# Enhancing Cloud Security--Proactive Threat Monitoring and Detection Using a SIEM-Based Approach
## 2 Related Works
The authors propose a solution for optimizing SIEM throughput on the cloud using parallelization, which can help managed security service providers (MSSPs) to process large amounts of data efficiently and identify security issues quickly. In [29], [PERSON] et al. presented a study on analytical approaches to understanding the overall structure and developments in cloud computing but also discussed the concept of cloud computing security issues in terms of vulnerabilities, threats, and attacks. [PERSON] et al. [30] focused on integrity and confidentiality in cloud-outsourced data. They offered a top-level view of various cryptographic algorithms primarily based on different systems inside the outsourced database security and query authentication. In addition, they proposed a structure that could help in achieving the confidentiality and integrity of query outcomes of the outsourced database. [PERSON] et al. [31] provide valuable insights into leveraging machine learning for intrusion detection in the cloud computing environment. The authors propose an intrusion detection system model leveraging Deep Learning (DL) algorithms, specifically, the Radial Basis Function Neural Network (RBFNN) and Random Forest (RF). Their approach demonstrates improved accuracy and a substantial increase in the Matthews Correlation Coefficient (MCC). According to the authors, integrating this proposed IDS model into cloud environments has the potential to offer cloud providers enhanced security measures, such as minimizing unauthorized access and the risk of data breaches. PADRES, a tool designed for privacy, data regulation, and security, was created in [32] to assist companies in evaluating their compliance with GDPR. The emphasis of the software is the analysis of web applications, which results in a GDPR classification and a report with recommendations for improvement. In addition, the software also has a component that searches for vulnerabilities by integrating open-source scanning tools. However, PADRES did not directly focus on privacy concerns, and the responsibility of designing the inputs still falls on the developer as the compliance assessment questions are answered manually. [PERSON] [33] reviewed and analyzed the existing cloud threats and focused on those that do not apply to traditional systems. They also examined CSPs' security requirements by taking Europe's e-health system as a case study. The reviewed studies emphasize the significance of security in the cloud and highlight SIEM technology as a promising approach to tackling the complex security challenges posed by the dynamic and complex nature of cloud networks. Furthermore, a substantial portion of the reviewed studies predominantly concentrate on exploring security challenges related to Software as a Service (SaaS) models, while relatively fewer studies address security issues specific to Infrastructure as a Service (IaaS) models. While data confidentiality has rightly received considerable attention in the literature, it is crucial to recognize that safeguarding data confidentiality alone is inadequate for upholding the fundamental principles of the CIA triad, which encompasses confidentiality, integrity, and availability. It is undeniable that data confidentiality is a critical aspect of security, yet it is equally crucial to ensure the integrity and availability of cloud-based systems and services. Maintaining data integrity guarantees that data remain accurate, unaltered, and trustworthy throughout their lifecycle, while availability focuses on ensuring uninterrupted access to cloud resources and services. Moreover, the reviewed works have predominantly focused on security aspects; however, it is also important to recognize the significance of compliance as an integral part of an organization's overall security strategy. Ensuring compliance entails verifying that cloud resources adhere to industry standards and regulatory requirements.