© 2015, IERJ All Rights Reserved Page 1
ISSN 2395-1621 Homomorphic Encryption for Data
Mining in Cloud Security
#1Mr. Sagar M Kale,#2Mr. Ketan Balharpure,#3Mr. Sourabh Bhakkad,#4Mr.Pranav Hendre
#1234Computer Engineering, KJCOEMR, Pune
ABSTRACT ARTICLE INFO
A large, complex, digital data is being generated by many business organizations, industries, e-commerce with high exponential rate is termed as a big data. Big data is difficult to handle, process and analyze using traditional approach. Using cloud services, we can resolve problems like resource sharing, storage capacity, and data transfer bottlenecks etc. But there is a main issue of data security and privacy while storing the big data on cloud. A major threat in Data Mining based attacks, allows an adversary or an unauthorized user to extract valuable and sensitive information by analyzing the results generated from computation performed on the raw data. In order to provide privacy, security for cloud user as well as cloud provider.We proposed a system for secure data mining using well known techniques like homomorphic encryption system, k means clustering etc. In this process flow, cloud server is unaware of data uploaded by the user. And the client only gets the computational results. Through an experimental evaluation, we can maintain correctness and confidentiality of final result.
Keywords: cloud computing, Security, k-means, data mining, encryption.
Article History
Received: :4th January 2016 Received in revised form : 6th January 2016
Accepted: 7th January,2016 Published online : 9th January, 2016
I. INTRODUCTION
Cloud computing is a technology that uses the internet and central remote servers to maintain data and applications. Cloud computing allows consumers and businesses to use applications without installation and access their personal files at any computer with internet access. It frees a user from the concerns about the expertise in the technological infrastructure of the service.
It allows end user and small companies to make use of various computational resources like storage, software and processing capabilities provided by other companies.
The cloud services can be divided into three categories:
Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Amazon, Microsoft, Google are some of the major cloud service providers. Google App Engine (GAE) is a type of PaaS provided by Google which allows web application hosting.
Windows Azure, SQL Azure is some of the services offered by Microsoft providing processing and storage capabilities for large datasets . Amazon Web Services (AWS) including Simple Storage Service (S3), SQS, EC2 are cloud services provided by the Amazon . Thus convenience, on demand measured access, shared easily
configurable computational resources, rapid provisioning, location independence and self-service are some of the major characteristics of a cloud environment .
Problem statement:-The main goal of this article is to provide the security of the data, to take the backup of the data retrieve of the data.
II. RELATEDWORK
A] Data storage security using partially homomorphic Encryption in cloud[1]
In this paper Sunanda Ravindran , Parsi Kalpana, studied partially homomorphic Encryption in cloud.
they are describing two multiplicative homomorphic cryptosystems, how they differ and how we can use them to secure our data and perform operations on the data with the help of ciphertexts.
B] Performance of ring based fully homomorphic Encryption for securing data in cloud computing[2]
© 2015, IERJ All Rights Reserved Page 2 In this paper, the design and implementation of a Fully
Homomorphic Encryption (FHE) scheme based on Ring is reported. Fully Homomorphic Encryption is a good basis to enhance the security measure of untrusted systems or applications that stores and manipulates sensitive data.
C] Homomorphic encryption applied on cloud[3]
In this paper Mr. V. Biksham , Dr. D. Vasumathi, we proposes a method called homomorphic encryption to run operations in cloud encrypted data without decrypting them which will provide same results after computations as if we have worked directly on the plain text.
D] Survey on recent algorithms for privacy preserving data mining [4]
In this paper, a survey on recent researches made on Privacy preserving data mining techniques with Fuzzy logic, neural network learning, secured sum and encryption algorithms is presented. Privacy preserving Data mining is an emerging technology which performs data mining operations in centralized or distributed data in a secured manner to preserve sensitive data. A number of techniques such as randomization, secured sum algorithm and k-anonymity have been suggested in order to perform privacy-preserving data mining.
E] A fully homomorphic encryption Implementation on cloud computing [5]
Fully Homomorphic Encryption is a good basis to enhance the security measures of un-trusted systems or applications that stores and manipulates sensitive data.
The model is proposed on cloud computing which accepts encrypted inputs and then perform blind processing to satisfy the user query without being aware of its content, whereby the retrieved encrypted data can only be decrypted by the user who initiates the request.
This allows clients to rely on the services offered by remote applications without risking their privacy.
F] Homomorphic encryption and it’s security applications [6]
In this article we describe the typical encryption schemes including single-key homomorphic encryption scheme and public key homomorphic encryption scheme and then elaborate its application in the field of security, including the applications in database security, secure multi-party computation and the Internet of things. Finally, we discuss the research direction of homomorphic encryption.
G] An improved k-means clustering algorithm: Step forward for removal of dependency on k [7]
In this paper, we have proposed an algorithm based on the K-Means, but it does not require the number of clusters K as input. The time complexity and quality of the clusters produced by the proposed algorithm is compared with that of original K –Means using two different data sets.
Title Publication Author Facts
Data storage security using partially homomorphic Encryption
in cloud
International Journal of Advanced Research in Computer
Science and Software Engineering, Volume 3, Issue
4, April 2013.
Sunanda Ravindran , Parsi Kalpana
Partially homomorphic Encryption in cloud.
They are describing two multiplicative homomorphic cryptosystems and secure
our data and perform operations on the data.
Performance of ring based fully homomorphic Encryption for securing data in cloud computing
International Journal of Advanced Research in Computer
and Communication Engineering, Vol. 3, Issue 11,
November 2014.
Hemalatha , Dr. R. Manickachezian,
In this paper, the design and implementation of a Fully Homomorphic Encryption (FHE) scheme based on Ring is reported.
