Volume-8 , Issue-3 , Mar - 2020 Go Back

Cloud computing which comprises various technologies from Infrastructure to Software services makes users to view computing in a new direction, as it is offering users a better IT services at low-cost. In case of collective usage of resources cloud providers that work collaboratively to form a federation of clouds or Inter-cloud. The federated cloud will address the issues like data availability, data loss, sharing of resources, data security  etc. In case of resource sharing some of the applications require the credentials of the users or data to be shared between the federated clouds, which may lead to misuse of the identity, identification theft, and platform reliability. These issues are to be addressed in the federated cloud environment. An issue of security in cloud computing is an open research issue which also applied for federated clouds. In this paper we discuss some of the issues related to federation clouds and its impact on services are studied, new mechanisms and technique to be designed to reduce the risk is discussed.

Cloud computing,Deployment models, Services,Federation,Security

[1]
National Institute of Standards and Technology specialpublication.no.800-145,
“The NIST definition of cloud computing” Sept. 2011

[2]   Cloud computing. Wikipedia. [online].
Available at 
ttp://en.wikipedia.org/wiki/Cloud_computing.

[3]
Cloud Computing Use Cases, A white paper produced bythe Cloud Computing Use
Case Discussion Group, Version 4.0 [online].Available.
http://cloudusecases.org. July 2010,

[4]
Rajkumar Buyya, Rajiv Ranjan, and Rodrigo N. 
Calheiros,   ”InterCloud: Utility-Oriented
Federation of Cloud  Computing
Environments for Scaling of Application Services”, ICA3PP,2010,Part I, LNCS
6081, Springer, 2010 , pp. 13–31.

[5]
S. Subashini and V. Kavitha, “A survey on security issues in service delivery
models of cloud computing”, Journal of Networkand Computer Applications (2011),
pp. 1-11. doi: 10.1016 /j.jnca.      
2010.07.006

[6]
Cloud Security Alliance, “Security Guidance for Critical Areas of  Focus in Cloud Computing”, V2.1, 2009.

[7]   Federated identity management”,[Online],[Available],http://en.wikipedia.org/wiki/Federated_identity_management
,Dec, 2011,”

[8]
Xiao Zhang; Hong-tao Du; Jian-quan Chen; Yi Lin; Lei-jie Zeng,"Ensure Data
Security in Cloud Storage", Network   
Computing and Information Security (NCIS), InternationalConference
(IEEE),vol.1,14-15 May,2011 pp.284- 287. doi:  
10.1109/NCIS.2011.64

[9]    Tobias Kurze_, Markus Klemsy, David
Bermbachy, Alexander    Lenkz, Stefan
Taiy and Marcel Kunze,” Cloud Federation”,IEEE    Computer society

[10]
M. A. AlZain and E. Pardede, “Using Multi Shares for Ensuring  Privacy in Database-as-a-Service”, 44th
Hawaii, International     Conference on
System Sciences (HICSS),2011,pp 1-9. doi:   
10.1109/HICSS.2011.478

[11]
David Bernstein, DeepakVij, “Intercloud Security Considerations” , 2nd IEEE
International Conference on Cloud Computing Technology and Science, doi:
10.1109/CloudCom.2010.82. doi: 10.1109/ CloudCom. 2010.82

[12].  Eghbal Ghazizadeh, Jamalul-lail Ab Manan
et.al. A Survey on Security Issues of Federated Identity in the Cloud
Computing, 2012 IEEE 4th International Conference on Cloud Computing   Technology and Science,2012.IEEE.

[13]  Paul Watson, Application Security through
Federated Clouds, IEEE Cloud computing,2014.

[14].  K.Venkataramana,Prof M. Padmavathamma,”Threshold
Secure Data Sharing Scheme for Federated Clouds”,International  Journal of Research in Computer Science eISSN
2249-8265  Volume 2 Issue 5 (2012) pp.
21-28

[15]  Attila Kertesz, Gabor Kecskemeti, Zsolt
Nemeth, Marc Oriol, Xavier Franch, “A Holistic Service Provisioning Solution
for Federated Cloud Infrastructures”, S-Cube 2012, Zurich, Switzerland, IEEE

[16]   B. Rochwerger, D. Breitgand, E. Levy, A.
Galis, K. Nagin, I.M. Llorente, R. Montero, Y. Wolfsthal, E. Elmroth, J.
Cáceres, M. Ben-Yehuda, W. Emmerich, F. Galán, “The reservoir model and
architecture for open federated cloud computing”, IBM J. Res. Develop. 53
(2009) 535–545.

[17]   Sakshi kathuria, "A Survey on Security
Provided by Multi-Clouds in Cloud Computing," International Journal of
Scientific Research in Network Security and Communication, Vol.6, Issue.1,
pp.23-27, 2018

[18]
Anitya Kumar Gupta, Srishti Gupta, "Security Issues in Big Data with Cloud
Computing," International Journal of Scientific Research in Computer
Science and Engineering, Vol.5, Issue.6,   
pp.27-32, 2017

[19]  Shaik. Munwar, K. Ramani, K. Madhavi,
"Secure Data Storage Scheme using Blockchain for Federated cloud",
InternationalJournal of Computer Sciences and Engineering, Vol.07, Issue.06,  pp.51-55, 2019

V. Keerthi, T. Anuradha, "A Study on Federation Clouds and its Issues," International Journal of Computer Sciences and Engineering, Vol.8, Issue.3, pp.109-113, 2020.

Sentiment analysis is one of the fastest growing research areas in computer science, making it challenging to keep track of all the activities in the area. In recent years, sentiment analysis has shifted from analyzing online product reviews to social media texts from Twitter and Facebook. Many topics beyond product reviews like stock markets, elections, disasters, medicine, software engineering, etc. extend the utilization of sentiment analysis. This paper discusses in details the various techniques to Sentiment Analysis, so class of sentiment identify accurately. Text mining pre-processing steps were also discussed for generation of features. This paper provides previous researcher work in detail. Challenges of sentiment mining were also summarized. 

Data Mining, Opinion mining, Sentiment analysis, Text Preprocessing

Sukhlal Sangule, Sunil Phulre, "A Survey on Digital Content Sentiment Features and Techniques," International Journal of Computer Sciences and Engineering, Vol.8, Issue.3, pp.114-118, 2020.

Opinion mining has played a momentous role in providing product recommendations to users. An efficient recommendation system helps in improving customer satisfaction and also enhances business. The credibility of purchasing a product highly depends on online reviews. Since not all online reviews are truthful and trustworthy, it is important to develop techniques for detecting review spam, it is possible to conduct review spam detection using various machine learning techniques. We survey the prominent machine learning techniques that have been proposed to solve the problem of review spam detection. This literature survey is done to study the various fake review detection techniques in detail.    

Sentiment Analysis; opinion Mining; Fake reviews; Machine learning; Recommendation Systems

Ashwini M C, M C Padma, "Detection of Fake Reviews through Opinion Mining: A Survey," International Journal of Computer Sciences and Engineering, Vol.8, Issue.3, pp.119-125, 2020.