Oluwakemi Christiana Abikoye

@unilorin.edu.ng

Computer Science/ Communication and Information Sciences
University of Ilorin



                          

https://researchid.co/abikoye.o

RESEARCH, TEACHING, or OTHER INTERESTS

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

32

Scopus Publications

1023

Scholar Citations

18

Scholar h-index

28

Scholar i10-index

Scopus Publications

  • A Lightweight Image Cryptosystem for Cloud-Assisted Internet of Things
    Esau Taiwo Oladipupo, Oluwakemi Christiana Abikoye, and Joseph Bamidele Awotunde
    MDPI AG
    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, and Oluwakemi Christiana Abikoye
    Institute of Electrical and Electronics Engineers (IEEE)
    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.

  • SMSPROTECT: An automatic smishing detection mobile application
    Oluwatobi Noah Akande, Oluwadara Gbenle, Oluwakemi Christiana Abikoye, Rasheed Gbenga Jimoh, Hakeem Babalola Akande, Abdullateef O. Balogun, and Anuoluwapo Fatokun
    Elsevier BV

  • 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, and Chun-Ta Li
    MDPI AG
    The application of the Internet of Medical Things (IoMT) in medical systems has brought much ease in discharging healthcare services by medical practitioners. However, the security and privacy preservation of critical user data remain the reason the technology has not yet been fully maximized. Undoubtedly, a secure IoMT model that preserves individual users’ privacy will enhance the wide acceptability of IoMT technology. However, existing works that have attempted to solve these privacy and insecurity problems are not space-conservative, computationally intensive, and also vulnerable to security attacks. In this paper, an IoMT-based model that conserves the privacy of the data, is less computationally intensive, and is resistant to various cryptanalysis attacks is proposed. Specifically, an efficient privacy-preserving technique where an efficient searching algorithm through encrypted data was used and a hybrid cryptography algorithm that combines the modification of the Caesar cipher with the Elliptic Curve Diffie Hellman (ECDH) and Digital Signature Algorithm (DSA) were projected to achieve user data security and privacy preservation of the patient. Furthermore, the modified algorithm can secure messages during transmission, perform key exchanges between clients and healthcare centres, and guarantee user authentication by authorized healthcare centres. The proposed IoMT model, leveraging the hybrid cryptography algorithm, was analysed and compared against different security attacks. The analysis results revealed that the model is secure, preserves the privacy of critical user information, and shows robust resistance against different cryptanalysis attacks.

  • 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, and Dinh-Thuan Do
    Institute of Electrical and Electronics Engineers (IEEE)
    The need to ensure the longevity of Wireless Sensor Networks (WSNs) and secure their communication has spurred various researchers to come up with various WSN models. Prime among the methods for extending the life span of WSNs is the clustering of Wireless Sensors (WS), which reduces the workload of WS and thereby reduces its power consumption. However, a drastic reduction in the power consumption of the sensors when multicore sensors are used in combination with sensors clustering has not been well explored. Therefore, this work proposes a WSN model that employs clustering of multicore WS. The existing Elliptic Curve Cryptographic (ECC) algorithm is optimized for parallel execution of the encryption/decryption processes and security against primitive attacks. The Elliptic Curve Diffie-Helman (ECDH) was used for the key exchange algorithm, and the Elliptic Curve Digital Signature Algorithm (ECDSA) was used to authenticate the communicating nodes. Security analysis of the model and comparative performance analysis with the existing ones were demonstrated. The security analysis results reveal that the proposed model meets the security requirements and resists various security attacks. Additionally, the projected model is scalable, energy-conservative, and supports data freshness. The results of comparative performance analysis show that the proposed WSN model can efficiently leverage multiprocessors and/or many cores for quicker execution and conserves power usage.