Homomorphic encryption applied on cloud
International Journal of Engineering Research and Applications (IJERA) ISSN:
2248-9622 NATIONAL CONFERENCE on
Mr. V. Biksham , Dr. D. Vasumathi
In this proposes a method homomorphic encryption to run operations in cloud encrypted data without decrypting them which
© 2015, IERJ All Rights Reserved Page 3 Developments, Advances &
Trends in Engineering Sciences (NCDATES- 09th & 10th
January 2015).
will provide same results after computations as if we have worked directly
on the plain text.
Survey on recent algorithms for privacy preserving data mining
International Journal of Computer Science and Information Technologies, Vol.
6 (2), 2015, 1835-1840.
S. Selva Ratna , Dr. T.
Karthikeyan
To understand the challenges faced in Privacy preserving data mining and also helps to
identify best techniques suitable for various data
environment A fully homomorphic
encryption Implementation on cloud
computing
International Journal of Information & Computation Technology, ISSN 0974-2239
Volume 4, Number 8 (2014).
Shashank Bajpai , Padmija Shrivastava
It the security measure of untrusted systems or applications that stores and manipulates sensitive
data.
Homomorphic encryption and it’s security
applications
International Journal of Digital Content Technology and its
Applications (JDCTA) Volume6, Number7, April 2012, doi:10.4156/jdcta.vol6.issue7.36.
Xun-yi-Ren,Lin-Juan chen,Hai-Shanwan
In this article we describe the typical encryption schemes including single-
key homomorphic encryption scheme and public key homomorphic
encryption scheme.
An improved k-means clustering algorithm: Step
forward for removal of dependency on k
International conference on reliability, optimization and information technology-icroit
2014, india, feb 6-8 2014.
Anupama chadha,Suresh kumar
K-means has gain popularity because of its
simplicity and speed of classifying massive data
rapidly and efficiently
III. EXISTINGSYSTEM
Data mining can be a serious threat to the cloud security. Specially, to the organizations dealing with the financial, governmental, education or legal issues of people. To maintenance of client privacy along with data privacy in cloud is a major area of concern for the cloud provider as well as cloud user.
© 2015, IERJ All Rights Reserved Page 4 Fig 1: Encryption applied to the Cloud Computing
IV. PROPOSED SYSTEM
We are proposing a system in data mining on the given data using k-means clustering approach while maintaining the privacy of the content at both the host and also preventing the intermediate values to be leaked to the adversary. It is desired that the hosts know their inputs, the final outputs and no intermediate values and increased performance as compared to existing system.
Fig 2: System Architecture
In proposed system we are focusing on security of data on cloud server. For performance improvement we are using K-means as well as RSA algorithms. We are adding extra constrain along with cloud system i.e. Homomorphic
Encryption. We can also proposed public key and private key.
V. FUTURE SCOPE
The proposed approach can further be extended by adding a digital signature or hashing technique to authenticate the third party so as to prevent an adversary from posing as the third party to host’s.
VI. CONCLUSION
Security and privacy is the major issue concerning the clients as well as the providers of cloud services as a lot of confidential and sensitive data is stored in cloud which can provide valuable information to an attacker.
According to author this method solves the privacy issues of the cloud. It assumes that the user data is distributed on two hosts and performs a combined k-means clustering using the Homomorphic encryption system for security purpose so as to prevent any interpretation of intermediate results by an attacker.
VII. ACKNOWLEDGEMENT
We should like to thank Prof. Anjali Bhosle, Assistant professor Computer Engineering department, in KJ College of Engineering And Management Research, Pune, Maharashtra, India for their useful guidelines.
© 2015, IERJ All Rights Reserved Page 5 REFERENCES
[1] Deepti Mittal, Damandeep Kaur, Ashish Aggarwal,
“Secure Data Mining in Cloud using Homomorphic Encryption”. IEEE 2014 Cloud Security.
[2] Sunanda Ravindran , Parsi Kalpana,“Data storage security using partially Homomorphic Encryption in cloud”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 4, April 2013.
[3] Hemalatha , Dr. R. Manickachezian, “Performance of ring based fully homomorphic Encryption for securing data in cloud computing”, International Journal of Advanced Research in Computer and Communication Engineering ,Vol. 3, Issue 11, November 2014.
[4] Mr. V. Biksham , Dr. D. Vasumathi, “Homomorphic encryption applied on cloud”, International Journal of Engineering Research and Applications (IJERA) ISSN:
2248-9622 NATIONAL CONFERENCE on
Developments, Advances & Trends in Engineering Sciences (NCDATES- 09th & 10th January 2015).
[5] S. Selva Ratna , Dr. T. Karthikeyan, “Survey on recent algorithms for privacy preserving data mining”, S.Selva Rathna et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 6 (2) , 2015, 1835-1840.
[6] Shashank Bajpai , Padmija Shrivastava, “A fully homomorphic encryption Implementation on cloud computing”, International Journal of Information &
Computation Technology, ISSN 0974-2239 Volume 4, Number 8 (2014).
[7] Xun-yi-Ren,Lin-Juan chen,Hai-
Shanwan,“Homomorphic encryption and it’s security applications”, International Journal of Digital Content Technology and its Applications(JDCTA) Volume6, Number7, April 2012, doi:10.4156/jdcta.vol6.issue7.36.
[8]Anupama chadha,Suresh kumar, “An improved k- means clustering algorithm: Step forward for removal of dependency on k”,International conference on reliability,optimization and information technology-icroit 2014, india, feb 6-8 2014.
[9]Meer Soheil Abolghasemi,Mahdi Mokarrami Sefidab,Reza Ebrahimi Atani, “Using location based encryption to improve the security of data access in cloud computing”, International Conference on advances in computing, Communications and informatics(ICACCI) 2013.
