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123 articles for “Detection Techniques”
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Phishing Attack, Its Detections and Prevention Techniques
Abstract: The relentless surge of cyber threats represents a pressing challenge to global security and individual privacy. Among these, phishing attacks remain a particularly pernicious form of cybercrime. This study provides a comprehensive review of phishing attacks, their evolution, methodologies, impacts, and countermeasures. The methods of perpetrating phishing attacks have grown in sophistication, extending beyond the common email phishing to include spear phishing, whaling, clone phishing, vishing, smishing, and search engine …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 13–25 Read article
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Advances in Non-Invasive NIR-Techniques for Gout Detection and Measurement
Abstract: Recent advancements in non-invasive near-infrared (NIR) spectroscopy techniques have significantly improved the detection and measurement of gout, a common form of inflammatory arthritis. Traditional diagnostic methods for gout, such as joint aspiration and crystal analysis, are invasive and can be uncomfortable for patients. In contrast, NIR spectroscopy offers a promising alternative by enabling real-time, non-invasive assessment of uric acid levels and related biomarkers associated with gout. The integration of portable …
Published in International Journal of Toxins and Toxics · Vol. 2, Issue 1, 2025 · pp. 1–8 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Unified Ensemble Techniques for Enhanced DDoS Attack Prevention and Detection
Abstract: Today’s world is entirely reliant on the internet. The internet is a worldwide information source that all users rely on, hence its accessibility is critical. There have been reports in recent years, particularly in the information and technology division of significant organizations worldwide, of data breaches where the terms denial-of-service (DoS) and DDoS are consistently present in the stolen material. Network security is seriously threatened by DoS attacks. They have …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 20–27 Read article
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Advanced Helmet Recognition System with Integrated Number Plate Detection for Enhanced Traffic Monitoring Using Deep Learning
Abstract: This study focuses on the crucial problem of non-adherence to traffic regulations, particularly with the compulsory use of helmets by motorcyclists. Motorcycle accidents have a greater mortality rate compared to other types of accidents, indicating a need for a more effective enforcement strategy. Current procedures depend on traditional techniques where traffic officers manually observe traffic rule infractions through patrols and monitoring CCTVs, requiring substantial labor and time resources. The inherent …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 9–18 Read article
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Chemiluminescence: Recent Developments and Photochemical Applications in Analytical Chemistry
Abstract: Chemiluminescence (CL) is the observable production of electromagnetic radiation from a chemical reaction, typically in the form of ultraviolet, visible, or infrared light. According to subjective yield, CL has either been directly emitted from electronically excited intermediate products, or it has been supported by another molecule to emit CL. Since the 1950s, CL has been supported as a valid analytical tool, with the descriptive issued scope being limited to content …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 2, Issue 1, 2024 · pp. 20–25 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Brain Tumor Detection by Aggregating Deep Learning and GAN Models for Faster MRI image Synthesis
Abstract: Brain tumors comprise a global health challenge that, in order to be treated and organized, need early and accurate diagnosis. Usually conducted through medical imaging, brain tumor detection techniques have problems of accuracy, efficiency, and confidentiality. Issues of limited datasets, strict privacy laws that provide restrictions on data sharing, and the necessity for specialized expertise on medical image analysis relegates modern methodologies to vulgar charades. For patient prognosis, treatment planning, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 45–53 Read article
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AI-Powered Fire Detection System for Accurate and Timely Emergency Response
Abstract: AI-based fire detection system leverages deep learning and Open CV. Issues with conventional fire detection techniques include false alarms and expense. The proposed system uses deep learning for real-time fire detection in videos, enhancing accuracy and adaptability. OpenCV aids in crowd counting, improving situational awareness during emergencies. This innovation promises to revolutionize fire safety by offering timely and precise detection, potentially saving lives and property. Additionally, by counting crowds, the …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 30–36 Read article
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Innovative Approaches to Fake Product Detection: Blockchain and QR Code Synergy
Abstract: For consumers, corporations, and regulatory agencies, the worldwide market's rise of counterfeit goods presents serious issues. Maintaining consumer confidence, guaranteeing product safety, and preserving brand reputation all depend on the ability to identify counterfeit goods. An overview of the different approaches and difficulties associated with spotting counterfeit goods is given in this abstract. First off, the ability to identify sophisticated counterfeit goods is limited by the use of conventional techniques …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 21–27 Read article
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Intrinsic Evaluation of Graph Embeddings: Assessing Clustering and Community Detection Performance
Abstract: This paper presents an intrinsic evaluation of some graph embedding techniques on clustering and community detection tasks. We analyze a diverse set of embedding methods, ranging from traditional techniques such as Laplacian eigenmaps to more recent approaches like graph autoencoders, high-order proximity preserved embedding (HOPE), and graph attention network (GAT), using two widely studied datasets, Cora and CiteSeer. Our evaluation relies on two main metrics: Silhouette score with respect to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 40–48 Read article
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Intelligent Brain Tumor Diagnosis with AI-Based Classification* * Harnessing Deep and Machine Learning for Tumor Identification
Abstract: Brain tumors have become a leading cause of cancer- related deaths, posing significant health risks to many patients. This urgent medical challenge calls for rapid, automated, and reliable techniques to detect brain tumors accurately. Timely and precise tumor identification is crucial for devising effective medical plans that have the potential to save lives and improve patient outcomes. By leveraging advanced image processing methods, healthcare professionals can enhance their diagnostic capabilities …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
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Automated Suspicious Activity Detection in Video Surveillance Using Deep Learning: A Review
Abstract: In the current era of advanced security systems, video surveillance plays an essential role in ensuring safety by detecting suspicious activities. With the increase in real-time data, manual monitoring has become impractical, paving the way for automated surveillance systems utilizing machine learning (ML) and artificial intelligence (AI) technologies. This paper explores the integration of ML and AI models, specifically convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, for …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 20–27 Read article
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Driver Drowsiness Detection System
Abstract: One of the main causes of road accidents worldwide in recent years is driver fatigue. Assessing a driver's mood, or how sleepy they are, is a clear approach to gauge their level of exhaustion. Therefore, detecting driver fatigue is very important to save lives and property. The creation of a prototype drowsiness detection system is the aim of this research. The system operates in real time, continuously capturing images and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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Revolutionizing Plant Disease Detection: A Comprehensive Review
Abstract: Rise in population demands more food production but the diseases in plants contribute to loss. The advancement in agricultural field has a remarkable effect in detecting plant diseases. These diseases will have a major impact on the quality of plant and yield and hence can destroy the entire plant if they are not controlled on time. To reduce disease-related losses, it is necessary to identify different types of diseases and …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 2, 2023 · pp. 44–55 Read article
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Cyberattack Detection and Prevention Using Empowering AI Tools
Abstract: With more organizations entering the digital transformation sphere, the opportunities and risks in cyberspace have increased and gone up in levels of sophistication and occurrence. Many of these developments are attributed to the limits of existing cyber security solutions where addressing new threats requires advanced detection technologies and techniques. Cyber threats gained a new meaning and dimension with artificial intelligence (AI) coming into play in ways that supplement security systems …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 1–7 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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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article