Kehinde Babaagba
kehinde babaagba

Dr Kehinde Babaagba

Lecturer

 0131 455 5024

  K.Babaagba@napier.ac.uk

  

Biography

Kehinde Oluwatoyin Babaagba is a Lecturer at the School of Computing at Edinburgh Napier University. She gained a First Class BSC (Hons) in Computer Science from Redeemers University, Nigeria, where she also emerged as the best graduating student of her set. She also holds an MSC in Computing Information Engineering (Distinction) from Robert Gordon University, where she also emerged as class prize winner for the MSC in Computing Information Engineering programme. She holds a PhD in Computing from Edinburgh Napier University. She worked as Associate Lecturer during her PhD and University Tutor at Edinburgh Napier University. Prior to joining Napier, she worked as Assistant Lecturer at Redeemer’s University and Academic Trainee at Osun State University, Nigeria.

She has made contributions to the research community as well as industries within the context of applying AI techniques to solve real-world problems. During her masters, she worked with the Institute for Innovation, Design & Sustainability of Robert Gordon University on using competing mutating agents as a tool for improving the performance of genetic algorithms. Furthermore, she also contributed to the design of a system for analyzing a corpus of malicious instances using machine-learning strategies. Her PhD research paved the way towards prediction of malware evolution, which contributes invaluable knowledge to building robust systems that defend self-mutating malware. These have made significant contributions to cybersecurity specialists and researchers in securing the UK’s networked and online activities from misuse, as well as promote better wide-spread adoption of trusted and secure Artificial Intelligence (AI) systems across the UK’s digital economy. She has been able to publish some academic papers (https://scholar.google.com/citations?view_op=list_works&hl=en&user=5WYIQUsAAAAJ). Some of which have led to awards like Outstanding Student Contribution, Best Student Paper nomination and Excellent Oral Presentation.

More recently, Kehinde’s research interests include transfer learning, computer vision, generative adversarial networks as well as other machine learning applications in cybersecurity. She is also involved in teaching and supervision of various honors and masters’ projects. Besides, Kehinde is very passionate about mentoring young students interested in software engineering, data science and cybersecurity, to this end She is a STEM ambassador. This opportunity affords her the privilege of impacting knowledge and encouraging young students in their journey to becoming software engineers, data scientists and security specialists.

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Esteem
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Reviewing

• Finance Chair for the IEEE Conference on Dependable and Secure Computing (IEEE DSC 2022).
• Publication Chair for EvoAPPS 2022 part of Evo* which is the leading conference in Europe for Evolutionary Computation.
• Web and System Management co-chair for the IEEE International Conference on Smart City and Informatization (IEEE iSCI-2021).
• Reviewer for Journals like IEEE Transactions on Industry Informatics, Journal of Cybersecurity Technology, Journal of Security and Communication Networks.
• Participant of Student as Colleagues (SaC) in the review of teaching practices program with Edinburgh Napier University in partnership with the Department of Learning and Teaching Enhancement, from November 2018 to May 2019.
• Workshop Coordinator at the Scotland-wide SICSA (Scottish Informatics and Computer Science Alliance) 2018 PhD Conference.

Projects

• Evolutionary based Generative Adversarial Learning Approach to Metamorphic Malware Detection - SICSA Funded.
• Participant of the Edinburgh Napier University Data Driven Innovation City Deal Project.
• Member of the Curriculum Developers’ Network of Edinburgh Napier University's Data Driven Innovation City Deal project.

Professional Membership

• Member of IEEE including Women in Engineering society and Computational Intelligence society.
• Member of ACM.
• Associate Member of ALT.
• STEM Ambassador under the Scottish STEM Ambassador Hub.

School

Research Groups

Themes

Research Areas

Esteem

Advisory panels and expert committees or witness

  • Society for the Promotion of Evolutionary Computation in Europe and its Surroundings (SPECIES) - Board Member

 

Conference Organising Activity

  • Finance Chair for the IEEE Conference on Dependable and Secure Computing (IEEE DSC 2022).
  • Publication Chair for EvoAPPS 2022 part of Evo* which is the leading conference in Europe for Evolutionary Computation.
  • Web and System Management co-chair for the IEEE International Conference on Smart City and Informatization (IEEE iSCI-2021)
  • Workshop Coordinator at the Scotland-wide SICSA (Scottish Informatics and Computer Science Alliance) 2018 PhD Conference.

 

Fellowships and Awards

  • Associate Fellow of Advance HE
  • Best Paper (3rd place) for the IEEE Conference on Dependable and Secure Computing (IEEE DSC 2022)
  • Outstanding Contribution Award - 2020 Evo* (EuroGP-EvoApplications-EvoCOP-EvoMUSART 2020 conferences, known collectively as EvoStar)
  • Excellent Oral Presentation Award - 2019 ACM International Conference on Educational and Information Technology (ICEIT 2019)

 

Membership of Professional Body

  • Associate Member of Association for Learning Technology
  • STEM Ambassador under the Scottish STEM Ambassador Hub
  • Member of ACM
  • Member of IEEE

 

Public/Community Engagement

  • #DataYou by the Data Skills Gateway
  • Curriculum Developers’ Network of Edinburgh Napier University's Data Driven Innovation City Deal project

 

Reviewing

  • Security and Communication Networks
  • IEEE Transactions on Industry Informatics
  • Journal of Cybersecurity Technology
  • Student as Colleagues (SaC) in the review of teaching practices program with Edinburgh Napier University in partnership with the Department of Learning and Teaching Enhancement

 

Filter by

Date


14 results

Image Forgery Detection using Cryptography and Deep Learning

Conference Proceeding
Oke, A., & Babaagba, K. O. (2024)
Image Forgery Detection using Cryptography and Deep Learning. In Big Data Technologies and Applications. BDTA 2023 (62-78). https://doi.org/10.1007/978-3-031-52265-9_5
The advancement of technology has undoubtedly exposed everyone to a remarkable array of visual imagery. Nowadays, digital technology is eating away the trust and historical co...

