous advantages. But the main cause is about trust. Cloud computing offers the potential to reduce the environmental impact of Information and Communication Technology (ICT), mostly due to its flexibility and scalability. The users trust the cloud and decide to store sensitive data in the cloud, but the cloud does not provide that much security to the users' data. The key security issue with clouds is that the user of the data may not have control over their data and never have any idea about where the data is placed. This paper deals with cloud computing security issues and threats, especially with data confidentiality and privacy issues. The interests of different groups on users' private data, the legal aspects which enable governments and service providers itself to access their users' data and also the technical background on how they can do so, is covered. Finally some feasible remedies are also presented.

References

[1]. Moritz Borgmann, Tobias Hahn, Michael Herfert, Thomas Kunz, Marcel Richter, Ursula Viebeg, and Sven Vowé. (2012). “On the security of cloud storage services”, Fraunhofer Institute for Secure Information Technology- SIT, Tech. Rep. SIT-TR-001.

[2]. Armando Fox, Rean Gri_th, A Joseph, R Katz, A Konwinski, G Lee, D Patterson, A Rabkin, and I Stoica. (2009). “Above the clouds: A berkeley view of cloud computing”, Dept. Electrical Eng. and Comput. Sciences, University of California, Berkeley, Rep. UCB/EECS, 28.

[3]. Iulia Ion, Niharika Sachdeva, Ponnurangam Kumaraguru, and Srdjan .apkun. (2011). “Home is safer than the cloud!: privacy concerns for consumer cloud storage”, In Proceedings of the Seventh Symposium on Usable Privacy and Security, page 13. ACM.

[4]. Harry Katzan Jr et al. (2011). “On the privacy of cloud computing”, International Journal of Management & Information Systems (IJMIS), Vol. 14, No. 2.

[5]. William Jeremy Robison. (2009). “Free at what cost: Cloud computing privacy under the stored communications act” The George town Law Journals, Vol. 98, pp. 1196-1232.

[6]. Christopher Soghoian (2010). “Caught in the cloud: Privacy, encryption, and government back doors in the web 2.0 era”, J. on Telecomm. & High Tech. L., Vol. 8, pp. 359.

[7]. Christopher Soghoian (2012). “The Spies We Trust: Third Party Service Providers And Law Enforcement Surveillance”. Ph.D thesis, Indiana University.

[8]. Christopher Soghoian and Sid Stamm. (2012). “Certi_ed lies: Detecting and defeating government interception attacks against ssl (short paper)”. In Financial Cryptography and Data Security, Vol. 7035, pp. 250-259, Springer,19

[9]. Stephen S. Yau and Ho G. An (2010). “Confidentiality Protection in Cloud Computing Systems”, Int J Software Informatics, Vol.4, No.4, pp. 35-1365.

[10]. T. Ristenpart, E. Tromer, H. Shacham, and S. Savage, (2009). “Hey, you, get off of my cloud: exploring information leakage in third-party compute clouds,” Proc. 1 6 t h ACM Conference on Computer and Communications Security, pp. 199-212.

[11]. B. D. Payne, M. Carbone, and W. Lee, (2007). “Secure and Flexible Monitoring of Virtual Machines,” In Proc. ACSAC'07, pp. 385-397.

[12]. Venkatesh, V. (2000). “Determinants of percieved ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model”, Information Systems Research, Vol. 11, No. 4, pp. 342- 365.

[13]. Igbaria, M., & Iivari, J. (1995). “The effects of selfefficacy on computer usage”, Omega, Vol. 23, No. 6, pp. 587-605.

[14]. Garbarino, E., & Johnson, M. S. (1999). “The different roles of satisfaction, trust and commitment in customer relationships”, Journal of Marketing, Vol. 63, No. 1, pp. 70- 87

[15]. Brodkin, J. (2008). “Gartner: Seven cloud- computing security risks”, Retrieved September 23, 2009, from Network World, from http://www.networkworld.com/news /2008/070208-cloud.html

[16]. Gartner (2008). “Assessing the Security Risks of Cloud Computing ” , Retrieved December 5 , 2009 , http://www.networkworld.com/news /2008/070208-cloud.html http://www.gartner.com/DisplayDocument?id=685308

[17]. Spiekermann, S. and Cranor, L. F. (2009). “Engineering Privacy”, IEEE Transactions on Software Engineering, Vol. 35, No. 1, pp. 67-82.

