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20 articles for “AI-driven attacks”
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Ramifications of Artificial Intelligence and Cyber Security
Abstract: Artificial intelligence (AI) has pros and cons for cyber security: AI can improve network security, anti-malware, and fraud detection. AI can simulate cyberattacks, automate responses, and analyse enormous databases. AI-powered phishing and deepfakes are cyber risks. AI can potentially be attacked and become a liability for corporations. AI has transformed cyber security, bringing both new opportunities and challenges. AI-powered tools discover abnormalities faster, automate threat responses, and improve threat detection …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 1, 2025 · pp. 40–45 Read article
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Leveraging Standards and Deep Learning Approaches to Secure Internet of Things (IoT) Devices from Cyber Attack
Abstract: The widespread adoption of Internet of Things (IoT) devices between 2019 and 2024 has significantly grows in various sectors in Japan, including healthcare, manufacturing, and the development of smart cities. Although this growth offers many advantages, it also makes these devices more vulnerable to cyber threats. High-profile security breaches in Japan have sparked discussions about the requirement for enhanced security measures to protect the rapidly evolving IoT technologies. This study …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 Read article
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An Analytical Study on Cybersecurity Threats and AI-Driven Mitigation Strategies in Next-Generation Smart Grids
Abstract: The increasing adoption of next-generation smart grids has introduced significant cybersecurity challenges due to their reliance on interconnected digital infrastructures and IoT-based control mechanisms. This study aims to analyze cybersecurity threats in smart grids and explore AI-driven mitigation strategies to enhance grid security and resilience. The research examines common cyber threats such as malware attacks, denial-of-service (DoS), data breaches, and insider threats while evaluating the effectiveness of AI-based solutions, including …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 16–25 Read article
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A Systematic Literature Review on Security Challenges in Cloud–Edge Hybrid Systems
Abstract: Cloud–edge hybrid systems have become a key framework in today’s distributed computing landscape, combining fast, near-source data processing at the edge with the flexible scalability and resource richness of centralized cloud infrastructures. However, this in- tegration introduces a complex security landscape where tradi- tional perimeter- based cloud security measures are insufficient for resource- constrained and physically exposed edge nodes. This literature review synthesizes findings from established research publications (2020–2025), focusing …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 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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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 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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Artificial Intelligence in Cybersecurity: Emerging Trends, Technological Advancements, and Future Directions for Cyber Defense
Abstract: Artificial Intelligence (AI) is revolutionizing the field of cybersecurity by automating complex security tasks, improving threat detection capabilities, and enhancing the precision of threat response mechanisms. With the rapid evolution of cyber threats such as malware, ransomware, phishing, and data breaches, conventional security systems are often insufficient to provide timely and accurate protection. AI, powered by machine learning algorithms and neural networks, enables the analysis of vast datasets to detect …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 103–112 Read article
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AI-Based Cybersecurity Framework for Protecting Smart Surveillance Infrastructure in Mumbai
Abstract: Smart city infrastructures increasingly rely on interconnected surveillance systems to ensure safety, operational efficiency, and public trust. However, the rapid expansion of IoT-based monitoring technologies has introduced new cyber risks, especially in high-density metropolitan areas. This paper proposes an AI-driven cyber resilience framework targeting smart surveillance infrastructure as a critical smart-living domain, focusing on Mumbai as a case study. Using the CIC-IDS2017 dataset, a machine learning-based intrusion detection model is …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 Read article
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A Study on AI-Driven Multi-Layered Defense in 6G Ecosystems
Abstract: The 6G networks bring about new degrees of possible functions related to connectivity, latency, data throughput, and integration with artificial intelligence (AI). This enables advances within healthcare, autonomous systems, and smart cities. The positive impact of rapid advancements must also be balanced with heightened risks due to the sheer volume of gaps that can be exploited, and the complex nature of the alignments and breaches. This results in the breaches …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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AI-Based Machine Learning Web Application Firewall (ML-WAF)
