Enhanced Trusted Third Party for Cyber Security in Multi Cloud Storage

2014 ◽  
pp. 525-533
Author(s):  
Naresh Sammeta ◽  
R. Jagadeesh Kannan ◽  
Latha Parthiban
Keyword(s):  
Cyber Security ◽  
Cloud Storage ◽  
Third Party ◽  
Trusted Third Party ◽  
Multi Cloud

scholarly journals Blockchain-based Integrity Verification of Data Migration in Multi-cloud Storage

2021 ◽  
Vol 2132 (1) ◽  
pp. 012031
Author(s):  
Kun Xu ◽  
Weiwei Chen ◽  
Yanan Zhang
Keyword(s):  
Cloud Storage ◽  
Data Integrity ◽  
Third Party ◽  
Data Migration ◽  
Simulation Experiments ◽  
Integrity Verification ◽  
Cloud Broker ◽  
Smart Contract ◽  
Migration Data ◽  
Multi Cloud

Abstract In the process of multi-cloud storage data migration, data integrity is vulnerable to corruption, but the existing data integrity verification schemes for data migration across clouds are not highly reliable. To address this problem, a blockchain-based data integrity verification scheme for migration across clouds is proposed in this paper. In this scheme, a blockchain network is used instead of a third-party auditor. For each migration, a multi-cloud broker will send an integrity verification request to blockchain at three different times, and a smart contract will verify the data integrity according to the RSA-based homomorphic verification tags. Then, the security of the scheme is analyzed. Finally, simulation experiments and tests are conducted on Ethereum, and the results show the feasibility of the scheme.

Issues in security and privacy of big data

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.

A New User-controlled and Efficient Encrypted Data Sharing Model in Cloud Storage

2019 ◽  
Vol 13 (4) ◽  
pp. 356-363
Author(s):  
Yuezhong Wu ◽  
Wei Chen ◽  
Shuhong Chen ◽  
Guojun Wang ◽  
Changyun Li
Keyword(s):  
Data Sharing ◽  
Data Security ◽  
Cloud Storage ◽  
Screening Program ◽  
Original Data ◽  
Third Party ◽  
Active System ◽  
Encrypted Data ◽  
Active User ◽  
User Data

Background: Cloud storage is generally used to provide on-demand services with sufficient scalability in an efficient network environment, and various encryption algorithms are typically applied to protect the data in the cloud. However, it is non-trivial to obtain the original data after encryption and efficient methods are needed to access the original data. Methods: In this paper, we propose a new user-controlled and efficient encrypted data sharing model in cloud storage. It preprocesses user data to ensure the confidentiality and integrity based on triple encryption scheme of CP-ABE ciphertext access control mechanism and integrity verification. Moreover, it adopts secondary screening program to achieve efficient ciphertext retrieval by using distributed Lucene technology and fine-grained decision tree. In this way, when a trustworthy third party is introduced, the security and reliability of data sharing can be guaranteed. To provide data security and efficient retrieval, we also combine active user with active system. Results: Experimental results show that the proposed model can ensure data security in cloud storage services platform as well as enhance the operational performance of data sharing. Conclusion: The proposed security sharing mechanism works well in an actual cloud storage environment.

scholarly journals Distributed data hiding in multi-cloud storage environment

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Leonel Moyou Metcheka ◽  
René Ndoundam
Keyword(s):  
Cloud Storage ◽  
Network Protocols ◽  
Secret Message ◽  
Covert Channel ◽  
Distributed Data ◽  
Comparison Results ◽  
Major Interest ◽  
Cloud Storage Environment ◽  
Audio Video ◽  
Multi Cloud

AbstractClassical or traditional steganography aims at hiding a secret in cover media such as text, image, audio, video or even in network protocols. Recent research has improved this approach called distributed steganography by fragmenting the secret message and embedding each secret piece into a distinct cover media. The major interest of this approach is to make the secret message detection extremely difficult. However, these file modifications leave fingerprints which can reveal a secret channel to an attacker. Our contribution is a new steganography paradigm transparent to any attacker and resistant to the detection and the secret extraction. Two properties contribute to achieve these goals: the files do not undergo any modification while the distribution of the secret in the multi-cloud storage environment allows us to hide the existence of the covert channel between the communicating parties. Information’s are usually hidden inside the cover media. In this work, the covert media is a pointer to information. Therefore the file carries the information without being modified and the only way to access it is to have the key. Experiments show interesting comparison results with remarkable security contributions. The work can be seen as a new open direction for further research in the field.

A Blockchain-Based Multi-Cloud Storage Data Auditing Scheme to Locate Faults

2021 ◽  
pp. 1-1
Author(s):  
Cheng Zhang ◽  
Yang Xu ◽  
Yupeng Hu ◽  
J. Wu ◽  
Ju Ren ◽  
...  
Keyword(s):  
Cloud Storage ◽  
Data Auditing ◽  
Multi Cloud

scholarly journals Producing ‘good enough’ automated transcripts securely: Extending Bokhove and Downey (2018) to address security concerns

2021 ◽  
Vol 14 (1) ◽  
pp. 205979912098776
Author(s):  
Joseph Da Silva
Keyword(s):  
Cyber Security ◽  
English Language ◽  
Negative Impact ◽  
Early Career ◽  
Third Party ◽  
Doctoral Research ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Audio Data

Interviews are an established research method across multiple disciplines. Such interviews are typically transcribed orthographically in order to facilitate analysis. Many novice qualitative researchers’ experiences of manual transcription are that it is tedious and time-consuming, although it is generally accepted within much of the literature that quality of analysis is improved through researchers performing this task themselves. This is despite the potential for the exhausting nature of bulk transcription to conversely have a negative impact upon quality. Other researchers have explored the use of automated methods to ease the task of transcription, more recently using cloud-computing services, but such services present challenges to ensuring confidentiality and privacy of data. In the field of cyber-security, these are particularly concerning; however, any researcher dealing with confidential participant speech should also be uneasy with third-party access to such data. As a result, researchers, particularly early-career researchers and students, may find themselves with no option other than manual transcription. This article presents a secure and effective alternative, building on prior work published in this journal, to present a method that significantly reduced, by more than half, interview transcription time for the researcher yet maintained security of audio data. It presents a comparison between this method and a fully manual method, drawing on data from 10 interviews conducted as part of my doctoral research. The method presented requires an investment in specific equipment which currently only supports the English language.

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