Integrated Approaches in the Development of Intelligent Information Systems: A Comprehensive Review of Cloud, IoT, Big Data, Machine Learning, and Information Forensics Challenges

Abstract

The rapid evolution of Integrated Information Systems (IIS) has led to a complex convergence of Cloud Computing, Internet of Things (IoT), and Machine Learning (ML). While this synergy enhances computational efficiency, it introduces significant challenges in information forensics and system security. This paper explores the multidimensional security landscape of unified ecosystems, focusing on the vulnerabilities inherent in distributed resources. We analyze the necessity of “Forensic-by-Design” principles and the role of robust biometric solutions in securing e-commerce and integrated environments. Special attention is given to the impact of user interaction variability on speaker recognition performance, as well as the potential of modern IT tools in assessing and optimizing system integrity. By synthesizing recent advancements in MLOps and cloud-native architectures with empirical findings on digital literacy and security technologies, this study provides a strategic framework for developing resilient and accountable intelligent systems. The findings emphasize that technical excellence must be balanced with rigorous forensic standards to mitigate risks in increasingly dynamic, cloud-based infrastructures.