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Found 8 papers, 0 papers with code
Deep Learning-Based Speech and Vision Synthesis to Improve Phishing Attack Detection through a Multi-layer Adaptive Framework
The ever-evolving ways attacker continues to im prove their phishing techniques to bypass existing state-of-the-art phishing detection methods pose a mountain of challenges to researchers in both industry and academia research due to the inability of current approaches to detect complex phishing attack.
An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey
In this research, we analyzed the suitability of each of the current state-of-the-art machine learning models for various cyberattack detection from the past 5 years with a major emphasis on the most recent works for comparative study to identify the knowledge gap where work is still needed to be done with regard to detection of each category of cyberattack.
Performance Comparison and Implementation of Bayesian Variants for Network Intrusion Detection
Bayesian classifiers perform well when each of the features is completely independent of the other which is not always valid in real world application.
Ambient Technology & Intelligence
Today, we have a mixture of young and older individuals, people with special needs, and people who can care for themselves.
Adversarial Sampling for Fairness Testing in Deep Neural Network
In this research, we focus on the usage of adversarial sampling to test for the fairness in the prediction of deep neural network model across different classes of image in a given dataset.
Enhancing Border Security and Countering Terrorism Through Computer Vision: a Field of Artificial Intelligence
In this research work, we used open source computer vision (Open CV) and adaboost algorithm to develop a model which can detect a moving object a far off, classify it, automatically snap full image and face of the individual separately, and then run a background check on them against worldwide databases while making a prediction about an individual being a potential threat, intending immigrant, potential terrorists or extremist and then raise sound alarm.
AI Powered Anti-Cyber Bullying System using Machine Learning Algorithm of Multinomial Naive Bayes and Optimized Linear Support Vector Machine
"Unless and until our society recognizes cyber bullying for what it is, the suffering of thousands of silent victims will continue."
