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147 articles for “Network security challenges”
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Detection of Phishing Website Using URL
Abstract: Phishing attacks are one of the greatest threats to online security, where fraud websites deceive users into giving out sensitive information. Traditional methods of detection, such as blacklists and heuristic-based systems, often fail in identifying newly created or sophisticated phishing websites. This study proposes an intelligent phishing website detection system using Convolutional Neural Networks (CNNs) in analyzing URLs and associated features. Using labeled URLs, the system employs such attributes such …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 10–15 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article
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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
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Epilert: Epilepsy Tracker and Detector
Abstract: Epilepsy, affecting over 50 million individuals worldwide, necessitates innovative solutions for effective monitoring and intervention. Current systems face challenges such as inaccuracy, limited accessibility, and discomfort, leaving patients and caregivers vulnerable. Epilert, a wearable device, addresses these gaps by employing advanced sensors and machine-learning algorithms for real-time epilepsy detection and monitoring. The device integrates electromyography (EMG) and motion sensors to capture and analyze physiological and movement data. Preprocessing techniques ensure …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
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Post COVID-19 Impact on Agriculture and Food Security
Abstract: The Coronavirus COVID-19 pandemic is a global health crisis that is already having devastating impacts on the world’s economy. The challenges and vulnerabilities related to food security in these countries are further exacerbated by the current coronavirus (COVID-19) global pandemic. As a quick response strategy to reduce the spread of the coronavirus, countries have imposed various types of movement restrictions, both locally and globally, which have therefore been affected. Agricultural …
Published in Journal of Production Research & Management · Vol. 12, Issue 1, 2022 · pp. 8–13 Read article
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Role of Machine Vision in Autonomous Vehicles: A Review
Abstract: The integration of machine vision in autonomous vehicles (AVs) is a critical advancement in the field of intelligent transportation systems. Machine vision systems enable AVs to perceive their environment, understand road conditions, detect obstacles, and make real-time decisions necessary for safe navigation. These systems rely heavily on image processing techniques, which have evolved significantly over the past decade, leading to improved performance in complex driving scenarios. These developments are largely …
Published in Trends in Machine design · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
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Assessing the Suitability of Piped Water Supply for Tanker-fed Villages By Using WaterGems
Abstract: The Drinking water security has become a challenge for the country, specially in rural areas. So it is necessary to use available sustainable resources to resolve the problem. Many parts of Maharashtra face severe drinking water shortage in spite of high rainfall lying typically in the range of 2000-3000 mm. Aurangabad district alone has more than 100 tanker-fed villages, majority of which are concentrated in Paithan taluka. This study covered …
Published in Journal of Water Resource Engineering and Management · Vol. 7, Issue 1, 2020 · pp. 41–48 Read article
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IoT and Sensor Technologies: Pioneering Smart Agriculture for a Sustainable Future
Abstract: Smart agriculture provides creative answers to important global problems including resource efficiency, environmental sustainability, and food security. It improves agricultural yields, reduces waste, and optimizes farming operations by combining technologies like IoT, AI, and big data. This strategy ensures dependable food supply for a growing population while minimizing environmental damage and promoting sustainable development. In addition to solving the problems facing agriculture now, smart agriculture opens the door to a …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 2, 2025 · pp. 1–8 Read article
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Monitoring of Unauthorized Identity and Access Behaviour for Outsourced Data in Cloud Environment
Abstract: The outsourcing of data is a significant challenge in the modern cloud computing ecosystem when it comes to tracking unauthorized identification and access behaviour. In order to overcome this issue, this research suggests a thorough method for reliable anomaly detection in cloud systems. Improving data security and offering a trustworthy monitoring system are the two main goals. The suggested approach proceeds methodically, gathering information from several sources such as user …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 9–19 Read article
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The Role and Functions of Computer Engineers
Abstract: Computer engineers play a crucial role in shaping the ever-evolving technological landscape by designing, developing, and optimizing computer systems and software. Their expertise spans various domains, including hardware design, embedded systems, software development, cybersecurity, and network architecture. These professionals contribute significantly to advancements across multiple industries, from healthcare and finance to telecommunications and artificial intelligence. This article delves into the diverse responsibilities of computer engineers, highlighting their involvement in problem-solving, …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 37–51 Read article
