Reviewing Threat Detection Methods in SaaS Platforms Through the Use of Adaptive Cloud Security Models

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Year : 2025 | Volume : 12 | 03 | Page :
    By

    Nilesh Jain,

  1. Associate Professor, Department of Computer Sciences and Applications Mandsaur University Mandsaur, Daulatpura, Madhya Pradesh, India

Abstract

Software as a Service (SaaS) solution has revolutionized the contemporary business processes as scalable and service-on-demand solution on cloud networks. Yet, this expansion has brought in sophisticated cybersecurity risks because of a multi-tenant environment facing the internet in the SaaS environment. The key to assure the service availability and protection of the data stored off-site is effective threat detection in such dynamic ecosystems. This review article seeks to discuss the traditional and the advanced methods of threat detection within SaaS platforms with a focus on what goes wrong with the traditional methods of threat detection, including signature-based, anomaly-based based and others. It notes the trend to the AI-driven, machine learning-enabled, and context-sensitive detection leveraged to improve security monitoring in real-time and incident response. The research also refers to the concept of adaptive cloud security models that plan to apply dynamic configurations of cloud security settings in response to changing cyber threats. Components incorporated in these models include risk assessment engines, policy control module, and cryptographic services to ensure protection of the cloud holistically and robustly. Severe conversions of the literature give a clear appraisal of the current progress in intelligent invasion perceiving apparatus, dynamic access protocol, and security regulation driven by AI. The paper ends by addressing emerging challenges of scalability, model drift, and interoperability and gives future research directions to create autonomous, explainable, and adaptive security frameworks of next-generation SaaS infrastructures.

Keywords: SaaS Security, Threat Detection, Adaptive Cloud Security, cybersecurity, Machine Learning (ML) in Cloud Security, proactive defense, proactive defense

How to cite this article:
Nilesh Jain. Reviewing Threat Detection Methods in SaaS Platforms Through the Use of Adaptive Cloud Security Models. Journal of Artificial Intelligence Research & Advances. 2025; 12(03):-.
How to cite this URL:
Nilesh Jain. Reviewing Threat Detection Methods in SaaS Platforms Through the Use of Adaptive Cloud Security Models. Journal of Artificial Intelligence Research & Advances. 2025; 12(03):-. Available from: https://journals.stmjournals.com/joaira/article=2025/view=228377


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Ahead of Print Subscription Review Article
Volume 12
03
Received 19/06/2025
Accepted 29/07/2025
Published 29/09/2025
Publication Time 102 Days
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