Overview

According to Daher and Hajjdiab (2018), the development of cloud computing has made it easier for numerous enterprises all over the world to store vast amounts of data. The scalability and elasticity of cloud computing have made it possible for businesses' Human Resource Management (HRM) systems to store their organizations' crucial information in the cloud. For instance, the Onibere Odunayo Security (OOS-4) model has made it simpler for HRM to store data by having it deployed in the cloud. This has enabled the model to support OOS-4. Software is used in Human Resource Information Systems. This software often combines various human resource activities into a single package. These functions include recruitment, review, administration of benefits, and training. Performance analysis may also be included. The Human Resource Information Systems (HRIS), which are also known as Human Resource Management Systems (HRMS), are available to a wide variety of businesses. It incorporates a strategy approach that comprises storing, collecting, validating, maintaining, and retrieving data required by a specific business about its personnel activities, human resources, and organizational unit attributes (Linthicum, 2018). The data can be retrieved as needed.

Purpose of the research

When a company's essential data is kept in the cloud, it opens the door to a number of potential problems. These problems are mostly associated with the safety of the data, which calls for an exhaustive investigation into the dangers posed by cloud computing (Guo, 2019). In addition, it is vital to have a conversation about the different facets of cloud computing, with the goal of formulating solutions to the specific vulnerabilities that have been found in order to keep the organization's data secure. Concerns with the security of cloud computing include the virtualization of systems and the sharing of resources. According to Linthicum (2018), organizations and service providers of cloud storage should work together to develop solutions for improving cloud storage security that are based on unique security concerns. In addition, cloud human resource managers are equipped with a variety of modules to ensure that all tasks related to human resources are improved. For instance, choosing the appropriate benefit modules guarantees that management will have complete access to the benefit programs offered to employees. According to Xu et al.'s research from 2020, these benefit plans make it simple to implement other methods like adjusting salary schedules, saving for the education of children, and putting money away for medical expenses.

Literature review

According to Guo (2019), human resource management entails educating, recruiting, compensating, and evaluating workers, in addition to providing an acceptable response to their issues over justice, labor relations, and health and safety. Computing in the cloud, on the other hand, refers to a method to information processing in which computing capabilities that are generally handled centrally are typically provided in the form of services. These computing capabilities are typically offered to a variety of user-interfacing devices throughout the network systems in accordance with the individual requirements of each device. Computing in the cloud has given rise to a new facet of information technology, which is centered on the provision of a wide variety of services to clients. It is currently utilizing large amounts of computing power and storage space that is associated with cloud storage service providers in order to make sure that computing is made easier for a variety of customers and that their experience is improved. According to Hussein (2018), cloud computing is defined as a platform that makes a variety of services available to its customers based on the demand of users located all over the world.

According to Daher and Hajjdiab (2018), the top players in the platform, such as Microsoft, Google, and Amazon, are delivering cloud computing services that include platform as a service (PaaS), infrastructure as a service (IaaS), and software as a service (SaaS) for their customers to utilize (PaaS, IaaS, and SaaS). The Platform as a Service (PaaS) architecture gives its users the ability to create and develop their own apps without having to worry about storage or processors. Users of Google App Engine, which is an example of a platform as a service, have the ability to launch their apps using the programming languages Java and Python thanks to Google App Engine. Additionally, cloud computing has the potential to provide a large amount of leverage for use in human resource management systems. This is because there are many enormous datasets that need to be able to be accessed and stored with ease. It makes sure that human resource managers are able to concentrate on the applications, while cloud computing service providers take care of providing the essential facilities (Hussein, 2018).

Many people are concerned about the safety of their data while it is stored in the cloud, and the majority of these debates are centered on the activities that take place in the cloud (Hasan et al., 2020). It was clear that the data as well as the assets consisting of computing equipment and assets needed to be safeguarded. One user of cloud computing may access the databases of other customers using the cloud platform, despite the fact that this presents various opportunities. On the other hand, in order to limit or decrease the number of instances in which other users access data that belongs to other companies or users, the organizations that are utilizing the program are supposed to allocate certain privileges and roles to specific parties. In addition, there has been a rise in the number of attacks that are cloud-based, but strategies and precautions are being developed to prevent incidents of this nature. According to Xu et al.'s research from 2020, the level of data security that is connected with cloud storage should be sufficient to inspire sufficient trust that the platform is safer for enterprises to store their essential data.

Practical applications

Because it provides both local and global security designs that are relevant to military contexts for human resource information systems, the OOS-4 model is extremely important. This is related to the fact that the model is associated with applying sensitive sorts of information due to the presence of multiple levels of protection measures. The OOS-4 was developed to enable departmental and management security levels, where permission is necessary to post and create summary. This was done with the intention of preventing unauthorized access. In a more fundamental sense, the model generates an organization that possesses the appropriate people at the required places at the required time, which is also carried out in an environment that is more secure (Hasan et al., 2020).

