Analyzing Traffic Behavior in IoT-Cloud Systems : A Review of Analytical Frameworks

The tasks of the network administrator will be to monitor the numerous applications running on the network and perform a deep analysis of the network traffic. This encompasses tasks such as anomaly detection, network surveillance, and system optimization to derive meaningful information about network traffic. The article explores IoT-cloud designs in detail, examining their performance against network traffic and identifying critical security objectives. It looks at different traffic analysis methods, packet, flow statistics, and behavior modeling and looks at key security threats sarcastically, Distributed Denial of Service (DDoS), phishing, and SQL injection attacks. The paper further describes the most important security objectives that are needed to defend IoT-cloud environments, including confidentiality, integrity, and availability and reviews various cyber threats, like DDoS, man-in-the-middle, phishing, as well as SQL injection threat. Based on a literature review, this paper examines modern tools and techniques to implement traffic monitoring and anomaly detection, outlining their advantages and drawbacks in the existing solutions. By methodologically reviewing recent developments, the article will help researchers and practitioners to innovate more secure and smarter systems to conduct IoT-cloud traffic analysis.