Ensuring Security and Privacy Preservation for Cloud Data Services

2016 ◽  
Vol 49 (1) ◽  
pp. 1-39 ◽  
Author(s):  
Jun Tang ◽  
Yong Cui ◽  
Qi Li ◽  
Kui Ren ◽  
Jiangchuan Liu ◽  
...  
Keyword(s):  
Privacy Preservation ◽  
Security And Privacy ◽  
Cloud Data ◽  
Data Services

scholarly journals Adaptive Secure Cross-Cloud Data Collaboration with Identity-Based Cryptography and Conditional Proxy Re-Encryption

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Qinlong Huang ◽  
Yue He ◽  
Wei Yue ◽  
Yixian Yang
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Security And Privacy ◽  
Broadcast Encryption ◽  
Cloud Data ◽  
Identity Based ◽  
Identity Based Cryptography ◽  
And Performance ◽  
Cryptographic Techniques ◽  
Data Collaboration

Data collaboration in cloud computing is more and more popular nowadays, and proxy deployment schemes are employed to realize cross-cloud data collaboration. However, data security and privacy are the most serious issues that would raise great concerns from users when they adopt cloud systems to handle data collaboration. Different cryptographic techniques are deployed in different cloud service providers, which makes cross-cloud data collaboration to be a deeper challenge. In this paper, we propose an adaptive secure cross-cloud data collaboration scheme with identity-based cryptography (IBC) and proxy re-encryption (PRE) techniques. We first present a secure cross-cloud data collaboration framework, which protects data confidentiality with IBC technique and transfers the collaborated data in an encrypted form by deploying a proxy close to the clouds. We then provide an adaptive conditional PRE protocol with the designed full identity-based broadcast conditional PRE algorithm, which can achieve flexible and conditional data re-encryption among ciphertexts encrypted in identity-based encryption manner and ciphertexts encrypted in identity-based broadcast encryption manner. The extensive analysis and experimental evaluations demonstrate the well security and performance of our scheme, which meets the secure data collaboration requirements in cross-cloud scenarios.

scholarly journals A New Secure Model for Data Protection over Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Amr M. Sauber ◽  
Passent M. El-Kafrawy ◽  
Amr F. Shawish ◽  
Mohamed A. Amin ◽  
Ismail M. Hagag
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Data Protection ◽  
Cloud Services ◽  
Security And Privacy ◽  
Storage Model ◽  
Cloud Data ◽  
Security Issues ◽  
Data Owner ◽  
Proposed Model

The main goal of any data storage model on the cloud is accessing data in an easy way without risking its security. A security consideration is a major aspect in any cloud data storage model to provide safety and efficiency. In this paper, we propose a secure data protection model over the cloud. The proposed model presents a solution to some security issues of cloud such as data protection from any violations and protection from a fake authorized identity user, which adversely affects the security of the cloud. This paper includes multiple issues and challenges with cloud computing that impairs security and privacy of data. It presents the threats and attacks that affect data residing in the cloud. Our proposed model provides the benefits and effectiveness of security in cloud computing such as enhancement of the encryption of data in the cloud. It provides security and scalability of data sharing for users on the cloud computing. Our model achieves the security functions over cloud computing such as identification and authentication, authorization, and encryption. Also, this model protects the system from any fake data owner who enters malicious information that may destroy the main goal of cloud services. We develop the one-time password (OTP) as a logging technique and uploading technique to protect users and data owners from any fake unauthorized access to the cloud. We implement our model using a simulation of the model called Next Generation Secure Cloud Server (NG-Cloud). These results increase the security protection techniques for end user and data owner from fake user and fake data owner in the cloud.

Secure Data Validation and Transmission In Cloud and IoT Through Ban Logic And KP-ABE

2021 ◽  
Vol 11 ◽  
Author(s):  
Narander Kumar ◽  
Jitendra Kumar Samriya
Keyword(s):  
Privacy Preservation ◽  
Data Science ◽  
User Authentication ◽  
Ban Logic ◽  
Data Validation ◽  
Security Measures ◽  
Privacy And Security ◽  
Cloud Data ◽  
Control Approach ◽  
User Data

Background: Cloud computing is a service that is being accelerating its growth in the field of information technology in recent years. Privacy and security are challenging issues for cloud users and providers. Obective: This work aims at ensuring secured validation of user and protects data during transmission for users in a public IoT-cloud environment. Existing security measures however fails by their single level of security, adaptability for large amount of data and reliability. Therefore, to overcome these issues and to achieve a better solution for vulnerable data. Method: The suggested method utilizes a secure transmission in cloud using key policy attribute based encryption (KPABE). Initially, user authentication is verified. Then the user data is encrypted with the help of KP-ABE algorithm. Finally, data validation and privacy preservation are done by Burrows-Abadi-Needham (BAN) logic. This verified, and shows that the proposed encryption is correct, secure and efficient to prevent unauthorized access and prevention of data leakage so that less chances of data/identity, theft of a user is the analysis and performed by KP-ABE, that is access control approach. Results: Here the method attains the maximum of 88.35% of validation accuracy with a minimum 8.78ms encryption time, which is better when, compared to the existing methods. The proposed mechanism is done by MATLAB. The performance of the implemented method is calculated based on the time of encryption and decryption, execution time and validation accuracy. Conclusion: Thus the proposed approach attains the high IoT-cloud data security and increases the speed for validation and transmission with high accuracy and used for cyber data science processing.

