The main goal of this research paper is to explore the current state of data security systems in the cloud service industry. The research proposal will also analyze the ability of the current systems to combat the ever-evolving threats in the industry. The dissertation will collect data from literary sources that focus on cloud security systems to learn more. The primary research methodology for the dissertation will be a thematic analysis. The proposal will analyze the data collected through a comprehensive thematic analysis that will group the data into three main categories: the current data security threats, the current security framework & the future data security threats. This knowledge will be used to understand the current state of data security, the expected future threats, and the avenues of evolution necessary to combat the same. The research team will use purposive sampling to ensure that the research is conducted on relevant literary sources. The data sourcing, extraction, and indexing processes will be handled professionally to eliminate bias and preferences. The proposal wishes to arrive at a valid and reliable result that provides a complete overview of the current cloud data security domain. In addition to the thematic analysis, the research study also provides a brief overview of the current literature about the topic through an insightful literature review. The research proposal also provides a brief overview of the limitations and ethical considerations that might affect the dissertation process.

Table of Contents Abstract 2 Chapter 1: Introduction 4 Background 4 Problem Statement and Significance 5 Theoretical Framework 6 Researcher’s Positionality 9 Purpose 10 Research Question(s) 10 Significance 11 Definitions 11 Summary 11 Chapter 2: Literature Review 13 Theoretical Foundation 14 Review of Literature 15 Data Security 15 Growth of Cloud Services 17 Security Evolution 17 Gaps in Literature 19 Conclusion 20 Chapter 3: Methodology 22 Introduction 22 Statement of the Problem 22 Research Question(s) 22 Research Methodology 23 Research Design 23 Study Population and Sample Selection 24 Data Collection Methods 25 Data Analysis and Procedures 26 Validity & Reliability 27 Ethical Considerations 27 Limitations 28 Summary 28 References 30

Cloud services have gained a lot of popularity in the current technological era. With the rapid increase in digital adoption, even small and medium organizations are looking to improve their efficiency and revenue through cloud-based services. Rather than a physical on-site server, cloud services are made available via a remote cloud computing system (Zhe et al., 2017). In today's business environment, cloud service providers can be seen as third-party suppliers who help organizations run critical services through their remote cloud servers. This makes cloud services less costly to operate and maintain in the longer run. It is also one of the main reasons organizations are moving towards cloud-based organizational frameworks. Cloud services also provide several other benefits to both the organizations and the consumers. Therefore, cloud services have gained wide recognition among organizations as a desirable addition to the present IT infrastructure (Zhe et al., 2017).

It is essential to understand that cloud services also have several disadvantages, and these disadvantages limit the widespread use of cloud services and the growth of cloud services within organizations. One of the major problems with cloud services is that it is not secure. As mentioned earlier, cloud services are not run from a cloud computing service that is on-site. Therefore, there are several data security risks associated with cloud services. A typical cloud provider does not hold the necessary access keys (Zhe et al., 2017). If an organization does not have a strong user identity, an attacker will compromise the entire organization. Moreover, there is a very high risk that employees and non-technical workers may be left behind when a cloud service is shut down. Therefore, if a cloud service is being disrupted, security is compromised for many organizations (Zhe et al., 2017).

With the increasing demand for digitization, we can see that cloud services will play a significant part in organizations (Shaikh&Modak, 2017). Therefore, it is critical to ensure that the data security risks associated with cloud services need to be addressed and mitigated efficiently. We can see several cloud service providers work towards improving their security practices through user audits and peer reviews and by addressing data breach mitigation techniques and strategies (Shaikh&Modak, 2017). However, most of them could be considered stop-gap measures and not permanent solutions. Since technology is constantly evolving, the nature of threats for the field is also constantly changing. Therefore, it is crucial to thoroughly understand the security risks and look for ways to enable a sustainable data security solution for cloud services (Shaikh&Modak, 2017).