[18]. Bardin, J., Callas, J., Chaput, S., Fusco, P., Gilbert, F. et al. (2009). “Security Guidance for Critical Areas of Focus in Cloud Computing v2.1”, Retrieved January 28, 2010, from Cloud Security Alliance, from http://www. cloudsecurityalliance.org/guidance/

[19]. Karat, C. and Blom, J. (2004). “Designing personalized user experiences in e-Commerce”, Kluwer Academic Publishers

[20]. Price, M. and Partners, A. (2008). “The Paradox of Security in Virtual Environments”, Computer, Vol. 41, No. 11, pp. 22-28.

[21]. Vaughan-Nichols, S. (2008). “Virtualization sparks security concerns”, Computer, Vol. 41, No. 8, pp. 13-15.

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Article

An Overture of Mobile Cloud Computing and its Applications

D. R. Robert Joan*

Assistant Professor, Mathematics Education, Christian College of Education, Marthandam, Tamil Nadu, India.

Joan, D. R. R. (2014). An Overture of Mobile Cloud Computing and its Applications. i-manager’s Journal on Cloud Computing, 1(4), 11-18. https://doi.org/10.26634/jcc.1.4.3190

Abstract

In this article, the author presents some information related to Mobile cloud computing and its applications. Mobile Cloud Computing is the combination of cloud computing, mobile computing and wireless networks to bring rich computational resources to mobile users, network operators, as well as cloud computing providers. Mobile cloud computing at its simplest refers to an infrastructure where both the data storage and data processing happen outside of the mobile device. From various studies, the author concludes that mobile cloud computing provides data storage, processing services in clouds at low cost and elastically in an on-demand fashion. It also provides security architecture when mobile devices integrate with cloud. Some of the mobile cloud computing applications are mobile healthcare, mobile commerce, mobile learning, mobile gaming, social networks like twitter and facebook, booking applications for travel and shopping. Cloud services such as guiding their trip, showing maps, recording itinerary, and storing images and video are also in the mobile devices.

References

[1]. Abolfazli, S., Sanaei, Z., Ahmed, E., Gani, A., & Buyya, R. (2013). “Cloud-Based Augmentation for Mobile Devices : Motivation, Taxonomies, and Open Challenges”, IEEE Communications Surveys & Tutorials, pp. 1–32. doi:10.1109/SURV.2013.070813.00285.

[2]. Chen, X., Liu, J., Han, J., & Xu, H. (2010). “Primary Exploration of Mobile Learning Mode under a Cloud Computing Environment ”, Proceedings of the International Conference on E-Health Networking, Digital Ecosystems and Technologies (EDT), Vol. 2, pp. 484-487.

[3]. Dai, J. & Zhou, Q. (2010). “A PKI-based mechanism for secure and efficient access to outsourced data”, Proceedings of the 2nd International Conference on Networking and Digital Society, Vol. 1, pp. 640.

[4]. Dinh, H. T., Lee, C., Niyato, D., & Wang, P. (2010). “A Survey of Mobile Cloud Computing: Architecture, Applications, and Approaches”, The School of Computer Engineering, Nanyang Technological University, Singapore. Retrieved from http://onlinelibrar y .wiley.com/doi/10.1002/wcm.1203.

[5]. Donald, A.C., Arul, S. O., & Arockiam, L. (2013). “Mobile Cloud Security Issues and Challenges: A Perspective”, International Journal of Engineering and Innovative Technology, Vol. 3(1), ISSN: 2277-3754, ISO 9001:2008 Certified.

[6]. Kopec, D., Kabir, M. H., Reinharth, D., Rothschild, O., & Castiglione, J. A. (2003). “Human Errors in Medical Practice: Systematic Classification and Reduction with Automated Information Systems”, Journal of Medical Systems, Vol. 27(4), pp. 297 - 313.

[7]. La, H.H., & Kim, S.D. (2010). “A Conceptual Framework for Provisioning Context-aware Mobile Cloud Services”, Proceedings of the 3rd IEEE International Conference on Cloud Computing (CLOUD). pp. 466.

