Oluwakemi Christiana Abikoye

@unilorin.edu.ng

Computer Science/ Communication and Information Sciences
University of Ilorin

Oluwakemi Christiana Abikoye


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https://researchid.co/abikoye.o

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence, Computer Networks and Communications, Human-Computer Interaction
42

Scopus Publications

1326

Scholar Citations

21

Scholar h-index

32

Scholar i10-index

Scopus Publications

  • Block lightweight encryption scheme for securing internet of things data and information
    Esau Taiwo OLADIPUPO, David Olalekan OLAYEMI, Christiana Oluwakemi ABIKOYE, Abidemi Emmanuel ADENIYI, Oluwasegun Julius AROBA, Joseph Bamidele AWOTUNDE
    Systems and Soft Computing, 2026
    Healthcare Internet of Things (HIoT) systems increasingly process multimedia data, yet existing Lightweight Cryptosystems (LWCs) often provide insufficient confusion, diffusion, and security due to their short key and block sizes. These limitations also expose them to key-related attacks and Cipher Block Chaining (CBC) eroding. To address these challenges, this work proposes a new multimedia-oriented LWC in which only a single block is encrypted or decrypted, significantly reducing computational overhead. Elliptic Curve Diffie–Hellman (ECDH) is employed for key establishment, and a dedicated Image_XOR module—combining secure pseudorandom number generation with XOR operations—is designed to enhance confusion, diffusion, and nonlinearity. The scheme applies SHA-256 to the concatenated bytes of the Shared Secret Key (SSK) and the plain image to generate a hash value (hashval). The plain image, SSK, and hashval are processed through the Image_XOR module to produce the encrypted image, while hashval is further encrypted using a Modified Caesar cipher (MCaesar). Decryption reverses the operations using the corresponding MCaesar_Dec module. Comprehensive evaluations—including sensitivity, statistical analyses, and noise-attack resistance—demonstrate that the proposed LWC exhibits strong robustness, high key and plaintext sensitivity, and superior performance relative to classical LWC designs. Its very low processing time and reduced memory footprint indicate suitability for real-time deployment on resource-constrained IoT devices. Overall, the findings confirm that the proposed LWC achieves strong security with minimal resource consumption, making it highly suitable for modern HIoT environments.
  • An Improved Phishing URL Detection Using Machine Learning Methods
    Joseph Bamidele Awotunde, Christiana Oluwakemi Abikoye, Agbotiname Lucky Imoize, Youssef Mejdoub, Olamilekan Abdulazeez Imran
    Lecture Notes in Networks and Systems, 2026
  • A Diabetes Management-Based Personalized Food Recommender System
    Christiana Oluwakemi Abikoye, Agbotiname Lucky Imoize, Youssef Mejdoub, Adamah Morenikeji Kossiwa, Joseph Bamidele Awotunde
    Lecture Notes in Networks and Systems, 2026
  • AI in Education Technologies: New Development and Innovative Practices
    Usman-Hamza Fatimah Enehezei, Oluwakemi Christiana Abikoye, Muyideen Abdulraheem, Joseph Bamidele Awotunde, Paul Olujide Adebayo, Idowu Dauda Oladipo, Evelyn Damilola Temitayo
    Advanced AI Technologies for Improving Education Systems, 2026
    The rapidly developing field of Artificial Intelligence (AI) has the potential to completely transform human social interactions. AI has started to create new teaching and learning tools in the field of education, which are currently being tested in various settings. Recent technological developments and the growing rate of adoption of AI technologies necessitate the identification and analysis of issues pertaining to their implementation in the education sector because the field is linked to extremely dynamic business environments that are managed and maintained by information systems. Therefore, this chapter explores the transformative impact of AI on educational technologies, highlighting new developments and innovative practices that enhance teaching and learning experiences. It examines the integration of AI-driven tools in educational settings, addressing their potential to personalize learning, improve student engagement, and streamline administrative processes. The chapter investigates the challenges and ethical considerations associated with the implementation of AI in education, such as privacy concerns and the digital divide.
