Toward a big data approach for indexing encrypted data in Cloud Computing

In the existent system, data is encrypted and stored when passed to the cloud. During any operations on the data, it is decrypted and then the computation is done. This decrypted data is vulnerable and prone to be misused. After the computations are done, the data and the result are encrypted and stored back in the cloud. This creates an overhead to the system as well as increases time complexity. With this chapter, the authors aim to reduce the overhead of the systems to perform repeated encryptions and decryptions. This can be done by allowing the computations to happen directly on the encrypted text. The result obtained by performing computations on encrypted data will be the same as the ones done on the original plain text. This new security solution is fully fit for processing and retrieval of encrypted data, effectively leading to the broad applicable project, the security of data transmission, and the storage of data. The work is secured further with additional concepts like probabilistic and time stamp-based encryption processes.

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Security Mechanisms in Cloud Computing-Based Big Data

Research Anthology on Artificial Intelligence Applications in Security ◽

10.4018/978-1-7998-7705-9.ch032 ◽

2021 ◽

pp. 694-724

Author(s):

Addepalli V. N. Krishna ◽

Balamurugan M.

Keyword(s):

Cloud Computing ◽

Big Data ◽

Data Transmission ◽

Time Complexity ◽

Time Stamp ◽

Encrypted Data ◽

Plain Text ◽

System Data

In the existent system, data is encrypted and stored when passed to the cloud. During any operations on the data, it is decrypted and then the computation is done. This decrypted data is vulnerable and prone to be misused. After the computations are done, the data and the result are encrypted and stored back in the cloud. This creates an overhead to the system as well as increases time complexity. With this chapter, the authors aim to reduce the overhead of the systems to perform repeated encryptions and decryptions. This can be done by allowing the computations to happen directly on the encrypted text. The result obtained by performing computations on encrypted data will be the same as the ones done on the original plain text. This new security solution is fully fit for processing and retrieval of encrypted data, effectively leading to the broad applicable project, the security of data transmission, and the storage of data. The work is secured further with additional concepts like probabilistic and time stamp-based encryption processes.

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Security Mechanisms in Cloud Computing-Based Big Data

Advances in Wireless Technologies and Telecommunication - Handbook of Research on the IoT, Cloud Computing, and Wireless Network Optimization ◽

10.4018/978-1-5225-7335-7.ch009 ◽

2019 ◽

pp. 165-195

Author(s):

Addepalli V. N. Krishna ◽

Balamurugan M.

Keyword(s):

Cloud Computing ◽

Big Data ◽

Data Transmission ◽

Time Complexity ◽

Time Stamp ◽

Encrypted Data ◽

Plain Text ◽

System Data

In the existent system, data is encrypted and stored when passed to the cloud. During any operations on the data, it is decrypted and then the computation is done. This decrypted data is vulnerable and prone to be misused. After the computations are done, the data and the result are encrypted and stored back in the cloud. This creates an overhead to the system as well as increases time complexity. With this chapter, the authors aim to reduce the overhead of the systems to perform repeated encryptions and decryptions. This can be done by allowing the computations to happen directly on the encrypted text. The result obtained by performing computations on encrypted data will be the same as the ones done on the original plain text. This new security solution is fully fit for processing and retrieval of encrypted data, effectively leading to the broad applicable project, the security of data transmission, and the storage of data. The work is secured further with additional concepts like probabilistic and time stamp-based encryption processes.

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Lattice-Based Identity-Based Homomorphic Conditional Proxy Re-Encryption for Secure Big Data Computing in Cloud Environment

International Journal of Foundations of Computer Science ◽

10.1142/s0129054117400111 ◽

2017 ◽

Vol 28 (06) ◽

pp. 645-660 ◽

Cited By ~ 6

Author(s):

Chunguang Ma ◽

Juyan Li ◽

Weiping Ouyang

Keyword(s):

Cloud Computing ◽

Big Data ◽

Data Sharing ◽

Homomorphic Encryption ◽

Encryption Scheme ◽

Cloud Environment ◽

Public Cloud ◽

Encrypted Data ◽

Identity Based ◽

Big Data Computing

With the arrival of the era of big data, more and more users begin to adopt public cloud storage to store data and compute data. Sharing large amounts of sensitive data in the public cloud will arouse privacy concerns. Data encryption is a widely accepted method to prevent information leakage. How to achieve the cloud sharing and cloud computing of big data is a challenging problem. Conditional proxy re-encryption can solve cloud sharing, and homomorphic encryption can achieve cloud computing. In this paper, we combine conditional proxy re-encryption with homomorphic encryption to construct a lattice-based identity-based homomorphic conditional proxy re-encryption for secure big data computing in cloud environment. The scheme can not only realize the encrypted data sharing in the cloud, but also can realize the encrypted data computing in the cloud. That is, the homomorphic conditional proxy re-encryption scheme can homomorphically evaluate ciphertexts no matter ciphertexts are “fresh” or re-encrypted (re-encrypted ciphertexts can come from different identities). The constructed scheme modifies the homomorphic proxy re-encryption scheme of Ma et al. We also use the approximate eigenvector method to manage the noise level and decrease the decryption complexity without introducing additional assumptions. At last, we prove that the scheme is indistinguishable against chosen-plaintext attacks, key privacy secure and master secret secure.

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Challenges and Cloud Computing Environments Towards Big Data

International Journal of Scientific Research in Science Engineering and Technology ◽

10.32628/ijsrset207277 ◽

2014 ◽

pp. 203-208

Author(s):

Kiran Kumar S V N Madupu

Keyword(s):

Data Mining ◽

Cloud Computing ◽

Big Data ◽

Technology Development ◽

Computing Environments ◽

Modern Technologies

Big Data has terrific influence on scientific discoveries and also value development. This paper presents approaches in data mining and modern technologies in Big Data. Difficulties of data mining as well as data mining with big data are discussed. Some technology development of data mining as well as data mining with big data are additionally presented.

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Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i7.114 ◽

2017 ◽

Vol 7 (7) ◽

pp. 137

Author(s):

. Monika ◽

Pardeep Kumar ◽

Sanjay Tyagi

Keyword(s):

Cloud Computing ◽

Big Data ◽

Large Data ◽

Workflow Scheduling ◽

Cloud Environment ◽

Computing Environment ◽

Scientific Application ◽

Cloud Computing Environment ◽

Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

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Issues in security and privacy of big data

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i12.482 ◽

2018 ◽

Vol 7 (12) ◽

pp. 1

Author(s):

Shaveta Bhatia

Keyword(s):

Cloud Computing ◽

Big Data ◽

Approximate Method ◽

Biomedical Research ◽

Cyber Security ◽

Data Science ◽

Third Party ◽

Security And Privacy ◽

Security Threats ◽

The Third

The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity. It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

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