Data Security In Cloud Environment Research Articles

Trust based Reputation Framework for Data Security in Cloud Environment

Cloud computing relies on the Internet and is susceptible to numerous attacks, hence security is the most significant issue.It takes a long time to create trust values for trust authority and cloud servers.Research into trust relationships and trust-based security mechanisms in cloud environments is important because trust has been regarded as a security relationship that is more important than authorization.In a cloud computing environment, trust should exist between cloud users and service providers.As a result, a trust-based reputation framework with fuzzy rules for cloud data security is proposed.The trust values of data centers (DCs) and cloud users (CUs) are independently determined within this framework.The DC examines the CU's reputation and disregards it if it is poor.The user evaluates the serving DC's reputation during transmission to the user and disregards low reputations.The results achieved demonstrate that the trust of the proposed framework performs better.

Data Security in Cloud Environment by Using Hybrid Encryption Technique: A Comprehensive Study on Enhancing Confidentiality and Reliability

Data Security in Cloud Environment by Using Hybrid Encryption Technique: A Comprehensive Study on Enhancing Confidentiality and Reliability

Data security in cloud environment using cryptographic mechanism

Virtual computing resources are provided via a cloud system that is both clever and intelligent. Based on the user's request, computing resources are made available. A hybrid cloud is the best option for storing and accessing user data for cloud deployments. Maintaining security in a hybrid cloud environment is time-consuming. This study provides a novel strategy for securing data in the hybrid cloud by ensuring the user's data is protected. Users' data in a hybrid cloud is protected using cryptographic approaches provided in this approach. Using this strategy, users' data may be protected in public and private clouds using various encryption methods. The suggested data security paradigm offers various advantages to both consumers and providers in terms of data security. Three symmetric encryption methods are offered as a service in the cloud. The concept is implemented as a cloud-based application hosted in the cloud, and the effectiveness of three strategies is assessed. They are evaluated in terms of performance and security. Using the recommended encryption methods in a hybrid cloud environment is more efficient than using other methods. The proposed technique can be used for relational data. It can be modified and enhanced to process multimedia data.

Modeling and simulation of a novel secure quantum key distribution (SQKD) for ensuring data security in cloud environment

In recent days, providing data security over cloud is a complicated process. There are many research works that are developed for authentication based data security over cloud, using cryptographic methods. In contrast, physical rules are used for encrypting data. When the quantum models are appeared, it is called quantum cryptography. And, the key distribution in such models is called, Quantum Key Distribution (QKD). Using QKD in securing data is more effective against several attacks. This paper develops a novel simulation model called Secure Quantum Key Distribution for Cloud Data Security (SQKD-CDS) Model. For encrypting the user data, the simulation model uses Non-Abelian Encryption (NAE) for providing secure data security and, further, the quantum key is used for accessing the stored data from cloud. Moreover, the keys are shared between nodes in secure manner using the quantum channel. This proposed simulation model is evaluated using cloud simulator. The results show that the proposed simulation model outperforms other classical security simulation model in terms of efficiency, time complexity and computational complexity.

Improved Data Security in Cloud Environment for Test Automation Framework and Access Control for Industry 4.0

In analyzing project regressions, automation has emerged as a major agenda in managing changes in software which requires minimum manual intervention. For rapid testing environment, software development processes such as Agile, Scrum, and XP processes depend on continuous integration tools. There is no single tool to handle the project automation, and the main challenge is dependency on multiple tools. The proposed automation tool should support configuration, execution, and debugging facility. Integrating the project automation works such as software configuration management tools Mercurial and Git, job scheduling tools like Jenkins and Apache Continuum, test management tools like TestNG and Selenium need tight integration which is a challenge. The existing PKI infrastructure for access control does not share data among the software tools and processes increasing the complexity when an organization needs to leverage the existing cloud services. The proposed approach optimizes the execution time by taking single CSV with input test case and metadata information and efficiently group and executes the tests automatically. The proposed method includes implementation of security access control mechanism for the jobs execution platform in cloud environment.

A novel model to enhance the data security in cloud environment

Nowadays cloud computing has given a new paradigm of computing. Despite several benefits of cloud computing there is still a big challenge of ensuring confidentiality and integrity for sensitive information on the cloud. Therefore to address these challenges without loss of any sensitive information and privacy, we present a novel and robust model called ‘Enhanced Cloud Security using Hyper Elliptic Curve and Biometric’ (ECSHB). The model ECSHB ensures the preservation of data security, privacy, and authentication of data in a cloud environment. The proposed approach combines biometric and hyperelliptic curve cryptography (HECC) techniques to elevate the security of data accessing and resource preservations in the cloud. ECSHB provides a high level of security using less processing power, which will automatically reduce the overall cost. The efficacy of the ECSHB has been evaluated in the form of recognition rate, biometric similarity score, False Matching Ratio (FMR), and False NonMatching Ratio (FNMR). ECSHB has been validated using security threat model analysis in terms of confidentiality. The measure of collision attack, replay attack and non-repudiation is also considered in this work. The evidence of results is compared with some existing work, and the results obtained exhibit better performance in terms of data security and privacy in the cloud environment.