The rapid increase in digitization and the popularity of cloud computing systems have led to most organizations looking at creating a cloud-based operational framework. This combination makes the organizations more susceptible to data security risks (Kumar et al., 2018). The responsibility of mitigating these risks and keeping the organizations' safe falls on the hands of the third-party cloud suppliers. Therefore, these data security risks impact the end organizations and the third-party cloud suppliers. With the increase in cloud service users, they will find it hard to manage cloud systems and mitigate risks immediately. It is also important to note that the data security risks that threaten cloud services vary. This creates a significant problem for cloud service providers (Kumar et al., 2018).

An evaluation of current and future threats against cloud services is a challenge for cloud providers and companies within the industry. This research proposal will explore the current data security risks and analyze the security systems that third-party cloud suppliers have in place to understand the current cloud service environment comprehensively. This will help create sustainable solutions to combat the data security risks and issues (Kumar et al., 2018). With this understanding, cloud service providers will be able to reduce the financial risks and help with data security issues, protect their customers and help solve the data security issues of their cloud-based data services. Another important goal of the dissertation is to learn about the new data security threats emerging in the cloud service sector. The challenge highlighted will be experienced as more organization moves their data to the cloud, demanding a better management model to counter it. Therefore, the research proposal will be focused on understanding and evaluating both the current and emerging threats that threaten the data security of cloud services (Kumar et al., 2018). To ensure that the dissertation is focused, the same will be centered upon answering three essential research questions mentioned below.

R1: What are the current data security issues and risks that threaten an organization’s cloud services?

R2: What are the predicted future trends for the data security issues in organizations?

R3: How can current cloud data security be made more efficient to facilitate tighter data security in organizations?

Cloud services refer to services provided through remote cloud servers that third-party service providers set up. Cloud services have started to gain prominence because of their ability to increase organizational efficiency at minimal costs. Many cloud services are designed around remote storage, which reduces infrastructure and administration costs (Udendhran, 2017). The cloud market provides several potential cloud services, including file sharing and data management/analysis. These cloud services are highly beneficial for organizations from all sectors because they can scale without the burden of enormous costs. Cloud services also enable organizations to study, manage and analyze large data sets without having their servers or data centers. Data centers are expensive as they have higher operational and service costs when compared to cloud computing systems (Udendhran, 2017).

With the help of cloud services, organizations can manage complex business operations, including business logic, risk management, data recovery, and transaction management. We can also clearly see that some new technological advancements and innovations are helping the cloud computing field proliferate (Udendhran, 2017). While this is beneficial for organizations, this rapid growth also increases data security risks. Data security is an integral part of both enterprise and corporate security. Data security at an organizational level can be mitigated and eliminated with the help of solid encryption technologies or security protocols. However, these systems have little effect on cloud data security as the threats are highly varied (Udendhran, 2017).

Cloud data security has been a cause for concern for many years, and there have been several developments in this regard. Cloud service providers have created various measures to ensure the security of the data. Data protection systems are also deployed and maintained within the cloud and the organizational end by several technologies (Udendhran, 2017).For instance, companies have made it mandatory for IT staff to download and use encryption software before passing on crucial data to users.It is also essential to understand what role machine learning can play in incorporating cloud storage platforms. Since the data security threats are constantly evolving, many cloud service providers have incorporated AI-based systems like machine learning to help manage the security risks through threat analysis. These strategies have helped cloud service systems operate efficiently and mitigate data security threats to a level. This is further evidenced by several research papers on the topic (Udendhran, 2017).

However, many literary papers that have explored the concept have shown that the service providers are reacting to the threats rather than proactively creating security systems. While this has worked till now, the reactive data security systems might not keep data secure in the current business environment where most of the companies have started to use digital and cloud-based systems (Giri&Shakya, 2019). With the increase in customers, cloud service providers might find it challenging to efficiently manage their data privacy policies and security measures. Therefore, it is crucial to thoroughly analyze the current data security threats to create standardized systems that provide sustainable security results. It is also essential to use the analysis to predict future data security threats that might increase data protection and monitoring solutions (Giri&Shakya, 2019).

This research proposal will analyze the cloud data security threats to know what data security threats are growing the most and propose solutions for the service providers to help them address these threats and protect the data better. The proposal will also show how cloud service providers could develop the needed technologies to deal with the security issues that they might face in the future (Giri&Shakya, 2019). The proposal will also propose data security risk models that could help cloud service providers understand emerging threats in the cloud service sector. This will help them better protect against new data security threats and render faster resolutions to mitigate new data security threats. The dissertation will primarily collect literary papers on data security risks/threats and cloud-based systems (Giri&Shakya, 2019).