  • Improving Optimization Prowess of Ant Colony Algorithm Using Bat Inspired Algorithm
    Hakeem Babalola Akande, Oluwakemi Christiana Abikoye, Oluwatobi Noah Akande, and Rasheed Gbenga Jimoh
    IEEE
    Metaheuristic algorithms such as Ant Colony Optimization (ACO) algorithm and Bat Optimization Algorithm (BOA) have been widely employed in solving different optimization problems in several fields. ACO is modelled based on the social behaviour of ants that look for appropriate answers to a given optimization issue by recasting it as the case of locating the least expensive path on a weighted graph. A set of parameters linked to graph components (either nodes or edges) whose values are changed by the ants during runtime constitute the pheromone model, which biases the stochastic solution generation process. However, the effectiveness of ACO declines as the quantity of packets rises, making them ineffective for reducing traffic congestion. As more packets are transmitted, their strength decreases, causing packet congestion, rendering them useless for reducing packet traffic congestion. On the contrary, BOA which was modelled after the behavior of bats has also been employed in fixing network routing issues by listening to every sound in a space and taking note of what is going on around it. In order to further improve ACO algorithm and decrease packet traffic congestion, packet loss, and the time it takes a packet to reach its destination in a network system, this study employs the strength of BOA. Results obtained revealed the prowess of BOA in improving the performance of ACO for network packet routing.

  • 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, and Joyce Ayoola
    Springer Nature Singapore

  • Big Data Analytics of IoT-Based Cloud System Framework: Smart Healthcare Monitoring Systems
    Joseph Bamidele Awotunde, Rasheed Gbenga Jimoh, Roseline Oluwaseun Ogundokun, Sanjay Misra, and Oluwakemi Christiana Abikoye
    Springer International Publishing

  • 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, and Hafsat Omolola Olawuyi
    Springer Science and Business Media LLC

  • Efficiency of LSB steganography on medical information
    Oluwakemi Christiana Abikoye and Roseline Oluwaseun Ogundokun
    Institute of Advanced Engineering and Science
    The development of the medical field had led to the transformation of communication from paper information into the digital form. Medical information security had become a great concern as the medical field is moving towards the digital world and hence patient information, disease diagnosis and so on are all being stored in the digital image. Therefore, to improve the medical information security, securing of patient information and the increasing requirements for communication to be transferred between patients, client, medical practitioners, and sponsors is essential to be secured. The core aim of this research is to make available a complete knowledge about the research trends on LSB Steganography Technique, which are applied to securing medical information such as text, image, audio, video and graphics and also discuss the efficiency of the LSB technique. The survey findings show that LSB steganography technique is efficient in securing medical information from intruder.

  • 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, and Dayo R. Aremu
    Springer International Publishing

  • Ensemble models for predicting warts treatment methods


  • Application of Machine Learning for Ransomware Detection in IoT Devices
    Roseline Oluwaseun Ogundokun, Joseph Bamidele Awotunde, Sanjay Misra, Oluwakemi Christiana Abikoye, and Oluwafemi Folarin
    Springer International Publishing

  • 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, and Shakirat Aderonke Salihu
    Springer International Publishing

  • 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, and Joseph Bamidele Awotunde
    Springer International Publishing

  • A safe and secured medical textual information using an improved LSB image steganography
    Roseline Oluwaseun Ogundokun and Oluwakemi Christiana Abikoye
    Hindawi Limited
    Safe conveyance of medical data across unsecured networks nowadays is an essential issue in telemedicine. With the exponential growth of multimedia technologies and connected networks, modern healthcare is a huge step ahead. Authentication of a diagnostic image obtained from a specialist at a remote location which is from the sender is one of the most challenging tasks in an automated healthcare setup. Intruders were found to be able to efficiently exploit securely transmitted messages from previous literature since the algorithms were not efficient enough leading to distortion of information. Therefore, this study proposed a modified least significant bit (LSB) technique capable of protecting and hiding medical data to solve the crucial authentication issue. The application was executed and established by utilizing MATLAB 2018a, and it used a logical bit shift operation for execution. The investigational outcomes established that the proposed technique can entrench medical information without leaving a perceptible falsification in the stego image. The result of this implementation shows that the modified LSB image steganography outperformed the standard LSB technique with a higher PSNR value and lower MSE value when compared with previous research works. The number of shifts was added as a new performance metric for the proposed system. The study concluded that the proposed secured medical information system was evidenced to be proficient in secreting medical information and creating undetectable stego images with slight entrenching falsifications when likened to other prevailing approaches.