According to Xie, 2020, the operational human resource management process, which includes retirement, hiring, training, and deployment, should be carried out in settings that maintain confidentiality and exclude external parties. In addition, strategic human resource management, which provides organizations that are subject to checks with future orientations for their businesses. It also focuses on how management, integrated administrative, and personnel systems ought to be deployed in an effective manner in order to support functional processes both inside and outside the country. For instance, making key information essential for United Nations observation missions available to individuals could lead to intense lobbying on the part of the personnel. The primary purpose that the human resource models provide is to aid in the comprehension and examination of work organization, workforce governance, reward systems, and staffing structures. Management of human resources is an essential function since it plays an important part in fostering positive worker interactions, which are shaped by a variety of different circumstances. According to Ankrah and Sokro (2016), the presence of factors such as these has the potential to significantly impact the level of confidentiality maintained by a system. (Ankrah & Sokro, 2016) The final point is that the human resource system is a data-intensive approach, which means that the records of the organization are typically kept in the form of a database. The database contains all of the records of a specific company that have been captured by the applications. This database is also a typical target for cybercriminals because it contains sensitive company information. It is not always the case that data security is considered until the development of the applications, despite the fact that fixes are issued routinely. The majority of publicly administered human resource management systems either make insufficient use of data encryption or do not use it at all to protect the organization's database. On the other hand, the human resource management system that is available to the public ought to implement data encryption, and Google should make certain that its platforms require apps to be created in programming languages and deployed in runtime environments that are either Python or Java.

On the platform for cloud storage, the applications can be accessed either free domain names or the users' own domains. This will ensure that companies are able to easily manage the human resource information systems thanks to the anonymity that is produced by the cloud storage once the information has been encrypted. This will lead to minimal effects from external variables, which will improve the operations of human resource management (Xie, 2020).

Conclusion

Cloud storage is an essential component of the storage and data protection landscape. The processes of selecting, recruiting, retiring, training, and deploying personnel can all be improved with the help of human resource management in an organization. Because each user's needs are treated uniquely, the cloud storage will provide a level of protection that is superior to that provided by traditional methods. This protection will be provided to the data that is stored there. In most cases, the records that are obtained from the clouds using the applications are in the form of plain text. If you view them from records, they will appear in the form of numbers, which will make it more difficult for persons to gain illegal access to such data and use it. Because of this, it is more difficult for outside forces to access the data of the business and utilize those data to exert influence over the functions of human resource management.

References

• Ankrah, E., & Sokro, E. (2016). Intention and Usage of Human Resource Information Systems among Ghanaian Human Resource Managers. International Journal Of Business And Management, 11(2), 241. https://doi.org/10.5539/ijbm.v11n2p241
• Daher, Z., & Hajjdiab, H. (2018). Cloud Storage Comparative Analysis Amazon Simple Storage vs Microsoft Azure Blob Storage. International Journal Of Machine Learning And Computing, 8(1), 85-89. https://doi.org/10.18178/ijmlc.2018.8.1.668
• GUO, W. (2019). An Analysis of the Innovative Model of Enterprise Information Resource Management Based on "Internet +" and Cloud Computing. Destech Transactions On Social Science, Education And Human Science, (iced). https://doi.org/10.12783/dtssehs/icesd2019/29864
• Hasan, M., E, B., Almamun, M., & K, S. (2020). An Intelligent Machine Learning and Self Adaptive Resource Allocation Framework for Cloud Computing Environment. EAI Endorsed Transactions On Cloud Systems, 6(18), 165501. https://doi.org/10.4108/eai.13- 7-2018.165501
• Hussein, L. (2018). The Relationship Between Information Technology Governance and Human Resource Information Systems Infrastructure. TANMIYAT AL-RAFIDAIN, 37(120), 115- 130. https://doi.org/10.33899/tanra.2018.159991
• Linthicum, D. (2018). Approaching Cloud Computing Performance. IEEE Cloud Computing, 5(2), 33-36. https://doi.org/10.1109/mcc.2018.022171665
• Xie, Q. (2020). Machine learning in the human resource system of the intelligent manufacturing industry. Enterprise Information Systems, 1-21. https://doi.org/10.1080/17517575.2019.1710862
• Xu, Z., Zhang, Y., Li, H., Yang, W., & Qi, Q. (2020). Dynamic resource provisioning for cyber- physical systems in cloud-fog-edge computing. Journal Of Cloud Computing, 9(1). https://doi.org/10.1186/s13677-020-00181-y