The research proposal will collect data from academic libraries to understand the cloud data security framework better. The proposal will use document analysis on the literary reviews to gain new insights into the cloud data security framework. The data collected through the document analysis will be further explored through thematic analysis. This thematic analysis will be focused on three main categories: the current data security threats, the current security framework & the future data security threats. Future threats are predicted using shreds of evidence present in the literary papers. In addition to exploring the current cloud data security frameworks, the thematic analysis will help predict new threats. The same can be used as a guideline for creating new data security systems. The researchers will also use textual analysis to help determine where new and emerging threats could come from and the best security strategy for dealing with these issues/risks (Akhil et al., 2017).

Therefore, the focus is to help improve the current data security systems present in the cloud service sector. This thematic analysis will also help researchers and professionals in cloud data security. To ensure that the research is up to date, this thematic analysis will look at the most recent literary works in the field of data protection (Akhil et al., 2017).It will then predict and analyze which elements of these works hold up the current cloud data security framework.This will include, for example, the current security frameworks and the current data protection solutions within that framework. The latter two features will help us understand how the current cloud data security framework is failing compared to the current threats.

Cloud computing systems have become a significant part of the society we live in. Hence, it is essential to understand the benefits and challenges present in the same. While researching the topic of cloud computing and its related services, it was clear that data security has become a significant concern for most service providers (Akhil et al., 2017). Even with the development of various technologies and systems to combat security risks and issues, there are still concerns regarding cloud data security. This prompted the researcher to explore the topic in detail. The researcher was also fascinated by the fact that most organizations are moving to digital and cloud-based systems due to the pandemic. Therefore, the impact of a data security breach has become higher in the current society. Thus, the researcher felt that there needs to be an exploration of the future security risks and issues that could threaten cloud service providers (Akhil et al., 2017).

The main goal of the proposal is to explore the efficiency of the current cloud data security systems and understand whether they will handle issues that could arise in the future. The proposal will also provide suggestions and alternatives to improve cloud data security (Kumar et al., 2018).

Cloud data security is not an isolated issue that will affect only select organizations. Since most organizations in society are moving towards a digital-only operation, any data security risk will affect a wide range of companies. This is detrimental for the whole society. Therefore, there needs to be extensive research on the data security systems of service providers rendering cloud computing services (Kumar et al., 2018). In this dissertation, the main focus is understanding the current cloud data security scenario and improving the same with the help of extensive research into the field. To ensure that the dissertation is focused, the same will be centered upon answering three essential research questions mentioned below.

R1: What are the current data security issues and risks that threaten an organization’s cloud services?

R2: What are the predicted future trends for the data security issues in organizations?

R3: How can current cloud data security be made more efficient to facilitate tighter data security in organizations?

As mentioned earlier, a data hack in cloud services would cause significant disruptions in the current society. Data needs to be secured efficiently to ensure that organizations can operate efficiently because of the rapid increase of digitization. Most companies are moving towards a cloud-based infrastructure. With the increasing data flow, security and privacy are of utmost importance. It is considered essential to ensure the security of data and users' privacy from any attack (Zhe et al., 2017).Therefore, it is crucial to create a data security system capable of handling both current and future data security issues. This dissertation aims to contribute significantly to the field by analyzing the data security issues to find emerging data hacking and security-related trends. The research into the domain is significant to improve the data security frameworks of cloud service providers and enhance them to efficiently mitigate future risks in the domain (Zhe et al., 2017).

i. Machine Learning – Machine Learning is a type of Artificial Intelligence that uses systems to learn from data, identify patterns, and make decisions with limited human intervention (Zhe et al., 2017).

ii. Cloud Computing – Cloud computing is a computer system resource that uses on-demand data storage and computing power (Zhe et al., 2017).

Cloud computing systems have started to gain extensive recognition because of the various benefits it provides organizations from several sectors. Cloud services have become a critical tool for organizational growth and significantly