Preserving Data Security in Cloud Environment Using an Adaptive Homomorphic Blockchain Technique

Preserving Data Security in Cloud Environment Using an Adaptive Homomorphic Blockchain Technique

User Centric Block-Level Attribute Based Encryption in Cloud Using Blockchains

Cloud computing is a collection of distributed storage Network which can provide various services and store the data in the efficient manner. The advantages of cloud computing is its remote access where data can accessed in real time using Remote Method Innovation (RMI). The problem of data security in cloud environment is a major concern since the data can be accessed by any time by any user. Due to the lack of providing the efficient security the cloud computing they fail to achieve higher performance in providing the efficient service. To improve the performance in data security, the block chains are used for securing the data in the cloud environment. However, the traditional block chain technique are not suitable to provide efficient security to the cloud data stored in the cloud. In this paper, an efficient user centric block level Attribute Based Encryption (UCBL-ABE) scheme is presented to provide the efficient security of cloud data in cloud environment. The proposed approach performs data transaction by employing the block chain. The proposed system provides efficient privacy with access control to the user access according to the behavior of cloud user using Data Level Access Trust (DLAT). Based on DLAT, the user access has been restricted in the cloud environment. The proposed protocol is implemented in real time using Java programming language and uses IBM cloud. The implementation results justifies that the proposed system can able to provide efficient security to the data present in and cloud and also enhances the cloud performance.

Block Level Time Variant Dynamic Encryption Algorithm for Improved Cloud Security and Deduplication Using Block Level Topical Similarity

The problem of security and memory management has been well studied. A number of approaches has been discussed for the data security in cloud environment. However, the method does not produce higher security and introduces higher data duplication in the cloud which affects the data management performance. To overcome these issues, an efficient block level encryption and de-duplication scheme has been presented in this paper. The method represents the data into a number of blocks and stores them in the cloud storage. For each block considered, a dynamic encryption/decryption keys has been generated at each time window. The user has been validated with different public/private key approach. For the data access, the algorithm generates different keys for different blocks which restrict the access of users. Based on the key being generated, the data has been encrypted by the system to be decrypted by the cloud user upon access. The method maintains a block key table which contains the keys to be used for the particular time window. The method produces higher efficient results on data security and improves the performance of data management.

Block level time variant dynamic encryption algorithm for improved cloud security and de-duplication using block level topical similarity

The problem of security and memory management has been well studied. A number of approaches has been discussed for the data security in cloud environment. However, the method does not produce higher security and introduces higher data duplication in the cloud which affects the data management performance. To overcome these issues, an efficient block level encryption and de-duplication scheme has been presented in this paper. The method represents the data into a number of blocks and stores them in the cloud storage. For each block considered, a dynamic encryption/decryption keys has been generated at each time window. The user has been validated with different public/private key approach. For the data access, the algorithm generates different keys for different blocks which restrict the access of users. Based on the key being generated, the data has been encrypted by the system to be decrypted by the cloud user upon access. The method maintains a block key table which contains the keys to be used for the particular time window. The method produces higher efficient results on data security and improves the performance of data management.

A Genetic Algorithm based Key Management Approach for Enhancing Data Security in Cloud Environment

A Genetic Algorithm based Key Management Approach for Enhancing Data Security in Cloud Environment

Data Security in Cloud Environment Based on Comparative Performance Evaluation of Cryptographic Algorithms

Data Security in Cloud Environment Based on Comparative Performance Evaluation of Cryptographic Algorithms

Certificateless Bilinear Quantum Mutual Exclusive Signcryption for Data Security in Cloud

Signcryption perform both encryption and signature verification simultaneously with minimum computational time and overhead when compared to that of the traditional signature model. Certificateless Sigcryption rectifies issues corresponding to the key escrow problem and hence reducing the key management in the traditional key cryptography in Cloud environment. There has been some Certificateless Signcryption methods proposed, most of which are proved secured using the proxy pairing operations. However, with proxy pairing found to be computationally difficult in understanding and with the discrete operation reducing the advantages gained from smaller key size, data security is said to be compromised. To address this issue, in this work, a method called, Bilinear Quantum Mutual Exclusive Signcryption (BQ-MES) for data security in cloud environment is presented based on quantum principles. The new method inherits the security of bilinear mapping along with quantum, which possesses lower computation complexity than proxy operations, employed in signcrypting data in cloud environment. In the BQ-MES method, only a designated authorized cloud user recovers the data stored in the cloud via cloud service provider by verifying the validity of a signcrypted data. This is performed using Mutually Exclusive Probability model. Experimental works are conducted on the parameters such as computational time, computational overhead and data security rate. By evaluating the performance with related schemes, results show that the data stored in cloud environment is secured using BQ-MES method and computationally efficient.

