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186 articles for “Threats Detecting”
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Hybrid Intelligence in Cyber Security: A Study
Abstract: The digital landscape is a battlefield of escalating complexity, where the volume, velocity, and sophistication of cyber threats have exponentially outpaced human-centric defense models. Traditional rule-based security systems and siloed artificial intelligence (AI) solutions, while valuable, are increasingly brittle, overwhelmed by zero-day exploits, polymorphic malware, and coordinated, state-sponsored campaigns that operate in the shadows of big data. This paper posits that the paradigm of cybersecurity must fundamentally shift from one …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 01–09 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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AI and Sensor Systems Revolutionizing Intoxication and Smoking Pre- Detection
Abstract: In an increasingly interconnected and safety-conscious world, the pervasive issues of intoxication and uncontrolled smoking continue to pose significant threats to public health, safety, and productivity. From impaired driving incidents to workplace accidents, and from chronic health conditions linked to smoking to the risk of fires, the societal and economic costs are staggering. However, a new frontier in preventative technology is emerging: sophisticated AI and sensor-based systems designed for the …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 3, 2025 · pp. 14–25 Read article
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Unveiling the Silent Threat: The Escalation and Defence Against Antibiotic Resistance
Abstract: The global challenge of antibiotic resistance presents a significant risk to public health, driven by multifaceted factors worldwide. This issue, akin to the impacts of climate change, requires concerted efforts at national and international levels to mitigate its consequences. Antibiotics have revolutionized modern medicine, enabling critical interventions like surgeries, transplants, and cancer treatments. However, without global collaboration, we face significant setbacks across medical, social, and economic domains. Initiatives to address …
Published in International Journal of Antibiotics · Vol. 2, Issue 2, 2025 · pp. 1–26 Read article
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Detection of Phishing Website URLs and Email/SMS Using Random Forest and Multinomial Naive Bayes
Abstract: Currently, phishing attacks via SMS/email and URL have become significant threat to cybersecurity, posing risks to both individuals and organizations alike. Phishing attacks typically involve the creation of fraudulent websites or the dissemination of deceptive emails and SMS messages to trick users into disclosing sensitive information such as passwords, credit card numbers or personal details. To respond to these attacks, we develop a robust system for the detection of phishing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 22–30 Read article
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Machine Learning Approaches for Phishing Detection: A Comparative Study
Abstract: These days, everyone has an internet addiction. All of us have used the internet for banking, booking, recharging, and buying. Phishing is a type of website threat that exists online. On the original website, phishing is an attempt to illegally obtain information such as login ID, password and credit card information. In this research, we proposed an efficient phishing detection system based on machine learning. Overall, the experimental findings demonstrated …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 1, 2024 · pp. 35–45 Read article
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IoT-Based Emergency SOS System for Post-Accident Assistance
Abstract: The increase in road accidents poses significant challenges for timely medical response, often leading to life-threatening delays. This project proposes an IoT-based accident wound detection system that utilizes a night vision camera mounted on either the interior or exterior of a vehicle. The system aims to detect injuries sustained by individuals during a collision and promptly alert emergency services. By employing a night vision camera, the system can operate effectively …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 11–19 Read article
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DoS Attacks and Detection Schemes in Wireless Mesh Networks
Abstract: The attacks of DoS are a group of collaborative attacks made by attackers to threat internet security. A compromised system was used by the attacker has been used prohibit the user to access the resources. The attacker uses compromised systems to prevent users from having access to the server resources. In this survey, we will find defense mechanisms against DoS attacks that may have importance through the internet. The appliances …
Published in Journal Of Network security · Vol. 9, Issue 1, 2021 · pp. 11–19 Read article
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Automobile Collision Detection System Using GSM and GPS
Abstract: The accelerometer detects changes in the vehicle’s axis and the GSM module sends an alert message to the phone indicating the location of the event. Advanced technology makes our daily life easier. Because every coin has two sides, technology has both strengths and weaknesses. The development of technology has increased the number of traffic accidents, resulting in numerous deaths. The poor medical facilities that exist in our country exacerbate the …
Published in International Journal of Manufacturing and Production Engineering · Vol. 1, Issue 1, 2023 · pp. 15–19 Read article
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Real-time Collision Detection for Visually Impaired Peoples
