30 citations · 86 across the 11 of their papers we have counts for
11 papers
MAD-OOD: A Deep Learning Cluster-Driven Framework for an Out-of-Distribution Malware Detection and Classification
Tosin Ige, Christopher Kiekintveld, Aritran Piplai +3
Out of distribution (OOD) detection remains a critical challenge in malware classification due to the substantial intra family variability introduced by polymorphic and metamorphic…
An investigation into the performances of the Current state-of-the-art Naive Bayes, Non-Bayesian and Deep Learning Based Classifier for Phishing Detection: A Survey
Tosin Ige, Christopher Kiekintveld, Aritran Piplai +3
Phishing is one of the most effective ways in which cybercriminals get sensitive details such as credentials for online banking, digital wallets, state secrets, and many more from…
Deep Learning-Based Speech and Vision Synthesis to Improve Phishing Attack Detection through a Multi-layer Adaptive Framework
Tosin Ige, Christopher Kiekintveld, Aritran Piplai
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 rese…
An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey
Tosin Ige, Christopher Kiekintveld, Aritran Piplai
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 e…
Encoder-Decoder Based Long Short-Term Memory (LSTM) Model for Video Captioning
Sikiru Adewale, Tosin Ige, Bolanle Hafiz Matti
This work demonstrates the implementation and use of an encoder-decoder model to perform a many-to-many mapping of video data to text captions. The many-to-many mapping occurs via…
Performance Comparison and Implementation of Bayesian Variants for Network Intrusion Detection
Tosin Ige, Christopher Kiekintveld
Bayesian classifiers perform well when each of the features is completely independent of the other which is not always valid in real world application. The aim of this study is to…
Ambient Technology & Intelligence
Amos Okomayin, Tosin Ige
Ambient intelligence refers to technological enhanced electronic environments which are both responsive and sensitive to the presence of people within their environment. Environmen…
Adversarial Sampling for Fairness Testing in Deep Neural Network
Tosin Ige, William Marfo, Justin Tonkinson +2
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…
Enhancing Border Security and Countering Terrorism Through Computer Vision: a Field of Artificial Intelligence
Tosin Ige, Abosede Kolade, Olukunle Kolade
Border security had been a persistent problem in international border especially when it get to the issue of preventing illegal movement of weapons, contraband, drugs, and combatin…
Implementation of Data Mining on a Secure Cloud Computing over a Web API using Supervised Machine Learning Algorithm
Tosin Ige, Sikiru Adewale
Ever since the era of internet had ushered in cloud computing, there had been increase in the demand for the unlimited data available through cloud computing for data analysis, pat…
AI Powered Anti-Cyber Bullying System using Machine Learning Algorithm of Multinomial Naive Bayes and Optimized Linear Support Vector Machine
Tosin Ige, Sikiru Adewale
"Unless and until our society recognizes cyber bullying for what it is, the suffering of thousands of silent victims will continue." ~ Anna Maria Chavez. There had been series of r…