ADENOWO ADETOKUNBO ABAYOMI

Computer Science

At the Computer Science department office

Appointment on Visitation important

Topic: Software Engineering And Information Security.

Description: My research includes Software Engineering SE and Information Security IS .Within the SE theme, my research considerations are in requirements engineering and design of software and software-intensive/driven systems with interest in concepts such as Intelligence, Security, and, recently, Sustainability of such systems that addresses human challenges.My doctoral research introduced the sub-theme, Software Engineering for Intelligent Systems. The latter sub-theme explores the concept of intelligence from the angle of its requirements and design within software systems such as learning technologies / environments. The research involves the exploration of the interplay between technologies and theories for intelligent/smart virtual platforms and learning management systems. This multidisciplinary research brings together ideas from diverse disciplines and/or sub-disciplines such as artificial intelligence, human computer interaction, software engineering and learning theories. Ideas from the stated research sub-theme have been published, including publications in journals and presentation in e-Assessment in Practice, a symposium organised by the Defence Academy of United Kingdom, Cranfield University, UK. Some of the research outputs include a new pedagogic-driven software design metamodel; cognitive process visibility, intelligent authoring tool design characteristics, among others. The referred metamodel is underpinned by the synthesized and augmented ontological and epistemological meanings of two conventional theories that have never been utilized or integrated within a smart learning environment prior to its conception in the aforementioned research works.Also, within the IS theme, I am interested in security and privacy of data / information in storage and in transition, as well as security of applications running on information systems.

#	Certificate	School	Year
1.	Ph.D (Software Engineering and eLearning)	De Montfort University, Leicester, UK.	2012

Application of Machine Learning to Security and Privacy Issues in Internet of Things IoT : A Systematic Review

IoT devices are points of system vulnerability through which the system can be attacked. Machine Learning ML has been applied to detect threats in real-time. Different ML techniques and their various algorithms have been applied as solutions in various scenarios in order to meet security and privacy SP requirements for the IoT system. One of the areas in which ML has been successfully applied is in intrusion detection anomaly, signature or hybrid and has been shown to perform better than traditional means in flagging new trends of attacks. This paper presents a systematic review of the literature on the application of machine learning techniques for intrusion detection in IoT.Ten 10 years 2011-2021 data comprising academic articles are sourced from two databases IEEE and Proquest using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses PRISMA framework. Results showed that intrusion of privacy in IoT can be significantly detected with ML techniques. Furthermore, some of the common metrics used in confirming the validity of the proposed tecniques were identified.

ADENOWO ADETOKUNBO is a Associate Professor / Reader at the Department of Computer Science

ADENOWO has a Ph.D in Software Engineering and eLearning from De Montfort University, Leicester, UK.