  • Smart Hospital and Healthcare Facilities
    Oluwakemi Christiana Abikoye, Usman-Hamza Fatimah, Muyideen Abdulrahee, Joseph Bamidele Awotunde, Paul Olujide Adebayo, Idowu Dauda Oladipo, Evelyn Damilola Temitayo
    Medical Internet of Things Perspectives Impact and Challenges, 2026
    The chapter explores the transformative potential of smart hospital and healthcare facilities, emphasizing their role in modernizing healthcare delivery through the integration of advanced technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), robotics, and automation. It highlights how smart systems enhance patient care, operational efficiency, and decision-making by enabling real-time monitoring, predictive analytics, and data-driven interventions. Key innovations discussed include IoT-enabled asset management, smart beds, automated surgical theaters, and intelligent workforce management systems. These advancements support personalized treatment, reduce human error, and optimize resource allocation, contributing to improved clinical outcomes and reduced healthcare costs. The chapter also addresses the implementation challenges, such as interoperability with legacy systems, high costs, cybersecurity risks, and resistance from healthcare personnel. Ethical and legal considerations, including data privacy and algorithmic bias, are underscored as critical factors in the adoption of smart healthcare technologies. Ultimately, the chapter asserts that while smart hospitals promise a more efficient, responsive, and patient-centered future, their successful deployment demands coordinated efforts, strategic investment, and inclusive policy frameworks. This digital transformation holds the potential to redefine healthcare ecosystems and foster sustainable, high-quality care delivery on a global scale.
  • Federated Learning Augmented with Convolutional Neural Networks for Brain Cancer Classification
    Joseph Bamidele Awotunde, Christiana Oluwakemi Abikoye, Biswajit Brahma, Esau Taiwo Oladipupo, Anjan Bandyopadhyay
    Procedia Computer Science, 2025
    Leveraging MRI images for the categorization of brain tumors is a critical yet complex endeavor within the realm of medical imaging. Precise identification is crucial for prompt and effective treatment; however, the intricate nature of tumor morphology and variability in imaging often pose obstacles. Traditional practices largely rely on the manual examination of MRI images, supplemented by classic machine learning (ML) strategies. However, these techniques typically lack the robustness and scalability necessary for precise and automated tumor categorization. Key challenges include extensive manual processing, vulnerability to human error, limited ability to handle voluminous datasets, and insufficient adaptability to diverse tumor forms and imaging scenarios. To address these challenges, this paper introduces the use of federated learning, a ML-based model that integrates data from various entities, coupled with Convolutional Neural Networks (CNNs) for the classification of brain cancer. Federated learning facilitates the decentralized training of models across numerous clients while preserving the confidentiality of data, thus meeting the critical demand for privacy in the management of medical data. The model’s design incorporates transfer learning and a pre-trained CNN to refine its performance on the brain tumor dataset. The empirical evidence suggests that this integrated approach surpasses conventional techniques in the precise classification of brain cancer types. These insights underscore the promise of federated learning in conjunction with CNNs for medical image analysis, particularly in diagnosing brain cancer. This methodology could enhance the precision and efficiency of cancer classification, leading to improved treatment strategies and, ultimately, better patient care outcomes.
