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40 articles for “proactive threat detection”
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Advancing Threat Intelligence: A Synergistic Convergence of AI and Machine Learning for Proactive Detection
Abstract: The need for defense systems that are smarter, faster, and more adaptable has never been greater in an era when cyber threats are becoming increasingly intelligent and evasive. This project presents a cutting-edge approach to cybersecurity through the synergistic fusion of Artificial Intelligence (AI) and Machine Learning (ML), aiming not just to detect threats—but to predict and prevent them proactively. The automated ingestion of various cybersecurity data, including live network …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 · pp. 1–8 Read article
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Cybersecurity Innovations in Industrial Control Systems
Abstract: Industrial control systems (ICS) are essential for automating and managing industrial processes across a broad spectrum of sectors, including energy, manufacturing, transportation, and water treatment. Securing these systems is essential to avoid disruptions that could lead to significant economic losses and safety risks. Recent advancements in ICS cybersecurity encompass several key areas that collectively aim to bolster the security and reliability of these critical infrastructures, thereby enhancing industrial safety. Enhanced …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 2, 2024 · pp. 15–19 Read article
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Enhancing LAN Security Using Machine Learning
Abstract: The modern Local Area Network (LAN) is a critical component of any organization's infrastructure, facilitating communication, resource sharing, and access to the wider internet. However, this connectivity also brings inherent security risks. Traditional security measures, relying on signature-based detection and rule-based systems, are increasingly struggling to keep pace with the evolving sophistication of cyberattacks. This is where Machine Learning (ML) offers a powerful alternative, enabling proactive threat detection and enhanced …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 07–16 Read article
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Advanced Private Cloud Security and Privacy Preservation Through the Integration of Machine Learning and Cryptography
Abstract: In modern technological landscapes, private cloud security is of paramount concern due to the ever-increasing volume and complexity of cyber threats. This research work explores the integration of machine learning and cryptography to enhance security within private cloud environments. This study aims to mitigate vulnerabilities that may compromise data integrity, confidentiality, and availability in private cloud infrastructures by using machine learning algorithms and strong cryptography. By detecting anomalous cloud patterns …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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Reviewing Threat Detection Methods in SaaS Platforms Through the Use of Adaptive Cloud Security Models
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 …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 Read article
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Uncovering the Elusive Threat: An Investigative Study on Polymorphic Viruses
Abstract: In the intricate landscape of cybersecurity, polymorphic viruses have prominently emerged, distinguishing themselves through their unique ability to continually modify their code, rendering them stealthy and challenging to detect. This comprehensive study embarks on a journey through the complex world of these viruses. It commences with a historical lens, meticulously tracing their roots, their initial manifestations, and the progressive sophistication of their code-altering techniques. The research then pivots to a …
Published in Journal Of Network security · Vol. 11, Issue 3, 2023 · pp. 10–21 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Cyberattack Detection System in Private Cloud
Abstract: As cloud computing adoption in colleges continues to rise, the security of private cloud systems has become a paramount concern. Data breaches resulting from cyberattacks can inflict severe damage to a university's revenue and reputation. This research proposes a novel machine learning-based cyber threat detection system tailored to the university's private cloud environment. The system's main objective is to continuously monitor the cloud infrastructure and employ advanced machine learning algorithms …
Published in Recent Trends in Parallel Computing · Vol. 10, Issue 2, 2023 · pp. 37–44 Read article
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Transforming Hospital Environments: The Role of Sound Detection
Abstract: Hospitals are sanctuaries of healing, yet they are often paradoxically exposed to a pervasive, often underestimated threat: excessive noise. While internal hospital sounds pose their own challenges, the impact of external sounds – traffic, construction, sirens, and urban clamor – can profoundly compromise patient safety, recovery, and overall well-being. This article explores the critical role of advanced sound detection systems in mitigating this external acoustic intrusion, leveraging technology to create …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 4, Issue 1, 2026 · pp. 28–40 Read article
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AI-Based Threat Detection in Cloud Platforms
Abstract: This research work delves into the transformative role AI has come to assume for enhanced threat detection in the cloud ecosystem. The conventional security frameworks, which form the basis for many architectures, are several steps behind actualizing the rapidly evolving cyber threat landscape, exposing critical weaknesses in the areas of accuracy, adaptability, and speed of response. Initially, the study sets forth the problems with the old-school approaches to threat detection …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 01–10 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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AI-Driven Cyber Threat Detection and Response Framework for Higher Educational Institutions (HEIs)
