Home / Computer Science / Data storage security in cloud computing

Data storage security in cloud computing

 

Table Of Contents


Chapter ONE

1.1 Introduction
1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Research
1.9 Definition of Terms

Chapter TWO

2.1 Overview of Cloud Computing
2.2 Data Storage in Cloud Computing
2.3 Security Challenges in Cloud Computing
2.4 Encryption Techniques in Cloud Data Storage
2.5 Access Control Mechanisms
2.6 Data Integrity in Cloud Storage
2.7 Authentication in Cloud Computing
2.8 Risk Assessment in Cloud Data Storage
2.9 Compliance and Regulations
2.10 Best Practices in Cloud Data Security

Chapter THREE

3.1 Research Design
3.2 Sampling Techniques
3.3 Data Collection Methods
3.4 Data Analysis Procedures
3.5 Ethical Considerations
3.6 Validity and Reliability
3.7 Research Limitations
3.8 Timeframe and Budget

Chapter FOUR

4.1 Data Security Measures Implemented
4.2 Analysis of Data Breaches
4.3 Impact of Security Measures
4.4 Comparison with Industry Standards
4.5 User Feedback and Satisfaction
4.6 Recommendations for Improvement
4.7 Future Research Directions
4.8 Conclusion of Findings

Chapter FIVE

5.1 Summary of Findings
5.2 Conclusions
5.3 Implications of the Study
5.4 Recommendations
5.5 Contribution to the Field
5.6 Areas for Future Research
5.7 Reflections on the Study
5.8 Closing Remarks

Project Abstract

Abstract
Cloud computing has revolutionized the way data is stored and managed by providing convenient, on-demand access to a shared pool of computing resources over the internet. However, the adoption of cloud storage raises concerns about the security and privacy of the data stored in the cloud. Data storage security in cloud computing is a critical area of research due to the sensitive nature of the data being stored and the potential risks associated with unauthorized access, data breaches, and data loss. This research explores various security challenges and solutions related to data storage in cloud computing environments. The primary focus of this study is to analyze the different security mechanisms and protocols that can be implemented to enhance data storage security in the cloud. Encryption techniques play a vital role in protecting data confidentiality and integrity in cloud storage. By encrypting data before storing it in the cloud, organizations can ensure that even if unauthorized parties gain access to the stored data, they cannot decipher the information without the encryption key. Additionally, access control mechanisms such as role-based access control (RBAC) and attribute-based access control (ABAC) can help prevent unauthorized users from viewing or modifying sensitive data in the cloud. Data redundancy and backup strategies are essential components of data storage security in cloud computing. Redundancy ensures that data is replicated across multiple servers or data centers, reducing the risk of data loss due to hardware failures or system errors. Regular data backups further protect against data loss by enabling organizations to restore their data to a previous state in the event of a security incident or data corruption. Furthermore, this research investigates the importance of monitoring and auditing mechanisms in cloud storage security. Real-time monitoring of user activities and data access can help detect suspicious behavior and potential security threats in the cloud environment. Auditing tools provide organizations with insights into who accessed the data, when it was accessed, and what actions were taken, facilitating compliance with data protection regulations and internal security policies. In conclusion, data storage security in cloud computing is a multifaceted issue that requires a combination of technical, organizational, and procedural measures to mitigate risks and ensure the confidentiality, integrity, and availability of data in the cloud. By implementing robust security controls, encryption techniques, access controls, data redundancy, backup strategies, and monitoring mechanisms, organizations can strengthen the security of their data storage in cloud environments and build trust with their customers and stakeholders.

Project Overview

1.2     Background of Study

Several trends are opening up the era of Cloud Computing, which is an Internet-based development and use of computer technology. The ever cheaper and more powerful processors, together with the software as a service (SaaS) computing architecture, are transforming data centers into pools of computing service on a huge scale. The increasing network bandwidth and reliable yet flexible network connections make it even possible that users can now subscribe high quality services from data and software that reside solely on remote data centers.

Moving data into the cloud offers great convenience to users since they don’t have to care about the complexities of direct hardware management. The pioneer of Cloud Computing vendors, Amazon Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2) are both well known examples. While these internet-based online services do provide huge amounts of storage space and customizable computing resources, this computing platform shift, however, is eliminating the responsibility of local machines for data maintenance at the same time. As a result, users are at the mercy of their cloud service providers for the availability and integrity of their data. Recent downtime of Amazon’s S3 is a good example. From the perspective of data security, which has always been an important aspect of quality of service, Cloud Computing inevitably poses new challenging security threats for number of reasons.

Firstly, traditional cryptographic primitives for the purpose of data security protection cannot be directly adopted due to the users’ loss control of data under Cloud Computing. Therefore, verification of correct data storage in the cloud must be conducted without explicit knowledge of the whole data. Considering various kinds of data for each user stored in the cloud and the demand of long term continuous assurance of their data safety, the problem of verifying correctness of data storage in the cloud becomes even more challenging. Secondly, Cloud Computing is not just a third party data warehouse. The data stored in the cloud may be frequently updated by the users, including insertion, deletion, modification, appending, reordering, etc. To ensure storage correctness under dynamic data update is very important. However, this dynamic feature also makes traditional integrity insurance techniques futile and entails new solutions. Last but not the least, the deployment of Cloud

Computing is powered by data centers running in a simultaneous, cooperated and distributed manner. Individual user’s data is redundantly stored in multiple physical locations to further reduce the data integrity threats. Therefore, distributed protocols for storage correctness assurance will be of most importance in achieving a robust and secure cloud data storage system in the real world. However, such important area remains to be fully explored in the literature.

