Data Storage Security In Cloud Computing

5 Chapters

90 Pages

13,358 Words

Communications Technology | Computer Science | Computer/IT

Data storage security in cloud computing is a multifaceted challenge encompassing various measures to protect sensitive information stored in remote servers. Key considerations include encryption techniques to safeguard data both at rest and in transit, robust access controls to limit unauthorized entry to data repositories, stringent authentication mechanisms to ensure only authorized users can access the stored data, and comprehensive data loss prevention strategies to mitigate risks of accidental or malicious data breaches. Additionally, adherence to regulatory compliance standards such as GDPR, HIPAA, or PCI DSS is essential for maintaining legal and regulatory obligations regarding data protection and privacy. Continuous monitoring, threat detection, and incident response capabilities are crucial components of a comprehensive security framework in cloud-based storage environments to detect and mitigate evolving threats effectively. Collaboration between cloud service providers and clients is imperative to establish shared responsibility for security and ensure alignment with best practices in data storage security.

ABSTRACT

Cloud computing provides high performance, efficient utilization, and on-demand availability of resources which can be accessed from different locations concurrently. However, the cloud environment is vulnerable to different kinds of attacks which involve installing malicious software which creates backdoors or excess file uploads which creates brutal force attacks and slows down the server. In a cloud environment, where businesses have hosted important and critical data, the security of the stored files becomes crucial. To mitigate the threat to cloud environments, Cloud Security Systems (CSS) comes as a layer of defense. Although it is not a new technology, some drawbacks have been identified in the existing CSS designs, which results in low performance due to network congestion and less data efficiency. Our developed system offers a controlled approach for the problem of security, privacy and trust issues from the end users of cloud services by putting up a benchmark for the amount of resources users can store in the cloud service which solves the problem of scalability and load balancing. It offers provision of on-demand utility to users of the cloud service at a quick response time. This system was designed using Java programming language. We also used Unified Modeling Language as a tool to design the system, which helps in reducing the design complexity.

The Abstract of “Data Storage Security In Cloud Computing” ends here.

CHAPTER ONE

INTRODUCTION
1.1 Introduction
Cloud Computing is a new paradigm of computing which has evolved in recent times, it’s a platform where hardware and software are delivered to users in a manner that resembles the way utilities such as electricity are delivered to households today (Flanagan, 2002). Cloud computing is an online form of computing where users can access applications (especially, Web-Based Applications) via a web-browser, while the application is installed and stored on a data center which comprises several servers.

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.

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Overview of Cloud Computing and Data Storage

Cloud computing revolutionizes the way data is stored, processed, and accessed. Instead of relying on local servers and infrastructure, cloud services offer on-demand access to computing resources over the internet. These resources include storage, processing power, and applications, allowing users to scale their operations efficiently and cost-effectively.

In cloud computing, data storage typically involves storing information in remote data centers managed by CSPs. These data centers may be located in different geographical regions, providing redundancy and disaster recovery capabilities. Data storage services offered by CSPs range from simple object storage to sophisticated databases and data warehouses.

Security Challenges in Cloud Data Storage

While cloud computing offers numerous benefits, it also introduces unique security challenges. Some of the key security concerns related to data storage in the cloud include:

Data Breaches: Unauthorized access to sensitive data stored in the cloud can result in data breaches, leading to financial losses, reputational damage, and legal repercussions.
Data Loss: Data stored in the cloud may be vulnerable to accidental deletion, corruption, or loss due to hardware failures, natural disasters, or malicious activities.
Insider Threats: Employees of the CSP or malicious insiders may misuse their privileges to access or manipulate stored data for nefarious purposes.
Shared Infrastructure: Cloud environments often involve shared infrastructure, where multiple tenants share the same physical resources. This multi-tenancy model raises concerns about data isolation and integrity.
Compliance and Regulatory Requirements: Organizations operating in regulated industries must comply with various data protection regulations and industry standards, such as GDPR, HIPAA, PCI DSS, etc. Ensuring compliance in the cloud requires robust security controls and monitoring mechanisms.

Best Practices for Securing Cloud Data Storage

To address these security challenges and mitigate risks associated with cloud data storage, organizations can implement the following best practices:

Encryption: Encrypting data at rest and in transit helps protect against unauthorized access. Use strong encryption algorithms and key management practices to safeguard sensitive information.
Access Control: Implement granular access controls and authentication mechanisms to restrict access to data based on user roles, permissions, and least privilege principles. Use multi-factor authentication (MFA) for added security.
Data Segregation: Segregate sensitive data from non-sensitive data and use logical and physical controls to enforce segregation between different tenants in a multi-tenant environment.
Data Backup and Recovery: Implement regular data backup procedures and test the recovery process to ensure data integrity and availability in the event of data loss or disaster.
Security Monitoring and Logging: Deploy security monitoring tools and establish comprehensive logging mechanisms to detect suspicious activities, unauthorized access attempts, and other security incidents.
Regular Security Audits and Compliance Checks: Conduct regular security audits, vulnerability assessments, and compliance checks to identify and remediate security gaps proactively.
Vendor Due Diligence: Perform thorough due diligence when selecting a cloud service provider, considering factors such as security certifications, compliance commitments, data protection mechanisms, and incident response capabilities.
Security Awareness and Training: Educate employees, contractors, and stakeholders about security best practices, data handling policies, and potential security threats to promote a security-aware culture within the organization.

Emerging Trends in Cloud Data Storage Security

As technology evolves, new trends and innovations shape the landscape of cloud data storage security. Some notable emerging trends include:

Zero Trust Architecture: Zero Trust security model assumes that no entity, whether inside or outside the network, should be trusted by default. Adopting a Zero Trust approach involves verifying identities, enforcing least privilege access, and continuously monitoring for anomalous activities.
Confidential Computing: Confidential computing technologies, such as hardware-based encryption and secure enclaves, enable organizations to process and analyze sensitive data in encrypted form, even while in use, protecting data confidentiality and privacy.
Homomorphic Encryption: Homomorphic encryption allows computations to be performed on encrypted data without decrypting it first, preserving data confidentiality while enabling secure data processing and analysis in the cloud.
Blockchain for Data Integrity: Blockchain technology provides a tamper-evident and decentralized ledger for recording data transactions, enhancing data integrity and auditability in cloud environments.
AI-driven Security Analytics: Leveraging artificial intelligence (AI) and machine learning (ML) algorithms for security analytics enables proactive threat detection, anomaly detection, and automated incident response in cloud data storage systems.
Edge Computing Security: As edge computing becomes more prevalent, securing distributed edge devices and data processing nodes becomes increasingly important to protect against edge-related security threats and vulnerabilities.

Conclusion

Data storage security in cloud computing is a multifaceted challenge that requires a holistic approach encompassing encryption, access control, data segregation, monitoring, and compliance. By implementing best practices, staying abreast of emerging trends, and collaborating with trusted cloud service providers, organizations can enhance the security posture of their cloud data storage environments and mitigate the risks associated with storing sensitive information in the cloud. Continuous vigilance, proactive risk management, and a security-first mindset are essential to safeguarding data integrity, confidentiality, and availability in the cloud.