  • Anomaly Android Malware Detection: A Comparative Analysis of Six Classifiers
    Benjamin A. Gyunka, Oluwakemi C. Abikoye, and Adekeye S. Adekunle
    Springer International Publishing

  • 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, and Aderonke Anthonia Kayode
    Springer Science and Business Media LLC
    AbstractStructured Query Language (SQL) injection and cross-site scripting remain a major threat to data-driven web applications. Instances where hackers obtain unrestricted access to back-end database of web applications so as to steal, edit, and destroy confidential data are increasing. Therefore, measures must be put in place to curtail the growing threats of SQL injection and XSS attacks. This study presents a technique for detecting and preventing these threats using Knuth-Morris-Pratt (KMP) string matching algorithm. The algorithm was used to match user’s input string with the stored pattern of the injection string in order to detect any malicious code. The implementation was carried out using PHP scripting language and Apache XAMPP Server. The security level of the technique was measured using different test cases of SQL injection, cross-site scripting (XSS), and encoded injection attacks. Results obtained revealed that the proposed technique was able to successfully detect and prevent the attacks, log the attack entry in the database, block the system using its mac address, and also generate a warning message. Therefore, the proposed technique proved to be more effective in detecting and preventing SQL injection and XSS attacks

  • A safe and secured iris template using steganography and cryptography
    Oluwakemi Christiana Abikoye, Umar Abdulraheem Ojo, Joseph Bamidele Awotunde, and Roseline Oluwaseun Ogundokun
    Springer Science and Business Media LLC

  • 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, and Kayode S. Adewole
    Elsevier

  • Modified Least Significant Bit Technique for Securing Medical Images
    Roseline Oluwaseun Ogundokun, Oluwakemi Christiana Abikoye, Sanjay Misra, and Joseph Bamidele Awotunde
    Springer International Publishing

  • A Dynamic Round Triple Data Encryption Standard Cryptographic Technique for Data Security
    Oluwatobi Noah Akande, Oluwakemi Christiana Abikoye, Aderonke Anthonia Kayode, Oladele Taye Aro, and Oluwaseun Roseline Ogundokun
    Springer International Publishing

  • Optimizing android malware detection via ensemble learning
    Abikoye Oluwakemi Christianah, Benjamin Aruwa Gyunka, and Akande Noah Oluwatobi
    International Association of Online Engineering (IAOE)
    <p>Android operating system has become very popular, with the highest market share, amongst all other mobile operating systems due to its open source nature and users friendliness. This has brought about an uncontrolled rise in malicious applications targeting the Android platform. Emerging trends of Android malware are employing highly sophisticated detection and analysis avoidance techniques such that the traditional signature-based detection methods have become less potent in their ability to detect new and unknown malware. Alternative approaches, such as the Machine learning techniques have taken the lead for timely zero-day anomaly detections.  The study aimed at developing an optimized Android malware detection model using ensemble learning technique. Random Forest, Support Vector Machine, and k-Nearest Neighbours were used to develop three distinct base models and their predictive results were further combined using Majority Vote combination function to produce an ensemble model. Reverse engineering procedure was employed to extract static features from large repository of malware samples and benign applications. WEKA 3.8.2 data mining suite was used to perform all the learning experiments. The results showed that Random Forest had a true positive rate of 97.9%, a false positive rate of 1.9% and was able to correctly classify instances with 98%, making it a strong base model. The ensemble model had a true positive rate of 98.1%, false positive rate of 1.8% and was able to correctly classify instances with 98.16%. The finding shows that, although the base learners had good detection results, the ensemble learner produced a better optimized detection model compared with the performances of those of the base learners.</p>