Can Federated Models Be Rectified Through Learning Negative Gradients?

Conference Proceeding
Tahir, A., Tan, Z., & Babaagba, K. O. (2024)
Can Federated Models Be Rectified Through Learning Negative Gradients?. In Big Data Technologies and Applications (18-32). https://doi.org/10.1007/978-3-031-52265-9_2
Federated Learning (FL) is a method to train machine learning (ML) models in a decentralised manner, while preserving the privacy of data from multiple clients. However, FL is...

Emotion Recognition on Social Media Using Natural Language Processing (NLP) Techniques

Conference Proceeding
Gomez, L. R., Watt, T., Babaagba, K. O., Chrysoulas, C., Homay, A., Rangarajan, R., & Liu, X. (2023)
Emotion Recognition on Social Media Using Natural Language Processing (NLP) Techniques. In ICISS '23: Proceedings of the 2023 6th International Conference on Information Science and Systems (113-118). https://doi.org/10.1145/3625156.3625173
In recent years, text has been the main form of communication on social media platforms such as Twitter, Reddit, Facebook, Instagram and YouTube. Emotion Recognition from thes...

A Generative Neural Network for Improving Metamorphic Malware Detection in IoT Mobile Devices

Book Chapter
Turnbull, L., Tan, Z., & Babaagba, K. O. (2024)
A Generative Neural Network for Improving Metamorphic Malware Detection in IoT Mobile Devices. In A. Ismail Awad, A. Ahmad, K. Raymond Choo, & S. Hakak (Eds.), Internet of Things Security and Privacy: Practical and Management Perspectives (24-53). Boca Raton: CRC Press. https://doi.org/10.1201/9781003199410-2
There has been an upsurge in malicious attacks in recent years, impacting computer systems and networks. More and more novel malware families aimed at information assets were ...

An Evolutionary based Generative Adversarial Network Inspired Approach to Defeating Metamorphic Malware

Conference Proceeding
Babaagba, K. O., & Wylie, J. (2023)
An Evolutionary based Generative Adversarial Network Inspired Approach to Defeating Metamorphic Malware. In GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation (1753-1759). https://doi.org/10.1145/3583133.3596362
Defeating dangerous families of malware like polymorphic and metamorphic malware have become well studied due to their increased attacks on computer systems and network. Tradi...

A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling

Conference Proceeding
Turnbull, L., Tan, Z., & Babaagba, K. (2022)
A Generative Neural Network for Enhancing Android Metamorphic Malware Detection based on Behaviour Profiling. In 2022 IEEE Conference on Dependable and Secure Computing (DSC). https://doi.org/10.1109/DSC54232.2022.9888906
Malicious software trends show a persistent yearly increase in volume and cost impact. More than 350,000 new malicious or unwanted programs that target various technologies we...

A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs

Conference Proceeding
McLaren, R. A., Babaagba, K., & Tan, Z. (in press)
A Generative Adversarial Network Based Approach to Malware Generation Based on Behavioural Graphs. In The 8th International Conference on machine Learning, Optimization and Data science - LOD 2022
As the field of malware detection continues to grow, a shift in focus is occurring from feature vectors and other common, but easily obfuscated elements to a semantics based a...

Applications of Evolutionary Computation: 25th European Conference, EvoApplications 2022, Held as Part of EvoStar 2022, Madrid, Spain, April 20–22, 2022, Proceedings

Book
Jiménez Laredo, J. L., Hidalgo, J. I., & Babaagba, K. O. (Eds.)
(2022). Applications of Evolutionary Computation: 25th European Conference, EvoApplications 2022, Held as Part of EvoStar 2022, Madrid, Spain, April 20–22, 2022, Proceedings. Cham: Springer. https://doi.org/10.1007/978-3-031-02462-7
This book constitutes the refereed proceedings of the 25th International Conference on Applications of Evolutionary Computation, EvoApplications 2022, held as part of Evo*2022...

Toward Machine Intelligence that Learns to Fingerprint Polymorphic Worms in IoT

Journal Article
Wang, F., Yang, S., Wang, C., Li, Q., Babaagba, K., & Tan, Z. (2022)
Toward Machine Intelligence that Learns to Fingerprint Polymorphic Worms in IoT. International Journal of Intelligent Systems, 37(10), 7058-7078. https://doi.org/10.1002/int.22871
Internet of Things (IoT) is fast growing. Non-PC devices under the umbrella of IoT have been increasingly applied in various fields and will soon account for a significant sha...

Application of evolutionary machine learning in metamorphic malware analysis and detection

Thesis
Babaagba, K. O. Application of evolutionary machine learning in metamorphic malware analysis and detection. (Thesis)
Edinburgh Napier University. Retrieved from http://researchrepository.napier.ac.uk/Output/2801469
In recent times, malware detection and analysis are becoming key issues. A dangerous class of malware is metamorphic malware which is capable of modifying its own code and hid...

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