[8]. Li, H., & Hua, S. (2010). “Melog: mobile experience sharing through automatic multimedia blogging”, Proceedings of the 2010 ACM multimedia workshop on Mobile cloud media computing (MCMC), pp. 19-24.

[9]. Li, Z., Wang, C., & Xu, R. (2001). “Computation offloading to save energy on handheld devices: a partition scheme”, Proceedings of the 2001 international conference on Compilers, architecture, and synthesis for embedded systems (CASES). pp. 238 - 246.

[10]. Morshed, M. S., Jahan, M. M., Islam, M. K., Huq, M., Hossain S., & Basher, M. A. (2011). “Integration of Wireless Hand-Held Devices with the Cloud Architecture: Security and Privacy Issues”, International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), pp. 83-88.

[11]. Nasir, A. K., Kiah, M.L., Samee, U. K., & Sajjad, A. M., (2012). “Towards secure mobile cloud computing: A survey”, Future Generation Computer Systems, Vol. 29(5), pp. 1278-1299.

[12]. Oberheide, J., Veeraraghavan, K., Cooke, E., Flinn, J., & Jahanian, F. (2008). “Virtualized incloud security services for mobile devices”, Proceedings of the First Workshop on Virtualization in Mobile Computing, pp. 31- 35.

[13]. Portokalidis, G., Homburg, P., Anagnostakis, K., & Bos, H., (2010). “Paranoid Android: versatile protection for smart-phones”, 26th Annual Computer Security Application Conference (ACSAC). pp. 347-356.

[14]. Samimi, F. A., Mckinley, P. K., & Sadjadi S. M. (2006). “Mobile Service Clouds: A Self-Managing Infrastructure for Autonomic Mobile Computing Services”, Proceedings of the 2nd International Workshop on Self-Managed Networks, Systems & Services (SelfMan), pp. 130-141.

[15]. Satyanarayanan, M. (1996). “Fundamental challenges in mobile computing”, Proceedings of the 5th annual ACM symposium on Principles of distributed computing, pp. 1-7.

[16]. Satyanarayanan, M. (2010). “Mobile computing: the next decade”, Proceedings of the 1st ACM Workshop on Mobile Cloud Computing & Services: Social Networks and Beyond (MCS).

[17]. Shahzad, A., & Hussain, M. (2013). “Security Issues and Challenges of Mobile Cloud Computing”, International Journal of Grid and Distributed Computing, Vol.6(6), pp. 37-50, ISSN: 2005-4262, doi:10.14257/ ijgdc.2013.6.6.04.

[18]. Tayade, D. (2014). “Mobile Cloud Computing : Issues, Security,Advantages, Trends”, International Journal of Computer Science and Information Technologies, Vol. 5(5), pp. 6635-6639, ISSN: 0975-9646.

[19]. Yang, X., Pan, T., & Shen, J. (2010). “On 3G Mobile Ecommerce Platform Based on Cloud Computing”, Proceedings of the 3rd IEEE International Conference on Ubi-Media Computing, pp. 198-201.

[20]. Zhangwei, H., & Mingjun, X (2010). “A Distributed Spatial Cloaking Protocol for Location Privacy”, 2nd Intl Conf on Networks Security Wireless Communications and Trusted Computing (NSWCTC). Vol. 2, pp. 468.

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Article

Risk Assessment Mitigation of Kerberos Protocol Using Public Key Cryptography

M.Muni Babu* , K.V.Siva Prasad Reddy**

*-** Lecturer, Department of Computer Science and Engineering, Jawarhalal Nehru Technological University, Andhra Pradesh, India.

Babu, M. M., and Reddy, K. V. S. P. (2014). Risk Assessment Mitigation of Kerberos Protocol Using Public Key Cryptography. i-manager’s Journal on Cloud Computing,1(4), 19-23. https://doi.org/10.26634/jcc.1.4.3191