1.3   Statement of Problem

Cloud computing as a new innovation and ultimate solution for utility and distributed computing on Web Applications has been used by billions of users across the globe since its inception. Its implementation and impact cut across several fields, disciplines and businesses across the globe. Nevertheless, cloud computing have been bedeviled by certain obstacles, the goal of this research study is to discern the factors affecting performance and provide some solutions or guidelines to cloud users that might run into performance problems:

1. Integrity and protection of information deployed or stored in the cloud domain as opposed to the traditional approach of information storage.

2.           Ability to transform data from diverse sources into intelligence and deliver intelligence information to right users and systems.

3.           The need for load balancing and traffic control when multiple users access the cloud service.

4.           Need to address the scalability issue: Large scale data, high performance computing, automaton, response time, rapid prototyping, and rapid time to production.

5.           Security, privacy and trust issues from the end users of cloud services.

6.           Adopting cloud as a platform to enhance a vibrant business intelligence environment.

1.4 Aim and Objectives

The aim of the research work is to design a data storage security system that provides solution to factors affecting performance, security and reliability in the cloud computing domain.

This research study has the following objectives:

1.           To offer a controlled approach for the problem of security, privacy and trust issues from the end users of cloud services.

2.           To offer a benchmark for the amount of resources users can store in the cloud service which solves the problem of scalability and load balancing.

3.           To offer provision of on-demand utility to users of the cloud service at a quick response time.

1.5 Significance of the Study

The application of Information technology cuts across every facet of human endeavor (Izevbizua, 2013). The significance of this research study is:

1.   It offers guarantee on the quality of cloud computing services.

2.   It offers an easy information sharing platform for the users.

3.   It highlights and solves the problem of multi-tenancy (where a single application instance may serve hundreds of users or subscribers).

4.   It offers a measured security of information stored in the cloud domain.

1.6 Limitations of the Study

This study is constrained by certain factors which constitute limitations of the study:

1.           The problem of data size limit assign to subscribers of the system may not allow users to deploy as much resources as they desire to store and share among other users.

2.           The expense of acquiring a space on the cloud service provider was tasking initially. This lead to the concentration of the study to some restricted scope.

3.           The measure of resource security within the cloud domain may not suit users; which gives room for improvement of resource security in further research.

1.7 Definition of Terms

Server: It is any combination of hardware or software designed to provide services to clients.

Client: It requests and consumes the services provided by another having the role of server.

Virtualization: It is the ability to separate the OS from the hardware that operates it.

Private Cloud: It is an approach for designing, implementing and managing servers, applications and data center resources by reducing complexity, increasing standardization and automation, and provide elasticity.

Web Application: It is any software application that depends on the Web for its correct execution.

PHP: Hypertext Preprocessor is a server-side scripting language designed for web development as well as general purpose programming language.

DBMS: Database Management System is a computerized record keeping system that comprises collection of data organized to service many applications at the same time



Blazingprojects Mobile App

πŸ“š Over 50,000 Project Materials
πŸ“± 100% Offline: No internet needed
πŸ“ Over 98 Departments
πŸ” Software coding and Machine construction
πŸŽ“ Postgraduate/Undergraduate Research works
πŸ“₯ Instant Whatsapp/Email Delivery

Blazingprojects App

Related Research

Computer Science. 4 min read

Predicting Disease Outbreaks Using Machine Learning and Data Analysis...

The project topic, "Predicting Disease Outbreaks Using Machine Learning and Data Analysis," focuses on utilizing advanced computational techniques to ...

BP
Blazingprojects
Read more β†’
Computer Science. 4 min read

Implementation of a Real-Time Facial Recognition System using Deep Learning Techniqu...

The project on "Implementation of a Real-Time Facial Recognition System using Deep Learning Techniques" aims to develop a sophisticated system that ca...

BP
Blazingprojects
Read more β†’
Computer Science. 3 min read

Applying Machine Learning for Network Intrusion Detection...

The project topic "Applying Machine Learning for Network Intrusion Detection" focuses on utilizing machine learning algorithms to enhance the detectio...

BP
Blazingprojects
Read more β†’
Computer Science. 4 min read

Analyzing and Improving Machine Learning Model Performance Using Explainable AI Tech...

The project topic "Analyzing and Improving Machine Learning Model Performance Using Explainable AI Techniques" focuses on enhancing the effectiveness ...

BP
Blazingprojects
Read more β†’
Computer Science. 3 min read

Applying Machine Learning Algorithms for Predicting Stock Market Trends...

The project topic "Applying Machine Learning Algorithms for Predicting Stock Market Trends" revolves around the application of cutting-edge machine le...

BP
Blazingprojects
Read more β†’
Computer Science. 4 min read

Application of Machine Learning for Predictive Maintenance in Industrial IoT Systems...

The project topic, "Application of Machine Learning for Predictive Maintenance in Industrial IoT Systems," focuses on the integration of machine learn...

BP
Blazingprojects
Read more β†’
Computer Science. 2 min read

Anomaly Detection in Internet of Things (IoT) Networks using Machine Learning Algori...

Anomaly detection in Internet of Things (IoT) networks using machine learning algorithms is a critical research area that aims to enhance the security and effic...

BP
Blazingprojects
Read more β†’
Computer Science. 2 min read

Anomaly Detection in Network Traffic Using Machine Learning Algorithms...

Anomaly detection in network traffic using machine learning algorithms is a crucial aspect of cybersecurity that aims to identify unusual patterns or behaviors ...

BP
Blazingprojects
Read more β†’
Computer Science. 4 min read

Predictive maintenance using machine learning algorithms...

Predictive maintenance is a proactive maintenance strategy that aims to predict equipment failures before they occur, thereby reducing downtime and maintenance ...

BP
Blazingprojects
Read more β†’
WhatsApp Click here to chat with us