Abstract: Higher educational institutions (HEIs) are increasingly exposed to complex cyber threats due to their open-access digital ecosystems, diverse user populations, and extensive research infrastructures. Conventional signature-based intrusion detection systems often fail to detect zero-day and evolving attacks, creating an urgent need for intelligent and adaptive security mechanisms. This research introduces an AI-based framework for detecting and responding to cyber threats, specifically designed for HEIs. The framework employs an unsupervised machine …
Published in Journal Of Network security · Vol. 14, Issue 2, 2026 · pp. 28–34 Read article
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The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services
Abstract: The swift growth of cloud computing has transformed how organizations handle and store data, providing greater scalability and adaptability. However, the transition to cloud-based environments has heightened the complexity of cybersecurity challenges, especially in detecting and responding to security incidents. Conventional methods of incident response, which heavily depend on manual efforts, are no longer adequate to address the rapidly evolving and complex nature of modern cyber threats. This study explores …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 1–14 Read article
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Fortifying the Blockchain Fortress: A Machine Learning Paradigm for Enhanced Security
Abstract: Blockchain technology has emerged as a revolutionary tool in the digital landscape, enabling secure and transparent transactions across a decentralized network. Despite its robust security features, blockchain systems remain vulnerable to anomalies and malicious activities. The detection of these anomalies using machine learning has become essential for protecting blockchain networks and ensuring their integrity. This project delves into the application of machine learning techniques to detect abnormal patterns within blockchain …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 33–40 Read article
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Fortifying the Cloud: AI-Driven Security Paradigms and Evolving Threat Defenses in Modern Cloud Computing
Abstract: Organizations worldwide are raising their concerns about security maintenance while cloud computing expands rapidly to serve as a digital transformation foundation. The study explores modern cloud security patterns while also evaluating how artificial intelligence modifies the identification and evaluation of complex cyber threats along with their prevention methods. New security threats such as insider operations and DDoS attacks and data breaches alongside insecure APIs can be detected through machine learning …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
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AI-Driven Cybersecurity: Enhancing System Resilience with Advance Security Automation Program (ASAP)
Abstract: In the face of increasing cyber threats, this work presents advanced security automation program (ASAP) a revolutionary solution aimed at addressing modern cyber threats through the utilization of artificial intelligence (AI) and open-source technologies. Unlike conventional security systems like security information and event management (SIEM) and security operations center (SOC), ASAP provides automated defense mechanisms that surpass their limitations by significantly increasing both the speed and accuracy of incident detection …
Published in Journal of Open Source Developments · Vol. 11, Issue 2, 2024 · pp. 1–19 Read article
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AI-Powered Defense: Advancing Cybersecurity Through Artificial Intelligence Innovations
Abstract: In the current landscape of escalating cyber threats and increasingly sophisticated attack vectors, integrating artificial intelligence (AI) within cybersecurity strategies has become a critical step forward. This study explores the role of AI in strengthening cybersecurity by utilizing its strengths in data analysis, pattern recognition, and predictive modeling. Through AI, organizations can greatly enhance their ability to detect and respond to threats. Machine learning algorithms enable ongoing adaptation to new …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 35–41 Read article
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Multi-Layered AI-Driven Security in Wireless Ecosystems
Abstract: The proliferation of next-generation wireless technologies, from 5G/6G networks to the pervasive Internet of Things (IoT), has birthed a hyperconnected digital ecosystem of unprecedented scale and dynamism. This interconnectedness, however, introduces a vast and volatile attack surface, rendering conventional, signature-based security paradigms fundamentally obsolete. This paper posits that the only viable defense is an offensive, self-adaptive one, predicated on the integration of artificial intelligence (AI) directly into the wireless security …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 21–28 Read article
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The Role of Artificial Intelligence in Automating Incident Response in Cloud-Based Cybersecurity
Abstract: As cloud computing continues to gain traction across industries, the complexity and scale of cloud environments present significant challenges to traditional cybersecurity practices. The dynamic and distributed nature of cloud infrastructures necessitates agile and effective incident response mechanisms to detect, analyze, and mitigate threats in real-time. However, conventional incident response methods often fall short due to the growing sophistication of cyber threats and the vast amounts of data generated in …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 15–24 Read article
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The Impact of Climate Change on Infectious Diseases: Potential Risks and Mitigation Strategies
Abstract: As we confront the pressing challenge of climate change, it's vital to recognize its intertwined connection with infectious diseases. We must now navigate a future that combines strong public health interventions, environmental stewardship, and strong policy actions as we stand at the crossroads of crises. In an attempt to lessen the drastic effects of climate change on the dynamics of disease transmission, this study identifies potential risks and creative solutions. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 21–32 Read article