I need you to complete case study

Analyze Amazon’s privacy policies and design a service-level agreement you would sign if you were to process confidential data using AWS. Write this service-level agreement

1st post:

Based on the study by Rittinghouse & Ransome (2021),Issues with data breaches, insufficient identity and access management, and insecure interfaces and APIs are some of the major security issues that the Software as a Service (SaaS) cloud delivery model on the public cloud faces. When compared to private infrastructures, the attack surface on public cloud platforms is larger since services are exposed to more people. A public cloud data breach could occur as a result of a shared multi-tenancy environment, where the data of another tenant could be exposed if one tenant’s system is vulnerable. Unauthorised access is a common consequence of poorly implemented security policies or settings, both of which contribute to inadequate identity and access management.

With dedicated security measures and constant monitoring, private infrastructures are better able to ward off potential attacks from outside sources. However, they still face internal threats like insider attacks, which public clouds solve with standardised and robust security mechanisms monitored by cloud providers. Thus, while both systems face similar kinds of threats, the public cloud’s shared and easily available nature exacerbates certain vulnerabilities, necessitating stringent and continuous security measures.

2nd post

The SaaS cloud delivery model on the public cloud faces serious security risks, including insider threats, data breaches, account hijacking, denial of service (DoS) attacks, data loss, insecure APIs, and compliance risks. Because of the multi-tenant nature of these threats, public cloud environments and the broad accessibility of cloud services (Hashizume et al., 2013). Relying on cloud providers’ infrastructure and policies may also result in vulnerabilities due to incorrect configurations or insufficient backup and recovery processes (Popovi? & Hocenski, 2010).

In contrast, traditional service-oriented architecture (SOA) Increased isolation and control over private infrastructure lowers the risk of insider attacks and data breaches (Chow et al., 2009). More stringent network security and authentication procedures reduce the likelihood of account hijacking, and the smaller scale makes DoS attacks less frequent. Organizations are able to maintain total control and put in place customized security measures over backup procedures (Subashini & Kavitha, 2011).

Compliance and legal risks are easier to manage on private infrastructure due to fixed data locations and straightforward audit processes, unlike the dynamic and complex environment of the public cloud (ENISA, 2015). Ultimately, while both deployment models face similar security threats, the nature and impact of these threats differ significantly, necessitating a careful assessment of security needs, regulatory obligations, and resources when choosing the optimal deployment model for SaaS applications (Jensen et al., 2009).

3rd post

The exponential improvement of computer and communication technologies has profound implications for system complexity, impacting various aspects of development, management, and usage. As computing power increases exponentially and communication networks become faster and more reliable, systems can handle larger volumes of data and execute increasingly complex tasks. This enhanced capability leads to the development of more sophisticated software and hardware solutions, enabling systems to perform intricate functions with greater efficiency and accuracy [Moore, G. E. (1965)]. However, this increase in capability also introduces challenges in terms of system complexity. With systems becoming more interconnected and data-centric, ensuring security, integrity, and privacy of information becomes increasingly complex. Heightened security risks, such as cyberattacks and data breaches are more prevalent as systems grow in complexity, requiring robust security measures and vigilant monitoring to mitigate risks effectively [Anderson, R., & Moore, T. (2009)].Furthermore, the rapid pace of technological advancement raises user expectations, driving demand for seamless integration and intuitive interfaces, and high-performance systems. Meeting these expectations requires navigating intricate development processes, employing agile methodologies, continuous integration/continuous deployment (CI/CD) pipelines, and automated testing frameworks. However, managing dependencies, ensuring compatibility, and troubleshooting issues become more challenging as systems become more complex [Larman, C. (2004).]

In conclusion, while the exponential improvement of computer and communication technologies enables the development of more powerful and capable systems, it also introduces complexities that must be addressed. Organizations must carefully balance the benefits of technological advancement with the challenges of managing complex systems and implementing robust security measures, and meeting user expectations to ensure reliability, performance, and security of their systems.

4th post

System complexity has skyrocketed due to the exponential rise of computing and communication capabilities, with far-reaching effects in numerous domains. Complex designs that are hard to maintain and protect are the consequence of systems including more functions, components, and interactions as a result of rapid developments in computer power, data storage, and network capabilities. Enhanced computational capabilities enable the development of more sophisticated applications and services, which in turn necessitate more complex algorithms and data structures (Simon, 2016).

An further layer of complexity is added to an already challenging endeavour by the interconnectedness of modern systems, which require numerous devices and platforms to communicate perfectly. Incorporating state-of-the-art technologies such as AI, ML, and the IoT increases levels of complexity due to the need for real-time processing, analysis, and decision-making. The development of security measures usually lags behind the rate of technological developments, which worsens system vulnerabilities and makes cyber threats more likely. Due to the increased complexity, which impacts the system’s reliability and maintainability, robust design, testing, and troubleshooting methods are essential to ensure optimal performance. The exponential growth of technology has spurred creativity and efficiency, but it has also made it harder to manage and secure ever-more-complex systems.