Abstract: This research investigates the use of deep learning techniques for the real-time detection of malicious activities in web traffic and proposes an intelligent, AI-driven Web Application Firewall (WAF) designed to provide automated and adaptive security. The system analyzes diverse components of HTTP requests, including request methods, URLs, headers, cookies, and payload content, to accurately identify and classify malicious behavior. The proposed model targets a wide range of common and critical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Multi-Layered AI-Driven Paradigm Shift in IoT Ecosystem Security
Abstract: As the Internet of Things (IoT) continues to weave itself into the fabric of modern life – from smart homes and industrial automation to healthcare and urban infrastructure – the associated security vulnerabilities have become increasingly apparent. Traditional security mechanisms, often built on static rules and perimeter-based defenses, struggle to keep pace with the scale, heterogeneity, and dynamic nature of IoT ecosystems. In response, artificial intelligence (AI) has emerged as …
Published in Journal of Communication Engineering & Systems · Vol. 16, Issue 1, 2026 · pp. 13–21 Read article
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Challenges, Risks, and Limitations of Vibe Coding in AI- Assisted Software Development
Abstract: Vibe coding a new way of programming driven by LLMs (Large Language Model).it helps developers to write code from natural language. Coders can use prompts to AI for there code generation. Ai assistant generate software directly threw the text. Now they are able to make tasks and understand the user requirements. This process make our development fast and easy for the developers. but vibe coding has some drawbacks sometime it …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article
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A Framework for Privacy-preserving AI Models in Cloud Computing: Challenges and Solutions
Abstract: The growing adoption of cloud computing for deploying artificial intelligence (AI) models has led to significant advancements in sectors such as healthcare, finance, and e-commerce. However, the integration of AI with cloud computing raises critical privacy concerns, particularly when handling sensitive data. This paper presents a comprehensive framework for implementing privacy-preserving AI models in cloud environments, addressing the unique challenges, and proposing effective solutions. The suggested framework employs advanced privacy-preserving …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 1–12 Read article
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Aerodynamic Analysis of Foliage Stimulated Airfoil Design for Enhanced Strength with Carbon Fibre-reinforced Polymer
Abstract: Ever since the beginning of aviation, there has been an unwavering desire to improve airfoil design in order to improve aircraft performance. This insatiable desire for improvement has driven innumerable aerodynamicists to create a diverse range of revolutionary airfoils. This research investigates a revolutionary method to airfoil design, inspired by the complicated structures and aerodynamic qualities of natural leaves. Using biomimicry, the project seeks to increase the performance and efficiency …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 560–616 Read article
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Comparative Study of Compressive and Flexural Strength of Concrete by Partial Replacement of Cement by Nano Silica Powder in M40 Grade Concrete
Abstract: Concrete, a fundamental building material, traditionally relies on cement as a primary binder. However, the environmental and economic challenges associated with cement production have driven the search for alternative materials that can partially replace cement while maintaining or enhancing concrete's performance. This study focuses on the effects of Nano Silica Powder as a partial substitute for cement in M40 grade concrete, an advanced solution aimed at reducing the carbon footprint …
Published in Journal of Construction Engineering, Technology & Management · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
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The Rising Burden of Heart Attacks: Causes, Trends, and Prevention Strategies
Abstract: Heart attacks, or myocardial infarctions, remain a leading cause of morbidity and mortality worldwide, with their incidence rising steadily across diverse populations. This review explores the increasing prevalence of heart attacks, emphasizing traditional risk factors, such as poor diet, physical inactivity, smoking, and medical conditions like hypertension, diabetes, and hyperlipidemia. It also highlights emerging risk factors, such as chronic infections, pollutants, substance abuse, and the lasting cardiovascular effects of COVID-19. …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 2, 2025 · pp. 1–11 Read article
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Gatividhi Guard: The Activity Guardian—Revolutionizing Security Information and Event Management (SIEM) Technology
Abstract: In the dynamic landscape of cybersecurity, organizations confront increasingly intricate cyber threats that necessitate sophisticated security measures. Conventional systems such as Security Information and Event Management (SIEM) systems face ongoing challenges, they often struggle to effectively detect and mitigate sophisticated attacks within extensive data sets. To address these limitations, the introduction of Gatividhi Guard signifies a paradigm shift in SIEM technology. Gatividhi Guard is an innovative SIEM platform leveraging advanced …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 1, 2024 · pp. 29–44 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