  • Secured textual medical information using a modified LSB image steganography technique
    Roseline Oluwaseun Ogundokun, Oluwakemi Christiana Abikoye, Ezekiel Adebayo Ogundepo, Akinbowale Nathaniel Babatunde, Abdul Rahman Tosho Abdulahi, Aditya Kumar Sahu
    Securing the Digital World A Comprehensive Guide to Multimedia Security, 2025
    Health professionals are increasingly concerned with the welfare of their patients and the security of their medical records. With the shift toward electronic methods for obtaining and recording patient information, these records have become more vulnerable to cyberattacks. Ensuring that unauthorized individuals do not gain access to sensitive medical information is paramount. This chapter aims to enhance the security of textual medical records using an improved least significant bit (LSB) steganography technique. The objective is to develop a robust medical information system that secures patient data against potential cyber threats by implementing a modified LSB procedure called circular shift LSB steganography. The proposed system was developed and programmed in the MATLAB 2018a environment. The enhancement involved rational bit shift operations to improve the traditional LSB steganography method. The performance of the modified LSB technique was assessed using key metrics such as peak signal-to-noise ratio (PSNR), mean squared error (MSE), and the number of shifts. The modified LSB method demonstrated superior performance compared to traditional LSB methods. Quantitative analysis revealed PSNR values ranging from 74.3458 to 80.364, indicating higher image quality and reduced distortion. MSE values ranged from 0.002391 to 0.000598, showing minimal error and high fidelity of the stego images. Additionally, the number of shifts used in the embedding process ranged from 32,640 to 88,410, enhancing the security and robustness of the stego images. The enhanced LSB steganography technique, employing rational bit shift operations, outperformed traditional LSB methods regarding robustness, capacity, and imperceptibility. The introduction of the number of shifts as a new output measure further validated the improved security and effectiveness of the proposed method. The results confirm that the updated LSB technique provides a more secure solution for protecting textual medical records against unauthorized access and cyber threats. Future research should explore further optimization of the bit shift operations to enhance the security and efficiency of the LSB steganography technique. Additionally, expanding the application of this method to other types of sensitive data and evaluating its performance in different environments and scenarios will help establish its broader utility and effectiveness.
  • Detection and Classification of Potato Leaves Diseases Using Convolutional Neural Network and Adam Optimizer
    Shakirat Aderonke Salihu, Sunday Olamilekan Adebayo, Oluwakemi Christiana Abikoye, Fatima Ehenezie Usman-Hamza, Modinat Abolore Mabayoje, Biswajit Brahma, Anjan Bandyopadhyay
    Procedia Computer Science, 2025
    This study explores the development of a Convolutional Neural Network (CNN) with Adam Optimizer for detecting potato leaf blight, a critical concern in agriculture due to the economic importance of potatoes. The research focuses on developing a highly accurate model to distinguish between healthy and diseased potato leaves using image data. Key steps include dataset collection, image preprocessing with scaling, augmentation, and normalization, and the construction of a CNN architecture featuring convolutional, max-pooling, dense layers, and dropout regularization. The model’s performance, evaluated through accuracy, precision, recall, and F1-scores derived from confusion matrix analysis, achieved an impressive 96.88% accuracy. Specific detection metrics include 0.76 precision, 0.93 recall, and 0.84 F1-score for healthy leaves, and near-perfect scores for Late and Early Blight detection. The findings underscore the efficacy of CNNs combined with Adam optimization in agricultural disease diagnosis, offering a reliable tool for early potato leaf blight detection.
