•  71
    Deep Learning-Based Speech and Vision Synthesis to Improve Phishing Attack Detection through a Multi-layer Adaptive Framework
    with Christopher Kiekintveld and Aritran Piplai
    Proceedings of the IEEE 8. forthcoming.
    The ever-evolving ways attacker continues to improve 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. Thus, current anti-phishing methods remain vulnerable to complex phishing because of the increasingly sophistication tactics adopted by attacker coupled with the rate at which new tactics are bein…Read more
  •  91
    An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey (review)
    with Christopher Kiekintveld and Aritran Piplai
    Proceedings of the IEEE 11. forthcoming.
    To secure computers and information systems from attackers taking advantage of vulnerabilities in the system to commit cybercrime, several methods have been proposed for real-time detection of vulnerabilities to improve security around information systems. Of all the proposed methods, machine learning had been the most effective method in securing a system with capabilities ranging from early detection of software vulnerabilities to real-time detection of ongoing compromise in a system. As there…Read more
  •  95
    Performance Comparison and Implementation of Bayesian Variants for Network Intrusion Detection
    with Christopher Kiekintveld
    Proceedings of the IEEE 1 5. 2023.
    Bayesian classifiers perform well when each of the features is completely independent of the other which is not always valid in real world applications. The aim of this study is to implement and compare the performances of each variant of the Bayesian classifier (Multinomial, Bernoulli, and Gaussian) on anomaly detection in network intrusion, and to investigate whether there is any association between each variant’s assumption and their performance. Our investigation showed that each variant of …Read more
  •  146
    Encoder-Decoder Based Long Short-Term Memory (LSTM) Model for Video Captioning
    with Adewale Sikiru and Bolanle Matti Hafiz
    Proceedings of the IEEE 1-6. forthcoming.
    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 an input temporal sequence of video frames to an output sequence of words to form a caption sentence. Data preprocessing, model construction, and model training are discussed. Caption correctness is evaluated using 2-gram BLEU scores across the different splits of the dataset. Specific examples of output captions were …Read more
  •  107
    Adversarial Sampling for Fairness Testing in Deep Neural Network
    with William Marfo, Justin Tonkinson, Sikiru Adewale, and Bolanle Hafiz Matti
    International Journal of Advanced Computer Science and Applications 14 (2). 2023.
    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. While several framework had been proposed to ensure robustness of machine learning model against adversarial attack, some of which includes adversarial training algorithm. There is still the pitfall that adversarial training algorithm tends to cause disparity in accuracy and robustness among different group. …Read more
  •  990
    Data Mining in the Context of Legality, Privacy, and Ethics
    with Amos Okomayin and Abosede Kolade
    International Journal of Research and Innovation in Applied Science 10 (Vll): 10-15. 2023.
    Data mining possess a significant threat to ethics, privacy, and legality, especially when we consider the fact that data mining makes it difficult for an individual or consumer (in the case of a company) to control accessibility and usage of his data. Individuals should be able to control how his/ her data in the data warehouse is being access and utilize while at the same time providing enabling environment which enforces legality, privacy and ethicality on data scientists, or data engineer du…Read more
  •  112
    Ambient Technology & Intelligence
    with Amos Okomayin
    International Journal of Research and Innovation in Applied Science. forthcoming.
    Today, we have a mixture of young and older individuals, people with special needs, and people who can care for themselves. Over 1 billion people are estimated to be disabled; this figure corresponds to about 15% of the world's population, with 3.8% (approximately 190 million people) accounting for people aged 15 and up (Organization, 2011). The number of people with disabilities is upward due to the increase in chronic health conditions and many other things. These and other factors have made t…Read more
  •  226
    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 research on cyber bullying which are unable to provide reliable solution to cyber bullying. In this research work, we were able to provide a permanent solution to this by developing a model capable of detecting and intercepting bullying incoming and outgoing messages with 92% accuracy. We also developed a chatbot automat…Read more
  •  246
    AI Powered Anti-Cyber bullying system using Machine Learning Algorithm of Multinomial Naïve Bayes and Optimized Linear Support Vector Machine
    with Sikiru Adewale
    International Journal of Advanced Computer Science and Applications 13 (5). 2022.
    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 research on cyber bullying which are unable to provide reliable solution to cyber bullying. In this research work, we were able to provide a permanent solution to this by developing a model capable of detecting and intercepting bullying incoming and outgoing messages with 92% accuracy. We also developed a chatbot automat…Read more
  •  232
    Implementation of Data Mining on a Secure Cloud Computing over a Web API using Supervised Machine Learning Algorithm
    International Journal of Advanced Computer Science and Applications 13 (5). 2022.
    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, pattern recognition and technology advancement. With this also bring the problem of scalability, efficiency and security threat. This research paper focuses on how data can be dynamically mine in real time for pattern detection in a secure cloud computing environment using combination of decision tree algorithm and Random…Read more