Jul 2026· 2026 7th International Conference on Smart Systems and Inventive Technology (ICSSIT)· pp. 1848-1853· 0 citations· 31 references
Abstract
Cloud is the essential component for modern computer systems, offering businesses flexible scalability and on-demand resources. However, as attackers use more complex techniques to compromise cloud networks, this technological advancement has ushered in a new era of cybersecurity challenges. Wide-ranging effects, such as data loss, financial penalties, reputational harm, and legal responsibilities, can result from such breaches. In response to these challenges, a strong security framework is essential to effectively protect cloud infrastructure. Recently, several artificial intelligence (AI) techniques have been developed for cyber threat detection. Hence, to get deeper insight into this, the survey aims to analyse the role of cyber threat detection techniques and provide an overview of their applications. To achieve this, around 28 research papers from the years 2023-2026 are reviewed based on their methods, algorithms, datasets, performance metrics, and achievements. Furthermore, this work reviews different types of threats affecting the availability, confidentiality, and integrity of cloud services and resources, and examines the applications, including intrusion detection in cloud and several types of cyber threat detection systems. The core insights formulated in this review provide a comparison of analytics as well as future directions.
Cloud Computing has completely transformed the way businesses operate today with its scalability, flexibility, and cost efficiency. Cloud platforms have become a key component for organizations in various sectors to store data, deploy software, manage infrastructure, and implement digital transformation efforts. But the adoption of cloud computing has made it extremely challenging to deal with several security concerns like data breach, cyberattacks, unauthorized access, insider threats, and compliance concerns. The research paper employs secondary data collection and thematic analysis to critically discuss challenges of cloud security and risk management approaches in contemporary cloud computing environment. A thorough literature review of the scholarly papers from 2015 to 2023 is conducted to assess cybersecurity threats, cloud vulnerabilities, identity management systems, encryption technologies, compliance frameworks, and artificial intelligence-based threat detection systems.Peer reviewed journal articles, conference papers and industry reports were analysed using the method of themed analysis, which identified themes that appeared repeatedly throughout. The results show that cloud environments are still very susceptible to advanced cyberattacks, ranging from weak authentication and insecure APIs to misconfigured cloud services and inadequate governance. The study also points out the effectiveness of modern technologies like multi-factor authentication, zero-trust security models, artificial intelligence, and encryption enhance cloud security performance. But there are still issues in the way of the organizations' operations regarding regulatory compliance, data governance and shared security responsibilities.The study demonstrates that the key factors to achieving effective cloud security are continuous monitoring, robust governance policies, employee awareness training, and high-level cybersecurity frameworks. The study adds to the body of knowledge about the security of cloud computing, and offers practical suggestions for any organization working in the cloud.
Veeramani Sampathkumar, Dinesh Kumar Ramaraj, Rajesh Kotha et al.· International journal of com...· 0 citations
Cloud computing has become a fundamental paradigm for delivering scalable, flexible, and cost-effective computing resources through Internet-based platforms. Its rapid adoption across various sectors has enhanced operational efficiency, resource utilization, and service delivery. Despite these advantages, cloud environments continue to face significant security challenges that threaten the confidentiality, integrity, and availability of data and services. This review examines the major security threats affecting cloud computing environments, including data breaches, account hijacking, insider threats, insecure application programming interfaces (APIs), cloud misconfigurations, distributed denial-of-service (DDoS) attacks, multi-tenancy risks, and regulatory compliance issues. The study also analyzes the security implications associated with different cloud services and deployment models. Furthermore, it reviews contemporary security mechanisms and mitigation strategies, including encryption techniques, Identity and Access Management (IAM), Multi-Factor Authentication (MFA), Zero Trust Architecture (ZTA), Cloud Security Posture Management (CSPM), Artificial Intelligence-based security systems, DevSecOps practices, and Confidential Computing. In addition, the strengths and limitations of existing approaches are critically discussed, while emerging trends, research gaps, and future research directions are highlighted. By synthesizing recent developments in cloud security, this review provides researchers, practitioners, and decision-makers with a comprehensive understanding of current challenges and promising solutions for securing modern cloud computing environments.
Amat AL-latif H. Abo-Torkhoma, A. A. H. Abo-torkhoma, G. Ali· Emirates International Unive...· 0 citations
The rise in Cloud–Internet of Things (Cloud–IoT) infrastructure has greatly increased the exposure of organizations to cyber threats, with recent studies showing that over 68% of security breaches have originated from misconfigured cloud resources. Continuous Threat Exposure Management (CTEM) and Zero Trust Security (ZTS) models have been proposed to address these challenges; however, nearly 70% of current implementations are still detection-oriented rather than exposure-predictive. This critical review statistically evaluates current research on CTEM models, Zero Trust frameworks, and artificial intelligence-based cybersecurity solutions in multi-cloud and edge environments. A review of the literature suggests that less than 35% of current solutions have combined dynamic risk scoring with automated access control, while less than 25% of current solutions have allowed real-time adaptive policy enforcement. There is a great need for improvement in predictive threat exposure modelling, autonomous security orchestration, and continuous exposure mitigation in heterogeneous cloud–IoT infrastructures. The review identifies essential research goals in the development of an AI-based adaptive cyber defence framework that is predictive, intelligent, and continuously risk-driven in a Zero-Trust security paradigm.
Koteswara Rao Damacharla, S. Kumar· Journal of Information Secur...· 0 citations
The reviewed literature indicates that AI-based methodologies often demonstrate superior detection capabilities for intricate and previously unseen attack patterns compared to traditional methods; however, direct performance comparisons are complicated due to discrepancies in datasets, experimental designs, and evaluation protocols.
Jaswanth Garugu· International Journal for Re...· 0 citations
With the widespread adoption of cloud computing, securing enterprise networks against cyber threats has become increasingly important. Cloud environments are highly dynamic and constantly changing, making them susceptible to sophisticated cyberattacks that traditional Intrusion Detection Systems (IDS) often fail to detect. This study focuses on Intelligent Intrusion Detection Systems (IIDS) and their critical role in strengthening cloud security. Unlike conventional signature-based IDS that rely on fixed attack patterns, IIDS employ advanced Machine Learning (ML) and Artificial Intelligence (AI) techniques including deep learning, decision trees, and ensemble models to identify both known and emerging threats with greater accuracy. The paper proposes an integrated framework that combines real-time anomaly detection with automated response capabilities for cloud networks. Key architectural elements of IIDS are examined, alongside major deployment challenges such as scalability, false-positive rates, and computational requirements. Additionally, practical case studies and performance evaluations illustrate how IIDS enhance threat detection by improving accuracy, adaptability, and efficiency. Finally, the paper outlines future research directions to further advance IIDS capabilities and address the evolving security needs of modern cloud infrastructures.
R. Velu· 2026 4th International Confe...· 0 citations
A cybersecurity architecture oriented toward fraud prevention in a service sector company in Lima, Peru, whose design is grounded in the documentary analysis of 385 technical incident records is proposed, forming a defense-in-depth capable of reducing residual exposure and sustaining a robust anti-fraud response in digitalized administrative environments.
Enrique Castellares Cuya, José Rengifo Espinal· International Journal of Com...· 0 citations