  • A Lightweight Image Cryptosystem for Cloud-Assisted Internet of Things
    Esau Taiwo Oladipupo, Oluwakemi Christiana Abikoye, Joseph Bamidele Awotunde
    Applied Sciences Switzerland, 2024
    Cloud computing and the increasing popularity of 5G have greatly increased the application of images on Internet of Things (IoT) devices. The storage of images on an untrusted cloud has high security and privacy risks. Several lightweight cryptosystems have been proposed in the literature as appropriate for resource-constrained IoT devices. These existing lightweight cryptosystems are, however, not only at the risk of compromising the integrity and security of the data but also, due to the use of substitution boxes (S-boxes), require more memory space for their implementation. In this paper, a secure lightweight cryptography algorithm, that eliminates the use of an S-box, has been proposed. An algorithm termed Enc, that accepts a block of size n divides the block into L n R bits of equal length and outputs the encrypted block as follows: E=L⨂R⨁R, where ⨂ and ⨁ are exclusive-or and concatenation operators, respectively, was created. A hash result, hasR=SHA256P⨁K, was obtained, where SHA256, P, and K are the Secure Hash Algorithm (SHA−256), the encryption key, and plain image, respectively. A seed, S, generated from enchash=Enchashenc,K, where hashenc is the first n bits of hasR, was used to generate a random image, Rim. An intermediate image, intimage=Rim⨂P, and cipher image, C=Encintimage,K, were obtained. The proposed scheme was evaluated for encryption quality, decryption quality, system sensitivity, and statistical analyses using various security metrics. The results of the evaluation showed that the proposed scheme has excellent encryption and decryption qualities that are very sensitive to changes in both key and plain images, and resistance to various statistical attacks alongside other security attacks. Based on the result of the security evaluation of the proposed cryptosystem termed Hash XOR Permutation (HXP), the study concluded that the security of the cryptography algorithm can still be maintained without the use of a substitution box.
  • Ethnicity and Biometric Uniqueness: Iris Pattern Individuality in a West African Database
    John Daugman, Cathryn Downing, Oluwatobi Noah Akande, Oluwakemi Christiana Abikoye
    IEEE Transactions on Biometrics Behavior and Identity Science, 2024
    We conducted more than 1.3 million comparisons of iris patterns encoded from images collected at two Nigerian universities, which constitute the newly available African Human Iris (AFHIRIS) database. The purpose was to discover whether ethnic differences in iris structure and appearance such as the textural feature size, as contrasted with an all-Chinese image database or an American database in which only 1.53% were of African-American heritage, made a material difference for iris discrimination. We measured a reduction in entropy for the AFHIRIS database due to the coarser iris features created by the thick anterior layer of melanocytes, and we found stochastic parameters that accurately model the relevant empirical distributions. Quantile-Quantile analysis revealed that a very small change in operational decision thresholds for the African database would compensate for the reduced entropy and generate the same performance in terms of resistance to False Matches. We conclude that despite demographic difference, individuality can be robustly discerned by comparison of iris patterns in this West African population.
  • Enhancing Security and Ownership Protection of Neural Networks Using Watermarking Techniques: A Systematic Literature Review Using PRISMA