Glorified Secure Search Schema Over Encrypted Secure Cloud Storage With a Hierarchical Clustering Computation

2019 ◽  
pp. 657-677
Author(s):  
Shweta Annasaheb Shinde ◽  
Prabu Sevugan
Keyword(s):  
Computational Complexity ◽  
Hierarchical Clustering ◽  
Exponential Growth ◽  
Security And Privacy ◽  
Hierarchical Approach ◽  
Text Search ◽  
Huge Amount ◽  
Cloud Data ◽  
Secure Search ◽  
Secure Cloud Storage

This chapter improves the SE scheme to grasp these contest difficulties. In the development, prototypical, hierarchical clustering technique is intended to lead additional search semantics with a supplementary feature of making the scheme to deal with the claim for reckless cipher text search in big-scale surroundings, such situations where there is a huge amount of data. Least relevance of threshold is considered for clustering the cloud document with hierarchical approach, and it divides the clusters into sub-clusters until the last cluster is reached. This method may affect the linear computational complexity versus the exponential growth of group of documents. To authenticate the validity for search, minimum hash sub tree is also implemented. This chapter focuses on fetching of cloud data of a subcontracted encrypted information deprived of loss of idea and of security and privacy by transmission attribute key to the information. In the next level, the typical is improved with a multilevel conviction privacy preserving scheme.

Secure and Privacy Preserving Keyword Search over the Large Scale Cloud Data

2016 ◽  
pp. 200-215
Author(s):  
Wei Zhang ◽  
Jie Wu ◽  
Yaping Lin
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Keyword Search ◽  
Data Encryption ◽  
Privacy Preserving ◽  
Security And Privacy ◽  
Data Utilization ◽  
Cloud Data ◽  
Efficient Resource ◽  
Efficient Data

Cloud computing has attracted a lot of interests from both the academics and the industries, since it provides efficient resource management, economical cost, and fast deployment. However, concerns on security and privacy become the main obstacle for the large scale application of cloud computing. Encryption would be an alternative way to relief the concern. However, data encryption makes efficient data utilization a challenging problem. To address this problem, secure and privacy preserving keyword search over large scale cloud data is proposed and widely developed. In this paper, we make a thorough survey on the secure and privacy preserving keyword search over large scale cloud data. We investigate existing research arts category by category, where the category is classified according to the search functionality. In each category, we first elaborate on the key idea of existing research works, then we conclude some open and interesting problems.

scholarly journals Towards Secure and Privacy-Preserving IoT Enabled Smart Home: Architecture and Experimental Study

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6131
Author(s):  
Mamun Abu-Tair ◽  
Soufiene Djahel ◽  
Philip Perry ◽  
Bryan Scotney ◽  
Unsub Zia ◽  
...  
Keyword(s):  
Experimental Study ◽  
Smart Home ◽  
Privacy Preservation ◽  
Smart Cities ◽  
Security And Privacy ◽  
Test Cases ◽  
Security Threats ◽  
Hardware Implementations ◽  
Cryptographic Algorithms ◽  
Iot Devices

Internet of Things (IoT) technology is increasingly pervasive in all aspects of our life and its usage is anticipated to significantly increase in future Smart Cities to support their myriad of revolutionary applications. This paper introduces a new architecture that can support several IoT-enabled smart home use cases, with a specified level of security and privacy preservation. The security threats that may target such an architecture are highlighted along with the cryptographic algorithms that can prevent them. An experimental study is performed to provide more insights about the suitability of several lightweight cryptographic algorithms for use in securing the constrained IoT devices used in the proposed architecture. The obtained results showed that many modern lightweight symmetric cryptography algorithms, as CLEFIA and TRIVIUM, are optimized for hardware implementations and can consume up to 10 times more energy than the legacy techniques when they are implemented in software. Moreover, the experiments results highlight that CLEFIA significantly outperforms TRIVIUM under all of the investigated test cases, and the latter performs 100 times worse than the legacy cryptographic algorithms tested.

Semantic Multi-Keyword Search over Encrypted Cloud Data with Privacy Preservation

2019 ◽  
Author(s):  
Fei-Ju Hsieh ◽  
Tai-Lin Chin ◽  
Chin-Ya Huang ◽  
Shan-Hsiang Shen ◽  
Chung-An Shen
Keyword(s):  
Privacy Preservation ◽  
Keyword Search ◽  
Cloud Data

Security and Privacy in Big Data Computing

2020 ◽  
pp. 236-256
Author(s):  
Kiritkumar J. Modi ◽  
Prachi Devangbhai Shah ◽  
Zalak Prajapati
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
Security And Privacy ◽  
Comprehensive Overview ◽  
Privacy And Security ◽  
Cloud Data ◽  
Big Data Privacy ◽  
Cloud Data Storage ◽  
Type Data ◽  
Big Data Computing

The rapid growth of digitization in the present era leads to an exponential increase of information which demands the need of a Big Data paradigm. Big Data denotes complex, unstructured, massive, heterogeneous type data. The Big Data is essential to the success in many applications; however, it has a major setback regarding security and privacy issues. These issues arise because the Big Data is scattered over a distributed system by various users. The security of Big Data relates to all the solutions and measures to prevent the data from threats and malicious activities. Privacy prevails when it comes to processing personal data, while security means protecting information assets from unauthorized access. The existence of cloud computing and cloud data storage have been predecessor and conciliator of emergence of Big Data computing. This article highlights open issues related to traditional techniques of Big Data privacy and security. Moreover, it also illustrates a comprehensive overview of possible security techniques and future directions addressing Big Data privacy and security issues.

Sign in / Sign up

Export Citation Format

Share Document