  • COMPARATIVE STUDY of TWO DIVIDE and CONQUER SORTING ALGORITHMS: QUICKSORT and MERGESORT
    Oladipupo Esau Taiwo, Abikoye Oluwakemi Christianah, Akande Noah Oluwatobi, Kayode Anthonia Aderonke, and Adeniyi Jide kehinde
    Elsevier BV

  • Implementation of a Framework for Healthy and Diabetic Retinopathy Retinal Image Recognition
    Oluwatobi Noah Akande, Oluwakemi Christiana Abikoye, Aderonke Anthonia Kayode, and Yema Lamari
    Hindawi Limited
    The feature extraction stage remains a major component of every biometric recognition system. In most instances, the eventual accuracy of a recognition system is dependent on the features extracted from the biometric trait and the feature extraction technique adopted. The widely adopted technique employs features extracted from healthy retinal images in training retina recognition system. However, literature has shown that certain eye diseases such as diabetic retinopathy (DR), hypertensive retinopathy, glaucoma, and cataract could alter the recognition accuracy of the retina recognition system. This connotes that a robust retina recognition system should be designed to accommodate healthy and diseased retinal images. A framework with two different approaches for retina image recognition is presented in this study. The first approach employed structural features for healthy retinal image recognition while the second employed vascular and lesion-based features for DR retinal image recognition. Any input retinal image was first examined for the presence of DR symptoms before the appropriate feature extraction technique was adopted. Recognition rates of 100% and 97.23% were achieved for the healthy and DR retinal images, respectively, and a false acceptance rate of 0.0444 and a false rejection rate of 0.0133 were also achieved.

RECENT SCHOLAR PUBLICATIONS

  • 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

  • A lightweight image cryptosystem for cloud-assisted internet of things
    ET Oladipupo, OC Abikoye, JB Awotunde
    Applied Sciences 14 (7), 2808 2024

  • 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, e480 2024

  • Efficient Ensemble-based Phishing Website Classification Models using Feature Importance Attribute Selection and Hyper parameter Tuning Approaches
    RG Jimoh, AM OYELAKIN, OC Abikoye, MB Akanbi, AO Akanni, MA Jibrin, ...
    Journal of Information Technology and Computing 4 (2), 1-10 2023

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • Improved authenticated elliptic curve cryptography scheme for resource starve applications
    ET Oladipupo, OC Abikoye
    Computer Science and Information Technologies 3 (3), 169-185 2022

  • 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

  • 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

  • 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

  • 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

  • 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

MOST CITED SCHOLAR PUBLICATIONS

  • Modified advanced encryption standard algorithm for information security
    OC Abikoye, AD Haruna, A Abubakar, NO Akande, EO Asani
    Symmetry 11 (12), 1484 2019
    Citations: 77

  • 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
    Citations: 72

  • 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
    Citations: 70

  • 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
    Citations: 62

  • 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
    Citations: 61

  • 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
    Citations: 47

  • Offline signature recognition & verification using neural network
    OC Abikoye, MA Mabayoje, R Ajibade
    International Journal of Computer Applications 35 (2), 44-51 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
    Citations: 40

  • 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
    Citations: 34

  • 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
    Citations: 30

  • 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
    Citations: 29

  • 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
    Citations: 27

  • 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
    Citations: 27

  • 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
    Citations: 26

  • 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
    Citations: 23

  • A secured one time password authentication technique using (3, 3) visual cryptography scheme
    AO Christiana, AN Oluwatobi, GA Victory, OR Oluwaseun
    journal of physics: conference series 1299 (1), 012059 2019
    Citations: 23

  • 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
    Citations: 22

  • Android malware detection through machine learning techniques: A review
    A Christiana, B Gyunka, A Noah
    International Association of Online Engineering 2020
    Citations: 21

  • Text Classification Using Data Mining Techniques: A
    OC Abikoye, SO Omokanye, TO Aro
    Computing and Information Systems Journal 1 2018
    Citations: 18

  • 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
    Citations: 16