    Roseline Oluwaseun Ogundokun, Christiana Oluwakemi Abikoye, Aditya Kumar Sahu, Akinyemi Omololu Akinrotimi, Akinbowale Nathaniel Babatunde, Peter O. Sadiku, Omosola Jacob Olabode
    Multimedia Watermarking Latest Developments and Trends, 2024
  • SMSPROTECT: An automatic smishing detection mobile application
    Oluwatobi Noah Akande, Oluwadara Gbenle, Oluwakemi Christiana Abikoye, Rasheed Gbenga Jimoh, Hakeem Babalola Akande, Abdullateef O. Balogun, Anuoluwapo Fatokun
    ICT Express, 2023
  • Securing Critical User Information over the Internet of Medical Things Platforms Using a Hybrid Cryptography Scheme
    Oluwakemi Christiana Abikoye, Esau Taiwo Oladipupo, Agbotiname Lucky Imoize, Joseph Bamidele Awotunde, Cheng-Chi Lee, Chun-Ta Li
    Future Internet, 2023
  • An Efficient Authenticated Elliptic Curve Cryptography Scheme for Multicore Wireless Sensor Networks
    Esau Taiwo Oladipupo, Oluwakemi Christiana Abikoye, Agbotiname Lucky Imoize, Joseph Bamidele Awotunde, Ting-Yi Chang, Cheng-Chi Lee, Dinh-Thuan Do
    IEEE Access, 2023
  • Analytical Study on LSB-Based Image Steganography Approach
    Oluwakemi Christiana Abikoye, Roseline Oluwaseun Ogundokun, Sanjay Misra, Akasht Agrawal
    Lecture Notes in Electrical Engineering, 2022
  • Improving Optimization Prowess of Ant Colony Algorithm Using Bat Inspired Algorithm
    Hakeem Babalola Akande, Oluwakemi Christiana Abikoye, Oluwatobi Noah Akande, Rasheed Gbenga Jimoh
    Proceedings of the 5th International Conference on Information Technology for Education and Development Changing the Narratives Through Building A Secure Society with Disruptive Technologies Ited 2022, 2022
  • Big Data Analytics of IoT-Based Cloud System Framework: Smart Healthcare Monitoring Systems
    Joseph Bamidele Awotunde, Rasheed Gbenga Jimoh, Roseline Oluwaseun Ogundokun, Sanjay Misra, Oluwakemi Christiana Abikoye
    Internet of Things, 2022
  • TWEERIFY: A Web-Based Sentiment Analysis System Using Rule and Deep Learning Techniques
    Oluwatobi Noah Akande, Enemuo Stephen Nnaemeka, Oluwakemi Christiana Abikoye, Hakeem Babalola Akande, Abdullateef Balogun, Joyce Ayoola
    Lecture Notes on Data Engineering and Communications Technologies, 2022
  • English to Yoruba short message service speech and text translator for android phones
    Akinbowale Nathaniel Babatunde, Christiana Oluwakemi Abikoye, Abdulkarim Ayopo Oloyede, Roseline Oluwaseun Ogundokun, Afeez Adeshina Oke, Hafsat Omolola Olawuyi
    International Journal of Speech Technology, 2021
  • Efficiency of LSB steganography on medical information
    Oluwakemi Christiana Abikoye, Roseline Oluwaseun Ogundokun
    International Journal of Electrical and Computer Engineering, 2021
  • Ensemble models for predicting warts treatment methods
    Journal of Engineering Science and Technology, 2021
  • Malicious uniform resource locator detection using wolf optimization algorithm and random forest classifier
    Kayode S. Adewole, Muiz O. Raheem, Oluwakemi C. Abikoye, Adeleke R. Ajiboye, Tinuke O. Oladele, Muhammed K. Jimoh, Dayo R. Aremu
    Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics Theories and Applications, 2021
  • A safe and secured medical textual information using an improved LSB image steganography
    Roseline Oluwaseun Ogundokun, Oluwakemi Christiana Abikoye
    International Journal of Digital Multimedia Broadcasting, 2021
  • Anomaly Android Malware Detection: A Comparative Analysis of Six Classifiers
    Benjamin A. Gyunka, Oluwakemi C. Abikoye, Adekeye S. Adekunle
    Communications in Computer and Information Science, 2021
  • Application of Machine Learning for Ransomware Detection in IoT Devices
    Roseline Oluwaseun Ogundokun, Joseph Bamidele Awotunde, Sanjay Misra, Oluwakemi Christiana Abikoye, Oluwafemi Folarin
    Studies in Computational Intelligence, 2021
  • Application of Internet of Thing and Cyber Physical System in Industry 4.0 Smart Manufacturing
    Oluwakemi Christiana Abikoye, Amos Orenyi Bajeh, Joseph Bamidele Awotunde, Ahmed Oloduowo Ameen, Hammed Adeleye Mojeed, Muyideen Abdulraheem, Idowu Dauda Oladipo, Shakirat Aderonke Salihu