Abstract

Kerberos is an authentication service, which provides security over the network. It assumes that the messages can be read, modified and fabricated by an intruder. It does not provide any security against breaches caused by buggy software or poor passwords. The original design and implementation of Kerberos V1 through V4 was the work of three former Athena Project staff members, Steve Miller of Digital Equipment Corporation and Clifford Neuman along with Jerome Saltzer, Technical Director of Project Athena, and Jeffrey Schiller, MIT Campus Network [1][8][10]. It is designed to provide strong authentication for client/server applications by using secret-key cryptography. The Kerberos protocol uses Data Encryption Standard (DES) so that a client can prove its identity to a server (and vice versa) across an insecure network connection. Authentication is one of the important network security aspects nowadays in internet activity, a more secure application for authentication is fairly useful. Kerberos is an authentication service developed as part of Project Athena at MIT. In this paper, three proposed extensions to integrate public-key cryptography into Kerberos in cross realm are outlined and some basic performance comparisons are made between them and also comments were made on the major security issues related to public-key enhancements introduced to the Kerberos Authentication Protocol trust model. Here the authors have given brief introduction to Kerberos and, public-key cryptography is provided for those unfamiliar with these security systems.

References

[1]. J. Kohl, C. Neuman (1993). “The Kerberos Network Authentication Service (V5)”, September 1993, RFC 1510, ACM Digital Library.

[2]. Ian Downard, (2002). “Public-Key Cryptography Extensions into Kerberos”, University of Missouri-Rolla, Department of Electrical and Computer Engineering.

[3]. Carlo Baliello, Alessandro Basso, Cinzia Di Giusto, Hassan Khalil, Daniel Machancoses, (2002). “Kerberos protocol: an overview”, Distributed Systems Fall, pp. 1-12.

[4]. Farhana S. Munnee, Anirudh Jonnavitula, (2007).“Kerberos Using Public Key Cryptography”, GMUECE 646 Fall .

[5]. Harbitter, A. H., Menasce, D.A., (2001). “Performance of Public-key-enabled Kerberos authentication in large networks”, Proceedings 2001 IEEE Symposium on Security and Privacy. S&P 2001, pp. 170-83.

[6]. Downward, Ian (Naval Research Laboratory), (2002). “Public-key cr yptography extensions into kerberos”, IEEE Potentials, Vol. 21, No. 5, DEC/JAN, pp. 30- 34.

[7]. M. Bellovin and M. Merritt, (1994). “Limitations of the Kerberos authentication system”, Computer Commun. Rev., Vol.20, No. 5, pp.1 19-1 32.

[8]. William Stallings, (1999). “Cryptography and Network Security (Principle and Practice)”, Upper Saddle River N.J., Prentice Hall 1999.

[9]. Eman El-Emam, Magdy Koutb, Hamdy Kelash, and Osama Farag Allah, “An Optimized Kerberos Authentication Protocol”, 978 1-4244-5844-8/09, IEEE.

[10]. MIT Kerberos consortium, by the MIT Kerberos Consortium, 2008.

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Research Paper

Managing Overloaded Mechanisms in VM EnvironmentsUsing MVMOD Algorithm

V.Subasri* , M.Thasnima Nasreen, M.Kavitha, C.Divya, N.Rajganesh

- Final Year Students, B.Tech Information Technology, A.V.C College of Engineering, Tamilnadu, India.

Assistant Professor [SL], Department of Information Technology, A.V.C College of Engineering, Tamilnadu, India

Subasri, V., Nasreen, M, T., Kavitha, M., Divya, C., and Rajganesh, N. (2014). Managing Overloaded Mechanisms in VM Environments Using MVMOD Algorithm. i-manager’s Journal on Cloud Computing,1(4), 24-29. https://doi.org/10.26634/jcc.1.4.3192

Abstract

In modern virtualization based compute clouds, applications share the underlying hardware by running in isolated Virtual Machines (VMs). Each VM, during its initial creation, is configured with certain amount of computing resources (such as CPU, memory and I/O). A key factor for achieving economies of scale in a compute cloud is resource provisioning, which refers to allocating resources to VMs to match their workload. Typically, efficient provisioning is achieved by two operations: (1) Static Resource Provisioning: VMs are created with specified size and then consolidated onto a set of physical servers, the VM capacity does not change; and (2) Dynamic Resource Provisioning: VM capacity is dynamically adjusted to match workload fluctuations. In both static and dynamic provisioning, VM sizing is perhaps the most vital step. VM sizing refers to the estimation of the amount of resources that should be allocated to a VM. The objective of VM sizing is to ensure that the VM capacity commensurate with the workload by scheduling. While overbooking wastes costly resources, under-provisioning degrades application performance and may lose customers. In this proposed work, collocated VM provisioning approach is used in which multiple VMs are consolidated and provisioned based on an estimate of their aggregate capacity needs. This work focuses on implementing an autonomic risk-aware overbooking architecture capable of increasing the resource utilization of cloud data centers by accepting more virtual machines than physical available resources. Admission Control and Fuzzy logic functions are used to estimate the associated risk to each overbooking decision.

