## 5 Discussion and Conclusions  
The essential aim of this work was to execute a comprehensive article review on Cloud, Edge, and Fog paradigms, respectively, with a special focus on identifying similarities, differences, attacks, and countermeasures based on security and privacy aspects. Cloud, Edge, and Fog paradigms create a substantial heterogeneous quantity of data capable of being managed over a centralized or distributed system. Looking at the discussions presented in this work, we deduced that the security and privacy issues on the heterogeneity of this ecosystem are a significant challenge. Data transfer from one end to another opens a way for many security and privacy vulnerabilities, even though some of these weaknesses can be detected and eliminated quickly. Solutions cannot be swiftly deployed to user devices simply because of the complexity of the ecosystem. However, IDS mechanisms are largely significant for different paradigms, as some are considered effective in countering DoS/DDoS attacks (Zero-day-attack). In certain scenarios, IDS mechanisms introduce gateway devices to provide higher processing power if needed. Security and privacy are considered primary drawbacks, limiting several institutions and organizations to adopt computational offloading technology. As mentioned earlier, these paradigms face different security and privacy threats, but the most outstanding are DoS/DDoS attacks. For instance, Cloud customers can suffer heavily if Cloud services and resources are breached for a moment by attackers. Cloud systems encounter high latency and high costs in communication and data storage. These issues are present because of the centralized nature of the Cloud and its geographical distance from end-devices that produce data. To resolve these shortcomings in the Cloud, Edge Computing was introduced as a Cloud Computing extension. As identified during the review, Edge provides much less latency than Cloud platform to end-devices; thus, there is a rapid drop in security when migrating from the Cloud platform to the Edge platform due to the Edge network being decentralized (distributed) in nature. Furthermore, observing the migration of data to end-devices from Cloud platform via Edge network, the storage capacity sharply reduces. There is also a rapid decrease in real-time operations as data moves from end-devices via the Edge platform to the Cloud platform. For longer storage needs, a Cloud platform is used. Storage or processing of data from the end-devices occurs in the Edge platform. Despite the emerging of Edge Computing, vulnerabilities and threats still exist, and this, therefore, calls for strict measures with enhanced security and privacy techniques. Fog paradigm was considered to ameliorate Cloud and Edge paradigms. As with the Edge paradigm, Fog is rendering services (computation, networking, data storage, etc.) closer to the end-devices rather than moving data to the Cloud platform but in a distributed manner. However, the introduction of the Fog paradigm is seen to improve the infrastructural network to match the demands of large data quantity while enhancing the processing strength efficiently. Fog paradigm can improve mobility, complexity in a distribution environment, location identity, real-time response, as well as security and privacy. The fog paradigm does not depend on the Cloud data center but instead relies on end-devices to store and process its data. Broader availability of node access gives some level of flexibility to the applications. Like the Fog paradigm, the Edge paradigm also permits computation handling at the network edge, near where data are generated. What makes the Fog paradigm different from the Edge paradigm is its ability for Fog nodes to interconnect, while the Edge paradigm operates with separate Edge nodes. Confidentiality, integrity, and availability are information systems' most significant security and privacy properties. The transfer and storage of data must be confidential, with integrity, and made available.