    Advances in Science Technology and Innovation, 2021
  • Internet of Robotic Things: Its Domain, Methodologies, and Applications
    Amos Orenyi Bajeh, Hammed Adeleye Mojeed, Ahmed Oloduowo Ameen, Oluwakemi Christiana Abikoye, Shakirat Aderonke Salihu, Muyideen Abdulraheem, Idowu Dauda Oladipo, Joseph Bamidele Awotunde
    Advances in Science Technology and Innovation, 2021
  • A novel technique to prevent SQL injection and cross-site scripting attacks using Knuth-Morris-Pratt string match algorithm
    Oluwakemi Christiana Abikoye, Abdullahi Abubakar, Ahmed Haruna Dokoro, Oluwatobi Noah Akande, Aderonke Anthonia Kayode
    Eurasip Journal on Information Security, 2020
  • A safe and secured iris template using steganography and cryptography
    Oluwakemi Christiana Abikoye, Umar Abdulraheem Ojo, Joseph Bamidele Awotunde, Roseline Oluwaseun Ogundokun
    Multimedia Tools and Applications, 2020
  • Android malware detection through machine learning techniques: A review
    Abikoye Oluwakemi Christiana, Benjamin Aruwa Gyunka, Akande Noah
    International Journal of Online and Biomedical Engineering, 2020
  • Optimizing android malware detection via ensemble learning
    Abikoye Oluwakemi Christianah, Benjamin Aruwa Gyunka, Akande Noah Oluwatobi
    International Journal of Interactive Mobile Technologies, 2020
  • Implementation of a Framework for Healthy and Diabetic Retinopathy Retinal Image Recognition
    Oluwatobi Noah Akande, Oluwakemi Christiana Abikoye, Aderonke Anthonia Kayode, Yema Lamari
    Scientifica, 2020
  • Modified Least Significant Bit Technique for Securing Medical Images
    Roseline Oluwaseun Ogundokun, Oluwakemi Christiana Abikoye, Sanjay Misra, Joseph Bamidele Awotunde
    Lecture Notes in Business Information Processing, 2020
  • Speech recognition system: Overview of the state-of-the-arts
    International Journal of Engineering Research and Technology, 2020
  • A Dynamic Round Triple Data Encryption Standard Cryptographic Technique for Data Security
    Oluwatobi Noah Akande, Oluwakemi Christiana Abikoye, Aderonke Anthonia Kayode, Oladele Taye Aro, Oluwaseun Roseline Ogundokun
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2020
  • COMPARATIVE STUDY of TWO DIVIDE and CONQUER SORTING ALGORITHMS: QUICKSORT and MERGESORT
    Oladipupo Esau Taiwo, Abikoye Oluwakemi Christianah, Akande Noah Oluwatobi, Kayode Anthonia Aderonke, Adeniyi Jide kehinde
    Procedia Computer Science, 2020
  • Application of computational intelligence models in IoMT big data for heart disease diagnosis in personalized health care
    Amos Orenyi Bajeh, Oluwakemi Christiana Abikoye, Hammed Adeleye Mojeed, Shakirat Aderonke Salihu, Idowu Dauda Oladipo, Muyideen Abdulraheem, Joseph Bamidele Awotunde, Arun Kumar Sangaiah, Kayode S. Adewole
    Intelligent Iot Systems in Personalized Health Care, 2020
  • Modified advanced encryption standard algorithm for information security
    Oluwakemi Christiana Abikoye, Ahmad Dokoro Haruna, Abdullahi Abubakar, Noah Oluwatobi Akande, Emmanuel Oluwatobi Asani
    Symmetry, 2019
  • A Secured One Time Password Authentication Technique using (3, 3) Visual Cryptography Scheme
    Abikoye Oluwakemi Christiana, Akande Noah Oluwatobi, Garuba Ayomide Victory, Ogundokun Roseline Oluwaseun
    Journal of Physics Conference Series, 2019
  • Evaluation of the scholastic performance of students in 12 programs from a private university in the south-west geopolitical zone in Nigeria
    Roseline O. Ogundokun, Marion O. Adebiyi, Oluwakemi C. Abikoye, Tinuke O. Oladele, Adewale F. Lukman, Abidemi E. Adeniyi, Adekanmi A. Adegun, Babatunde Gbadamosi, Noah O. Akande
    F1000research, 2019
  • Usability evaluaton of users' experience on some existing E-Commerce platforms
    Library Philosophy and Practice, 2019
  • Electronic Medical Information Encryption Using Modified Blowfish Algorithm
    Noah Oluwatobi Akande, Christiana Oluwakemi Abikoye, Marion Olubunmi Adebiyi, Anthonia Aderonke Kayode, Adekanmi Adeyinka Adegun, Roseline Oluwaseun Ogundokun
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2019