References

[1]. A. Ali-Eldin, J. Tordsson, and E. Elmroth, (2012). “An adaptive hybrid elasticity controller for cloud infrastructures”, in Proc. of Network Operations and Management Symposium (NOMS), pp. 204–212.

[2]. A. Ashraf, B. Byholm, and I. Porres, (2012). “A sessionbased adaptive admission control approach for virtualized application servers,” in Proc. of Intl. Conference on Utility and Cloud Computing (UCC), pp. 65–72.

[3]. A. Beloglazov and R. Buyya, (2013). “Managing overloaded hosts for dynamic consolidation of virtual machines in cloud data centers under quality of service constraints,” IEEE Transactions on Parallel and Distributed Systems, Vol. 24, No. 7, pp. 1366–1379.

[4]. C. Mastroianni, M. Meo, and G. Papuzzo, (2013). “Probabilistic consolidation of virtual machines in selforganizing cloud data centers,” IEEE Transactions on Cloud Computing, Vol. 1, No. 2, pp. 215–228.

[5]. C. V´azquez, L. Tom´as, G. Moreno, and J. Tordsson, (2013). “A fuzzy approach to cloud admision control for safe over booking,” in Proc. of Intl. Workshop on Fuzzy Logic and Applications (WILF). Springer Verlag, LNCS, pp. 212–225.

[6]. D. Breitgand, Z. Dubitzky, A. Epstein, A. Glikson, and I. Shapira, (2012). “SLA-aware resource over-commit in an IaaS cloud,” in Proc. of 8th Intl. Conference on Network and Service Management (CNSM), pp. 73–81.

[7]. E. Feller, L. Rilling, and C. Morin, (2011). “Energyaware ant colony based workload placement in clouds,” in Proc. of IEEE/ACM 12th Intl. Conference on Grid Computing, pp. 26–33.

[8]. L. Larsson, D. Henriksson, and E. Elmroth, (2011). “Scheduling and monitoring of internally structured services in cloud federations,” in Proc. of IEEE Intl. Symposium on Computers and Communications (ISCC), pp. 173 178.

[9]. L. Tom´as and J. Tordsson, (2013). “Improving Cloud Infrastructure Utilization through Overbooking,” in Proc. of ACM Cloud and Autonomic Computing Conference (CAC).

[10]. L. Wu, S. K. Garg, and R. Buyya, (2012). “SLA-based admission control for a Software-as-a-Service provider in Cloud computing environments,”Journal of Computer and System Sciences, Vol. 78, No. 5, pp.1280 – 1299.

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Research Paper

Multi Layer Encryption Approach to Secure Data and Fine-Grained Access Control in Public Clouds

K.Nethaji Sundar Sukumar* , L. Venkateswara Reddy**

* PG Scholar, Department of Information Technology, Sree Vidyanikethan Engineering College (Autonomous), Andhra Pradesh, India.

** Professor, Department of Information Technology, Sree Vidyanikethan Engineering College (Autonomous), Andhra Pradesh, India.

K.Nethaji Sundar Sukumar and L.Venkateswara Reddy (2014). Multi Layer Encryption Approach to Secure Data and Fine-Grained Access Control in Public Clouds. i-manager’s Journal on Cloud Computing, 1(4), pp.30-35. https://doi.org/10.26634/jcc.1.4.3193

Abstract

Nowadays two layer encryption is the process of enforcing fine-grained access control to the cloud. Sensitive information or secret data transferring in to the cloud by using encryption is an important concept. Under this scenario, data owners encrypt the data to the cloud before uploading them and whenever user credential changes, then reencrypting encryption process takes place. Users register to the data owners and data owners are sending the secret keys of registered users. Data owner is communicating with clouds and users. For this, the authors have proposed an approach known as multi layer encryption, which is used to reduce burden of the overhead work at the data owners. So, in this process, the authors use multi layer encryption approach, whereas the data owners perform a coarse-grained and cloud performs a fine-grained encryption. The authors analyzed this process by using KeyGen algorithm and Attribute Based Group Key Management algorithm.