Abstract: AbstractThe blind people are at a significant drawback because they often lack the information for avoiding obstacles and threats in their path. They have very little information on self-velocity, objects, route, etc., which is essential for travel. Previously developed navigation systems use costly equipment which is often not affordable by the common blind peoples. Also, the navigation systems available are heavy weighted and very complex to use. Our research is …
Published in Journal of Microcontroller Engineering and Applications · Vol. 5, Issue 1, 2018 · pp. 1–4 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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Grid Integrated Micro Inverter for PV Module with Anti-Islanding and MPPT Schemes
Abstract: From the economic perspective, densely populated areas can generate great amounts of electric power by installing PV panels on its rooftops and it can be fed in to the grid. This study describes a grid tied micro inverter for photovoltaic applications. The system consists of a Cuk converter connected with a full-bridge current source inverter. The connection of micro inverter systems to the grid can raise several challenges as the …
Published in Journal of Power Electronics and Power Systems · Vol. 8, Issue 3, 2018 · pp. 39–45 Read article
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Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
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Integrating Sensor Technologies and Machine Learning for Detection and Mitigation of Structural Deformity and Slope Failure in Opencast Mines
Abstract: With furtherance in the mining industry, accidents due to slope failure are frequent in mining sites. Slope instability, a complex process, seriously threatens the miner’s life and properties. The damage inflicted by slope failures in the recent past has pulled the attention of authorities toward implementing disaster risk reduction measures. This research aims to develop an innovative approach that combines sensor technologies and machine learning techniques to detect and mitigate …
Published in Journal of Communication Engineering & Systems · Vol. 13, Issue 3, 2023 · pp. 38–45 Read article
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Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
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Cybersecurity in a Digital World: Risks and Future Perspectives
Abstract: The field of information security offers a wide range of guidance in academic and practitioner literature. While various strategies such as deterrence, deception, detection, and reaction are explored, most research focuses on technological countermeasures to prevent security threats. This study presents the findings of a qualitative study conducted in Korea, examining how businesses utilize security techniques to safeguard their information systems. The results highlight a strong emphasis on preventive measures, …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 44–49 Read article
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Smart Safety: Evaluating Inviguard as an Innovative Wearable for Head Protection
Abstract: This study details INVIGUARD, an innovative head protection wearable device designed to prevent falls and accidental collisions for the special people. The device is neck-worn and utilizes a unique structure in the form of a honeycomb which when a threat is recognized will expand in volume to form a protective shield around the head whilst in normal usage is small in size; when the danger is no longer perceived. Such …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 1, 2025 · pp. 15–26 Read article
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Typhoid Fever: Etiology, Clinical Manifestations, Diagnosis, and Management
Abstract: Typhoid fever is a systemic and potentially life-threatening infectious disease caused by Salmonella enterica serotype Typhi, which primarily spreads through the fecal-oral route via ingestion of contaminated food and water. It continues to be a major global public health concern, particularly in developing and low-resource countries where poor sanitation, inadequate personal hygiene, and unsafe water supplies prevail. The disease is characterized by prolonged high-grade fever, abdominal discomfort, headache, loss of …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 1, 2026 · pp. 1–4 Read article
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Passive Digital Phenotyping for Longitudinal Burnout and Occupational Mental Health Surveillance: A Transformer-Based Explainable Deep Learning Approach Using Smartphone Behavioral Streams
Abstract: Occupational burnout constitutes a pervasive yet chronically under-surveilled public health threat, its insidious temporal evolution rendering episodic self-report instruments structurally inadequate for early detection. This paper introduces BurnoutSense, a passive digital phenotyping framework that continuously harvests eight heterogeneous smartphone behavioral data streams encompassing application usage ecology, communication metadata, geospatial mobility, screen interaction dynamics, inferred sleep rhythmicity, keystroke kinematics, ambient noise exposure, and battery/charging cadence to construct individualized multivariate behavioral signatures …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 · pp. 44–53 Read article
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Sentinels of Safety: A Robotic Revolution in Autonomous Landmine Detection for Humanitarian Resilience
Abstract: Landmine Detection Robotic Vehicle Project is to create an autonomous robotic system that can identify landmines in dangerous locations. The rover navigates through a variety of terrains by using modern sensor technology, such as metal detectors and infrared photography, to detect buried landmines. The rover can distinguish between potentially dangerous items and harmless ones. The principal aim of the project is to optimise the efficacy and security of landmine removal …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 28–34 Read article