RECENT SCHOLAR PUBLICATIONS

  • Cyberbullying detection and prevention system for enhancing online platform safety using maximum entropy model
    OC Abikoye, O Gboyega, RO Ogundokun, AO Babatunde, CC Lee
    Security and Privacy 8 (2), e480 , 2025
    2025
    Citations: 4
  • Secured textual medical information using a modified LSB image steganography technique
    RO Ogundokun, OC Abikoye, EA Ogundepo, AN Babatunde, ...
    Securing the Digital World, 82-101 , 2025
    2025
    Citations: 7
  • Detection and classification of potato leaves diseases using convolutional neural network and Adam optimizer
    SA Salihu, SO Adebayo, OC Abikoye, FE Usman-Hamza, MA Mabayoje, ...
    Procedia Computer Science 258, 2-17 , 2025
    2025
    Citations: 9
  • A lightweight image cryptosystem for cloud-assisted internet of things
    ET Oladipupo, OC Abikoye, JB Awotunde
    Applied Sciences 14 (7), 2808 , 2024
    2024
    Citations: 16
  • Efficient ensemble-based phishing website classification models using feature importance attribute selection and hyper parameter tuning approaches
    RG Jimoh, AM OYELAKIN
    Journal of Information Technology and Computing 4 (2), 1-10 , 2023
    2023
    Citations: 3
  • Ethnicity and biometric uniqueness: iris pattern individuality in a West African database
    J Daugman, C Downing, ON Akande, OC Abikoye
    IEEE Transactions on Biometrics, Behavior, and Identity Science 6 (1), 79-86 , 2023
    2023
    Citations: 2
  • SMSPROTECT: An automatic smishing detection mobile application
    ON Akande, O Gbenle, OC Abikoye, RG Jimoh, HB Akande, AO Balogun, ...
    ICT Express 9 (2), 168-176 , 2023
    2023
    Citations: 62
  • Securing critical user information over the internet of medical things platforms using a hybrid cryptography scheme
    OC Abikoye, ET Oladipupo, AL Imoize, JB Awotunde, CC Lee, CT Li
    Future Internet 15 (3), 99 , 2023
    2023
    Citations: 32
  • An efficient authenticated elliptic curve cryptography scheme for multicore wireless sensor networks
    ET Oladipupo, OC Abikoye, AL Imoize, JB Awotunde, TY Chang, CC Lee, ...
    IEEE Access 11, 1306-1323 , 2023
    2023
    Citations: 48
  • Performance analysis of selected classification algorithms on android malware detection
    GK Afolabi-Yusuf, YO Olatunde, KY Obiwusi, MO Yusuf, OC Abikoye
    International Journal of Software Engineering and Computer Systems 9 (2 … , 2023
    2023
    Citations: 1
  • Classification of Music Genres Using Catboost Algorithm
    SA Salihu, IO Lawal, OC Abikoye, AO Balogun, HA Mojeed, ...
    2023
  • AFHIRIS: African human iris dataset (version 1)
    O Akande, N Ojimba, A Oghenekaro, O Abikoye, R Ogundokun, ...
    F1000Research 11, 1549 , 2022
    2022
    Citations: 2
  • Improving Optimization Prowess of Ant Colony Algorithm Using Bat Inspired Algorithm
    HB Akande, OC Abikoye, ON Akande, RG Jimoh
    2022 5th Information Technology for Education and Development (ITED), 1-5 , 2022
    2022
  • Improved authenticated elliptic curve cryptography scheme for resource starve applications
    ET Oladipupo, OC Abikoye
    Computer Science and Information Technologies 3 (3), 169-185 , 2022
    2022
    Citations: 8
  • An enhanced information retrieval-based bug localization system with code coverage, stack traces, and spectrum information.
    SA Salihu, OC Abikoye
    2022
  • Modified Playfair cryptosystem for improved data security
    ET Oladipupo, OC Abikoye
    Computer Science and Information Technologies 3 (1), 51-64 , 2022
    2022
    Citations: 6
  • TWEERIFY: a web-based sentiment analysis system using rule and deep learning techniques
    ON Akande, ES Nnaemeka, OC Abikoye, HB Akande, A Balogun, ...
    Proceedings of International Conference on Computational Intelligence and … , 2022
    2022
    Citations: 7
  • Big data analytics of iot-based cloud system framework: Smart healthcare monitoring systems
    JB Awotunde, RG Jimoh, RO Ogundokun, S Misra, OC Abikoye
    Artificial intelligence for cloud and edge computing, 181-208 , 2022
    2022
    Citations: 89
  • An Enhanced Blowfsh Algorithm with Reduced Computational Speed
    GM Damola, R Jimoh, O Abikoye
    2022
  • Efficiency of LSB steganography on medical information
    OC Abikoye, RO Ogundokun
    International Journal of Electrical and Computer Engineering (IJECE) 11 (5 … , 2021
    2021
    Citations: 18

