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A Deep Learning Ensemble With Data Resampling for Credit Card Fraud Detection
Aim: People can use credit cards for online transactions as it provides an efficient and easy-to-use facility. With the increase in usage of credit cards, the capacity of credit card misuse has also enhanced. Credit card frauds cause significant financial losses for both credit card ..
A Novel Multipurpose Watermarking Scheme Capable of Protecting and Authenticating Images with Tamper Detection and Localisation Abilities
Abstract: In this paper, a digital watermarking method is proposed which is based on Contourlet wavelet transform (CT) and Singular Value Decomposition (SVD). In the encryption process, the host image is decomposed into sub-bands using single level of Contourlet wavelet transform and..
An Improved Design for a Cloud Intrusion Detection System Using Hybrid Features Selection Approach With ML Classifier
Aim: The aim of this study is to enhance the efficacy of Cloud Intrusion Detection Systems by proposing an optimized design that integrates a hybrid feature selection approach with a machine learning classifier. The goal is to improve the accuracy and efficiency of intrusion detectio..
Chaotic Image Encryption Using Piecewise Logistic Sine Map
Aim: To analyze the Arnold cat map and demonstrating its effectiveness in the image encryption. Synopsis: With the development in the technology of computer networks, over this network, plenty of secret i..
Classifying Swahili Smishing Attacks for Mobile Money Users: A Machine-Learning Approach
Aim: Massive adoption of mobile money in countries, the global transaction value of mobile money exceeded $2 billion in 2021. Projections show transaction values will exceed $3 billion by the end of 2022, Spammers use Smishing (SMS Phishing) messages to trick a mobile money use..
DEA-RNN: A Hybrid Deep Learning Approach for Cyberbullying Detection in Twitter Social Media Platform
Aim: Cyberbullying (CB) has become increasingly prevalent in social media platforms. With the popularity and widespread use of social media by individuals of all ages, it is vital to make social media platforms safer from cyberbullying. This esents a hybrid Machine learning model, to..
Emoji, Sentiment and Emotion Aided Cyberbullying Detection in Hinglish
Aim: Cyber bulling is described as the serious, intentional, and repetitive acts of a person’s cruelty toward others using various digital technologies. It is mainly expressed through nasty tweets, texts, or other social media posts. So we analyzing sentiment, emoji and bully detection to contro..
Evolutionary Deep Belief Network for Cyber-Attack Detection in Industrial Automation and Control System
Technology: Cyber Security ..
Fraud Detection in Banking Data by Machine Learning Technique
Aim: The aim is to leverage the power of machine learning to create efficient and accurate fraud detection systems that protect the interests of both financial institutions and their customers.Abstract: As technology advanced and e-commerce s..
LSTM Based Phishing Detection for Big Email Data
Aim: Cybersecurity incidents have occurred frequently. Attackers have used phishing emails as a knock-on to successfully invade government systems. Therefore, we designed a phishing email detection method based on Bidirectional LSTM neural networkAbstract: &nbs..
Mobile crowd sensing approaches to address the COVID-19 pandemic in Spain
Abstract:Information technologies are called upon to help authorities to deal efficiently with the containment measures of the pandemic. One of the most critical measures taken by governments worldwide is the declaration of quarantine status. This involves confining the population to their homes to prevent the transmission of the virus. This is..
Phishing Detection System through Hybrid Machine Learning Based on URL
Aim: The aim of this research is to develop an advanced phishing detection system that leverages a hybrid machine learning approach to analyse URLs effectively and accurately identify potential phishing attempts.Abstract: This research introduces an innovative phish..
Phishing URL Detection: A Real-Case Scenario Through Login URLs
Aim: To provide an automated system for recognition the real-case Scenario through login URLsAbstract: Phishing is a social engineering cyber attack where criminals deceive users to obtain their credentials through a l..
Ransomware Classification and Detection with Machine Learning Algorithms
Aim: This study aims to improve the accuracy of Ransomware Classification and Detection with Machine Learning Algorithms Ransomware Classification, Feature Selection, Machine Learning, Cyber securityAbstract: Ransomware attacks pose a severe threa..