References

[1]. Mohamed Nabeel and Elisa Bertino, (2014). “Privacy Preserving Delegated Access Control in Public Clouds", IEEE Transactions on Knowledge and Data Engineering, Vol. 26, No. 9, pp. 2268-2280.

[2]. Jian Liu, Kun Huang, Hong Rong, Huimei Wang and Ming Xian (2015). “Privacy-Preserving Public Auditing for Regenerating-Code-Based Cloud Storage”, IEEE Transaction on Information and Security, pp. 1-13.

[3]. Mohamed Nabeel and Elisa Bertino (2014). “Attribute Based Group Key Management”, Transaction on Data Privacy, Vol. 7,No. 3, pp. 309-336.

[4]. M. Nabeel and E. Bertino, (2012). “Privacy Preserving Delegated Access Control in the Storage as a Service Model,” Proc. IEEE Int'l Conf. Information Reuse and Integration (IRI), pp. 645-652.

[5]. E. Bertino and E. Ferrari, (2002). “Secure and Selective Dissemination of XML Documents,” ACM Trans. Information and System Security, Vol. 5, No. 3, pp. 290- 321.

[6]. G. Miklau and D. Suciu, (2003). “Controlling Access to Published Data Using Cryptography,” Proc. 29th Int'l Conf. Very Large Data Bases (VLDB '03), pp. 898-909.

[7]. N. Shang, M. Nabeel, F. Paci, and E. Bertino, (2010). “A Privacy-Preserving Approach to Policy-Based Content Dissemination,” Proc. IEEE 26th Int'l Conf. Data Eng. (ICDE '10), pp. 944-955.

[8]. M.Nabeel, E. Bertino, M. Kantarcioglu, and B.M. Thuraisingham, (2011). “Towards Privacy Preserving Access Control in the Cloud,” Proc. Seventh Int'l Conf. Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom '11), pp. 172-180.

[9]. M. Nabeel, N. Shang, and E. Bertino, (2013). “Privacy Preserving Policy Based Content Sharing in Public Clouds,” IEEE Trans. Knowledge and Data Eng., Vol. 25, No. 11, pp. 2602-2614.

[10]. M. Nabeel and E. Bertino, (2011). “Towards Attribute Based Group Key Management,” Proc. 18th ACM Conf. Computer and Comm. Security, pp. 821-824.

[11]. D. Naor, M. Naor, and J.B. Lotspiech, (2001). “Revocation and Tracing Schemes for Stateless Receivers,” Proc. 21st Ann. Int'l Cryptology Conf. Advances in Cryptology (CRYPTO '01), pp. 41-62.

[12]. J. Li and N. Li, (2006). “OACerts: Oblivious Attribute Certificates,” IEEE Trans. Dependable and Secure Computing, Vol. 3, No. 4, pp. 340-352.

[13]. T. Pedersen, (1992). “Non-Interactive and Information-Theoretic Secure Verifiable Secret Sharing,” Proc. 11th Ann. Int'l Cryptology Conf. Advances in Cryptology (CRYPTO '91), pp. 129-140.

[14]. M. Nabeel and E. Bertino, (2014). “Attribute Based Group Key Management,” to appear in Trans. Data Privacy.

[15]. A. Sahai and B. Waters, (2005). “Fuzzy Identity-Based Encryption,” Proc. 24th Ann. Int'l Conf. Theory and Applications of Cryptographic Techniques (Eurocrypt '05), pp. 457-473.

[16]. M. Pirretti, P. Traynor P. McDaniel, and B. Waters, (2006). “Secure Attribute-Based Systems,” Proc. 13th ACM Conf. Computer and Comm. Security (CCS '06), pp. 99- 11.

[17]. V. Goyal, O. Pandey, A. Sahai, and B. Waters, (2006). “Attribute-Based Encryption for Fine-Grained Access Control of Encrypted Data,” Proc. 13th ACM Conf. Computer and Comm. Security (CCS '06), pp. 89-98.