MOST CITED SCHOLAR PUBLICATIONS

  • A novel technique to prevent SQL injection and cross-site scripting attacks using Knuth-Morris-Pratt string match algorithm
    OC Abikoye, A Abubakar, AH Dokoro, ON Akande, AA Kayode
    EURASIP Journal on Information Security 2020 (1), 14 , 2020
    2020
    Citations: 102
  • Modified advanced encryption standard algorithm for information security
    OC Abikoye, AD Haruna, A Abubakar, NO Akande, EO Asani
    Symmetry 11 (12), 1484 , 2019
    2019
    Citations: 101
  • Big data analytics of iot-based cloud system framework: Smart healthcare monitoring systems
    JB Awotunde, RG Jimoh, RO Ogundokun, S Misra, OC Abikoye
    Artificial intelligence for cloud and edge computing, 181-208 , 2022
    2022
    Citations: 89
  • Application of internet of thing and cyber physical system in Industry 4.0 smart manufacturing
    OC Abikoye, AO Bajeh, JB Awotunde, AO Ameen, HA Mojeed, ...
    Emergence of cyber physical system and IoT in smart automation and robotics … , 2021
    2021
    Citations: 78
  • Efficient Data Hiding System using Cryptography and Steganography.
    AJ Abikoye, O.C., Adewole, K. S. & Oladipupo
    International Journal of Applied Information Systems (IJAIS). 4 (11), 6-11 , 2012
    2012
    Citations: 73
  • A safe and secured iris template using steganography and cryptography
    OC Abikoye, UA Ojo, JB Awotunde, RO Ogundokun
    Multimedia Tools and Applications 79 (31), 23483-23506 , 2020
    2020
    Citations: 69
  • SMSPROTECT: An automatic smishing detection mobile application
    ON Akande, O Gbenle, OC Abikoye, RG Jimoh, HB Akande, AO Balogun, ...
    ICT Express 9 (2), 168-176 , 2023
    2023
    Citations: 62
  • An efficient authenticated elliptic curve cryptography scheme for multicore wireless sensor networks
    ET Oladipupo, OC Abikoye, AL Imoize, JB Awotunde, TY Chang, CC Lee, ...
    IEEE Access 11, 1306-1323 , 2023
    2023
    Citations: 48
  • Offline signature recognition & verification using neural network
    OC Abikoye, MA Mabayoje, R Ajibade
    International Journal of Computer Applications 35 (2), 44-51 , 2011
    2011
    Citations: 43
  • A rule-based expert system for mineral identification
    IO Folorunso, OC Abikoye, RG Jimoh, KS Raji
    Journal of Emerging Trends in Computing and Information Sciences 3 (2), 205-210 , 2012
    2012
    Citations: 41
  • Application of machine learning for ransomware detection in IoT devices
    RO Ogundokun, JB Awotunde, S Misra, OC Abikoye, O Folarin
    Artificial intelligence for cyber security: methods, issues and possible … , 2021
    2021
    Citations: 37
  • Analysis of Human Factors in Cyber Security: A Case Study of Anonymous Attack on Hbgary
    BA Gyunka, AO Christiana
    Computing and Information Systems Journal 21 (2), 10-18 , 2017
    2017
    Citations: 35
  • Securing critical user information over the internet of medical things platforms using a hybrid cryptography scheme
    OC Abikoye, ET Oladipupo, AL Imoize, JB Awotunde, CC Lee, CT Li
    Future Internet 15 (3), 99 , 2023
    2023
    Citations: 32
  • A safe and secured medical textual information using an improved LSB image steganography
    RO Ogundokun, OC Abikoye
    International Journal of Digital Multimedia Broadcasting 2021 (1), 8827055 , 2021
    2021
    Citations: 32
  • A dynamic round triple data encryption standard cryptographic technique for data security
    ON Akande, OC Abikoye, AA Kayode, OT Aro, OR Ogundokun
    International Conference on Computational Science and Its Applications, 487-499 , 2020
    2020
    Citations: 28
  • Iris feature extraction for personal identification using fast wavelet transform (FWT)
    C Abikoye Oluwakemi, JS Sadiku, S Adewole Kayode, G Jimoh Rasheed
    structure 6 (9) , 2014
    2014
    Citations: 27
  • Android malware detection through machine learning techniques: A review
    A Christiana, B Gyunka, A Noah
    International Association of Online Engineering , 2020
    2020
    Citations: 26
  • A secured one time password authentication technique using (3, 3) visual cryptography scheme
    OC Abikoye, NO Akande, AV Garuba, RO Ogundokun
    2019
    Citations: 25
  • Internet of robotic things: its domain, methodologies, and applications
    AO Bajeh, HA Mojeed, AO Ameen, OC Abikoye, SA Salihu, ...
    Emergence of Cyber Physical System and IoT in Smart Automation and Robotics … , 2021
    2021
    Citations: 21
  • Application of computational intelligence models in IoMT big data for heart disease diagnosis in personalized health care
    AO Bajeh, OC Abikoye, HA Mojeed, SA Salihu, ID Oladipo, ...
    Intelligent IoT systems in personalized health care, 177-206 , 2021
    2021
    Citations: 21