Search
38 articles for “fraud detection”
-
Data Mining for E-Commerce and Social Media: Insights and Future Research Directions
Abstract: The fast expansion of e-commerce and social media has heralded a new era of data-rich settings, with enormous quantities of user interactions, preferences, and transactions generated on a daily basis. Data mining has developed as a critical strategy for leveraging big datasets, allowing businesses to gain concrete knowledge and drive decision-making. Data mining in e-commerce improves operational efficiency and user pleasure by allowing for personalized recommendations, consumer segmentation, fraud detection, …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 1, 2025 · pp. 14–23 Read article
-
Building a Modern Land Registration System: Leveraging Node.js and React.js for Efficiency, Security and Scalability
Abstract: Land registration systems are critical for safeguarding property ownership and enabling efficient real estate transactions. However, traditional systems often suffer from inefficiencies, including lengthy processing times, susceptibility to fraud, and limited accessibility. This study proposes a modernized Land Registration System (LRS) leveraging Node.js for backend development and React.js for frontend design to address these challenges. The system integrates real-time data processing, automated document verification, and role-based access control (RBAC) to …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 1–6 Read article
-
Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
-
Real-Time Deepfake Detection in Video Conferencing Systems
Abstract: Deepfake technology presents non-exemplary threats to video conferencing platforms, enabling advanced fraud, impression and misinformation campaigns worth billions annually. Current detection methods either exhibit latencies exceeding 100ms or rely on server-side cloud processing, raising privacy concerns. This paper presents DeepConfGuard, a lightweight hybrid architecture combining MobileNetV2 for spatial feature extraction, a bidirectional LSTM with attention for temporal modelling, and EfficientNetV2 for refinement. It reaches 94.8% accuracy with 85 ms end‑to‑end …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
-
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
-
Review article on Quality Control in Clinical Trials
Abstract: Quality control (QC) is a critical component in the conduct of clinical trials, ensuring the accuracy, reliability, and credibility of data collected throughout the study. It encompasses a systematic set of procedures designed to monitor trial conduct and data integrity, thus safeguarding the rights, safety, and well-being of participants. This review explores the principles, implementation, and evolving practices of quality control in clinical trials, highlighting its importance across all phases …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 3, 2025 · pp. 01–07 Read article
-
Malicious Application Detection in Windows Using SVM Algorithm
Abstract: In recent years, both the development of Windows application clients and the uses of smart mobile phones have increased significantly. As the number of Windows application users continues to grow, there is a rise in malicious individuals who develop harmful Windows applications with the intent of unlawfully obtaining confidential information and engaging in fraudulent activities. These applications are designed to target vulnerable areas such as mobile banking and digital wallets, …
Published in International Journal of Mobile Computing Technology · Vol. 1, Issue 1, 2023 · pp. 30–36 Read article
-
A Trust-Enhanced Security Architecture for Authenticating Customer Records in Banking Institutions
Abstract: The growing digital disruption of banking and financial services has completely altered the face of customer onboarding, money transactions, and financial service deliveries. Even as digital technologies provide unparalleled levels of efficiency and accessibility for consumers of financial services, they have also presented new challenges that are equally daunting. Among the growing number of financial threats that digital technology has spawned is the risk of synthetic identity fraud. Unlike identity …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 16–22 Read article
-
Enhancing Smart Grid Security: Machine Learning Approaches for Detecting Anomalies
Abstract: The integration of Information and Communication Technology (ICT) with traditional electric grids has led to the development of smart grids. However, this integration has also increased the risk of anomalies, such as cyber-attacks, metering fraud, electricity theft etc. False Data Injection Attacks are a class of cyber-attacks against power grid monitoring systems, where adversaries can inject false data to manipulate the grid’s operation. Metering frauds pertain to malicious customers com- …
Published in Trends in Electrical Engineering · Vol. 14, Issue 2, 2024 · pp. 10–19 Read article
-
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
-
AI Voice Detection Tool
Abstract: In today’s digital era, distinguishing between AI-generated and human voices is more important than ever. This project introduces an AI-based voice detection system designed to accurately identify synthetic voices, ensuring security and authenticity across various applications like cybersecurity, media verification, and fraud prevention.Our system works by analyzing incoming audio samples and comparing them against a diverse database of both AI-generated and real human voices. Using advanced machine learning and signal …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 1–8 Read article
-
Detecting Phishing Websites Using Hybrid Methodologies
Abstract: In the digital era, personal information theft has become a widespread and increasingly severe crime. Cybercriminals, often known as hackers, use deceptive strategies, with phishing websites being a major method for stealing confidential data. These fake websites imitate legitimate ones, tricking users into revealing sensitive personal and financial information, which has led to a rise in fraud cases. To address this escalating threat, a comprehensive research paper is proposed. This …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 59–65 Read article
-
Attendance System Based on Facial Recognition
Abstract: Attendance management is a fundamental aspect of educational institutions and workplaces, ensuring accountability, discipline, and operational efficiency. Traditional methods, such as manual roll calls, RFID cards, and fingerprint scanners, are often time-consuming, error-prone, and susceptible to fraud. This research presents an automated attendance management system utilizing face recognition technology to address these challenges effectively. The proposed system employs OpenCV for real-time image processing, the face recognition library for accurate facial …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 28–34 Read article
-
Detecting Fake Accounts on Social Media Using Machine Learning
Abstract: The growing frequency of fake accounts on social media platforms underscores the critical necessity for effective detection methods. In response to this challenge, our study leverages state-of-the-art machine learning techniques to identify and counter deceptive entities effectively. By conducting a thorough analysis of social media data, our approach unveils intricate patterns indicative of fraudulent accounts, enabling proactive measures against them. Through the application of advanced algorithms, we present a comprehensive …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 21–32 Read article
-
Android Voting System Using Face Recognition
Abstract: This work investigates a novel authentication approach for online voting systems that includes facial recognition verification. The goal is to create an automated voting system that increases election security and voter convenience. Voters prefer to cast their ballots in designated areas, such as polling booths, resulting in long lines and the majority of people missing out on the chance to vote. Ineligible voters may potentially fabricate their ballots, generating a …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 15–20 Read article
-
Robustness of Deepfake Detection Systems Against Adversarial Attacks
Abstract: This paper explores a deep learning system to detect deepfake videos, a common type of fake media. With the use of sophisticated methods such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs), our system can reliably discern between authentic and altered videos. It analyzes both the images and the audio in videos to find signs of deepfake manipulation. We process video frames and audio, extract features with CNNs …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
-
Enhancing Cyber Security in the Banking Sector Using Biometrics
Abstract: The fast-paced digital evolution within the banking industry has led to a substantial rise in the number of financial transactions conducted through online and mobile platforms. While this transformation has improved customer convenience and service accessibility, it has also exposed banking systems to a wide range of cyber threats, such as identity theft, phishing attacks, credential compromise, and financial fraud. Conventional authentication mechanisms, including passwords and personal identification numbers (PINs), …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 15–20 Read article
-
Fingerprint and Face Recognition Based Attendance System for Exams
Abstract: In educational institutions, managing attendance efficiently and accurately is pivotal for ensuring academic integrity and administrative effectiveness. Traditional attendance tracking techniques, including human roll calls or barcode scanning, are laborious, error-prone, and vulnerable to fraud. Traditional methods of keeping track of attendance, including sign-in sheets and physical roll calls, are often time-consuming, prone to errors, and lack the security measures needed in many contemporary settings. Modern biometric technologies have made …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 3, 2024 · pp. 26–33 Read article