[18]. J. Bethencourt, A. Sahai, and B. Waters, (2007). “Ciphertext-Policy Attribute-Based Encryption,” Proc. IEEE Symp. Security and Privacy (SP'07), pp. 321-334.

[19]. X. Liang, Z. Cao, H. Lin, and J. Shao, (2009). “Attribute Based Proxy Re-Encryption with Delegating Capabilities,” Proc. Fourth Int'l Symp.Information, Computer, and Comm. Security (ASIACCS '09), pp. 276- 286.

i-manager's Journal on Cloud Computing (JCC)

Current Issue Vol. 11 Issue 1

Most Read

Most Cited

Volume 1 Issue 4 August - October 2014

A Survey about Green Credential Cloud and its Security

T.Jenitha Arun Rejus*

PG Graduate, Department of Computer Science, Archana Institute of Technology, Krishnagiri, India.

Rejus, T. J. A. R. (2014). A Survey about Green Credential Cloud and its Security. i-manager’s Journal on Cloud Computing, 1(4), 1-10. https://doi.org/10.26634/jcc.1.4.3189

Abstract

References

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An Overture of Mobile Cloud Computing and its Applications

D. R. Robert Joan*

Assistant Professor, Mathematics Education, Christian College of Education, Marthandam, Tamil Nadu, India.

Joan, D. R. R. (2014). An Overture of Mobile Cloud Computing and its Applications. i-manager’s Journal on Cloud Computing, 1(4), 11-18. https://doi.org/10.26634/jcc.1.4.3190

Abstract

References

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Risk Assessment Mitigation of Kerberos Protocol Using Public Key Cryptography

M.Muni Babu* , K.V.Siva Prasad Reddy**

*-** Lecturer, Department of Computer Science and Engineering, Jawarhalal Nehru Technological University, Andhra Pradesh, India.

Babu, M. M., and Reddy, K. V. S. P. (2014). Risk Assessment Mitigation of Kerberos Protocol Using Public Key Cryptography. i-manager’s Journal on Cloud Computing,1(4), 19-23. https://doi.org/10.26634/jcc.1.4.3191

Abstract

References

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Managing Overloaded Mechanisms in VM EnvironmentsUsing MVMOD Algorithm

V.Subasri* , M.Thasnima Nasreen**, M.Kavitha***, C.Divya****, N.Rajganesh*****

*-**** Final Year Students, B.Tech Information Technology, A.V.C College of Engineering, Tamilnadu, India. ***** Assistant Professor [SL], Department of Information Technology, A.V.C College of Engineering, Tamilnadu, India

Subasri, V., Nasreen, M, T., Kavitha, M., Divya, C., and Rajganesh, N. (2014). Managing Overloaded Mechanisms in VM Environments Using MVMOD Algorithm. i-manager’s Journal on Cloud Computing,1(4), 24-29. https://doi.org/10.26634/jcc.1.4.3192

Abstract

References

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Multi Layer Encryption Approach to Secure Data and Fine-Grained Access Control in Public Clouds

K.Nethaji Sundar Sukumar* , L. Venkateswara Reddy**

* PG Scholar, Department of Information Technology, Sree Vidyanikethan Engineering College (Autonomous), Andhra Pradesh, India. ** Professor, Department of Information Technology, Sree Vidyanikethan Engineering College (Autonomous), Andhra Pradesh, India.

K.Nethaji Sundar Sukumar and L.Venkateswara Reddy (2014). Multi Layer Encryption Approach to Secure Data and Fine-Grained Access Control in Public Clouds. i-manager’s Journal on Cloud Computing, 1(4), pp.30-35. https://doi.org/10.26634/jcc.1.4.3193

Abstract

References

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V.Subasri* , M.Thasnima Nasreen, M.Kavitha, C.Divya, N.Rajganesh

- Final Year Students, B.Tech Information Technology, A.V.C College of Engineering, Tamilnadu, India.

Assistant Professor [SL], Department of Information Technology, A.V.C College of Engineering, Tamilnadu, India

* PG Scholar, Department of Information Technology, Sree Vidyanikethan Engineering College (Autonomous), Andhra Pradesh, India.

** Professor, Department of Information Technology, Sree Vidyanikethan Engineering College (Autonomous), Andhra Pradesh, India.