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Securing Healthcare 5.0: A Review of Applications, Security Challenges, and Future Perspectives
Abstract: Healthcare 5.0 represents a revolutionary shift in the healthcare sector, focusing on individualized, patient-centric care through the integration of different cutting-edge technologies such as internet of things, artificial intelligence, big data analytics, blockchain, and cloud computing to enable healthcare services such as real-time health monitoring, personalized treatments, and access to expert advice regardless of geographic barriers. Potentially, Healthcare 5.0 supports more engaged and effective care and help through a focus …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 22–36 Read article
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A Study of Cloud-Enabled Deep Learning for Monitoring and Predicting Soil Health in Agriculture
Abstract: Soil health is a critical factor in ensuring sustainable agricultural practices and food security. Traditional methods for soil health assessment are often time-consuming, localized, and lack scalability. This study explores the integration of cloud-enabled deep learning techniques to monitor and predict soil health efficiently. Leveraging data from IoT sensors, satellite imagery, and lab-based analyses, a cloud-based framework is proposed to process and analyze soil health parameters such as pH, moisture …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 8–16 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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AI-Based House Price Prediction
Abstract: The housing market is one of the most dynamic and significant sectors of any economy, influencing both individual wealth and broader economic stability. Buyers, sellers, investors, and policymakers all rely on accurate housing price predictions. With the advent of artificial intelligence (AI) technologies, particularly machine learning algorithms, the task of house price prediction has seen remarkable advancements. This study provides a detailed overview of AI-based techniques for house price prediction. …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 1–7 Read article
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
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Raspberry Pi Based Tactical Autonomous Surveillance System
Abstract: In the ever-evolving realm of security and surveillance, the need for autonomous systems capable of operating in challenging environments has become increasingly evident. The Raspberry Pi-Based Tactical Autonomous Surveillance and Self-Destruction System addresses this need by combining advanced sensor technology, robust communication capabilities, and a self-destruction mechanism to provide a comprehensive security solution. This project proposes a Raspberry Pi-based tactical autonomous surveillance system that can be used to monitor and …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 1, 2024 · pp. 1–7 Read article
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Role and Efficacy of Artificial Intelligence in Cyber-security
Abstract: The internet is growing and so is the cyber world, more and more people, companies, organizations and governments, etc., who were previously ignorant or just didn’t want to enter the digital world have now started to reap its benefits as technology advances and provides more solutions to the existing real-world problems. This has unfortunately also increased the number of attackers, whether they may be cybercriminals, hacktivists, sponsored attackers or an …
Published in Journal Of Network security · Vol. 11, Issue 3, 2023 · pp. 1–9 Read article
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Securing IoT Wilderness with VHDL
Abstract: The Internet of Things (IoT) has revolutionized connectivity by integrating billions of devices and reshaping industries. However, this vast network also brings substantial security concerns. From compromised sensors to hijacked industrial control systems, the vulnerabilities within IoT devices can have far-reaching consequences. Hardware Security Modules (HSMs) provide a reliable and secure environment for performing cryptographic operations and safeguarding sensitive data. This article explores the crucial role of VHDL (VHSIC Hardware …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 1, 2025 · pp. 29–40 Read article
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DDoS Detection Using Cascade Correlation for Improving Network Resources in Cloud Environment
Abstract: Intrusion detection is critical for protecting network security from emerging cyber threats. This study describes a unique intrusion detection system (IDS) based on the Random Forest algorithm. Random Forests are used as an effective classifier to identify patterns linked with malevolent behaviour. This technique uses Random Forests to improve the accuracy and efficiency of intrusion detection systems. The suggested methodology's value is shown by its performance on the benchmark KDD …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 17–22 Read article
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Analysis and Identification of Malicious Mobile Applications Using Machines Learning
Abstract: Over the past few years, malware attacks on the Android platform have surged, posing significant risks to users' financial security, personal information, and device integrity. In the first half of 2019 alone, approximately 25 million smartphones were infected, highlighting the severity of these threats. The model ranks manifest features based on their frequency in normal and malicious apps, identifying key components that distinguish benign from malicious applications. To improve detection …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 17–24 Read article