Real Time Class Based Encryption for Efficient Data Security in Cloud Environment using User Profile

The data security in cloud has been well studied towards the data present in the cloud environment. Number of techniques has been discussed earlier and each produces different performance results in data security. But still there are gaps in performance in security which should be optimized. To improve the security performance, an efficient class based encryption (CBE) with User profile (UP) is presented. The proposed CBE-UP method groups the cloud data at attribute level based on the importance mentioned in the taxonomy. The data taxonomy covers various information related to the attribute of any data point like their sensitivity, importance in different class and so on. According to the taxonomy, the method estimates the Class Sensitivity Measure (CSM) for each attribute, which has been used to classify the data attribute. Further, for each Attribute class, the method generates different key from the key set and assigns various scheme to perform encryption and decryption. The selection of key and method has been iterated at each time window. The performance of data security has been improved and reduces the network overhead in distribution of keys to the registered users.

Ensure Hierarchal Identity Based Data Security in Cloud Environment

Cloud computing has emerged as a new promising field in the internet. It can be thought as a new architecture for the next generation of IT enterprises. It allows the user to access virtualized resources over the internet which can be dynamically scaled. Here, the owner's data is stored at a distributed data centre, which are responsible for its security constraints such as access control and data transmission to user. As the owner does not have physical access on their own data, the data centres are not trustworthy, this resulted in the cloud data security demand. Today, many cloud service providers (CSPs) are using the asymmetric and public key cryptography (PKG) for authenticating and data security purposes using the digital identity of the user. To this end, this article focuses on cloud data storage and its delivery to authorized user. For this purpose, a hierarchal identity-based cryptography method is used for data security and checking the data integrity, in order to make sure that there is no alteration or modification done by a malicious attacker or CSP for its own benefit.

An Invincible Rudimentary Architecture for Data Security in Cloud Environment Using Multi Cloud

Cloud is a distributed access of shared pool of resources that can provide the efficient service on demand basics to cloud user by the service providers. The important functions of cloud computing are storage and computation. The cloud user can use the cloud functions without any computing resources. Because of the popularity of cloud computing, providing security to the stored data is a major concern. In the literature, there are various works which have been proposed to provide the efficient security to the stored data in cloud environment. This paper provides the details of need of security in cloud environment, various categories of security threats, mechanisms, cloud architecture, multi-cloud and various security algorithms in detailed manner. The main attention of this paper is to point out the works on security in cloud computing, show the proposed architecute of multi cloud instead of single cloud and the way for the future work for the efficient design of cloud secure service system.

AES (Advanced Encryption Standard) Based Cryptography for Data Security in Cloud Environment

AES (Advanced Encryption Standard) Based Cryptography for Data Security in Cloud Environment

Class Based Multi Stage Encryption for Efficient Data Security in Cloud Environment Using Profile Data

The security issues in the cloud have been well studied. The data security has much importance in point of data owner. There are number of approaches presented earlier towards performance in data security in cloud. To overcome the issues, a class based multi stage encryption algorithm is presented in this paper. The method classifies the data into number of classes and different encryption scheme is used for different classes in different levels. Similarly, the user has been authenticated for their access and they have been classified into different categories. According to the user profile, the method restricts the access of user and based on the same, the method defines security measures. A system defined encryption methodology is used for encrypting the data. Moreover, the user has been returned with other encryption methods which can be decrypted by the user using their own key provided by the system. The proposed algorithm improves the performance of security and improves the data security.

A new key generation technique using GA for enhancing data security in cloud environment

Cloud computing is the distributed and centralised network with the collection of systems providing the resources based on pay-per-use. Security is the major issue in the cloud. Protecting the users' data is a critical task in cloud. Traditional cryptographic symmetric algorithms are suitable for storing data in a more secured way. Asymmetric algorithms are preferred for encrypting the keys rather than the data because of its less speed. The technique for generating or selecting the key plays a vital role in securing the data. Genetic algorithm is a powerful tool for solving the most of the optimisation problems. The proposed genetic algorithm is used for generating the best key which satisfies the specified fitness function. The optimal key generated from the proposed genetic algorithm is encrypted with asymmetric addition chaining cryptographic algorithm (ACCA) to make the key strong. This strengthened key can be used for encrypting data.

A new key generation technique using GA for enhancing data security in cloud environment

A new key generation technique using GA for enhancing data security in cloud environment