An in-depth evaluation of Hybrid Access Mechanisms for Real Time Big Data Environments from an empirical perspective

Abstract

  In the fast-paced digital world, real-time software environments such as cloud, fog deployments, and workstations are increasingly becoming vital for a multitude of applications. However, securing these environments is a significant challenge owing to the dynamic and complex nature of real-time data and processes. Existing models often fall short in addressing these challenges effectively, being limited by factors such as scalability, flexibility, and inability to adapt to ever-evolving cyber threats. In this paper, we present an in-depth evaluation of Hybrid Access Mechanisms (HAM) combined with Machine Learning (ML) based models for securing real-time software environments. Through a comprehensive review and empirical analysis, we investigate the effectiveness and performance of various models in securing these environments. Our analysis is conducted across a range of performance metrics including latency, throughput, accuracy, and resource utilization, thereby providing a holistic perspective on the optimal models suitable for real-time deployments. The proposed review brings forth the advantages of integrating HAM and ML models with big data, highlighting their capabilities in providing a robust and adaptive security framework that can effectively mitigate modern cyber threats while ensuring optimal performance. We demonstrate how these models can be fine-tuned to cater to the specific needs of real-time environments, thereby providing a tailored security solution that enhances the overall security use cases. The impacts of this work are manifold. By identifying the optimal models for securing real-time software environments, we provide valuable insights that can guide practitioners and researchers in the field of cybersecurity. Furthermore, our findings lay a solid foundation for future research, paving the way for the development of innovative security solutions that can effectively counteract the ever-evolving landscape of cyber threats. Ultimately, this research contributes significantly to the body of knowledge in cybersecurity, providing a comprehensive and empirical-based evaluation that is crucial for safeguarding the digital world scenarios.