Kayode Sakariyah Adewole

Scopus Publications

Research Communities in Smart Homes Security: A Systematic Mapping Study
Fazeleh Dehghani Ashkezari, Andreas Jacobsson, Kayode S. Adewole, Klara Svalin, Martin Höst
Iot, 2026
Smart homes are becoming increasingly common, bringing convenience to users but also raising serious security concerns. As the number of connected devices grows, so does the research interest in securing smart homes. However, the literature is broad, making it difficult to understand the main research directions and how they are connected. Given the scope and diversity of existing research, a systematic mapping study was chosen to provide a high-level overview of smart home security research by mapping research communities, identifying dominant themes, and examining their evolution over time. We retrieved articles from the Scopus database published between 2000 and April 2025, resulting in approximately 13,600 articles. After filtering out unrelated domains such as smart vehicles, smart industry, and general IoT, a final set of 6313 publications specifically focused on smart home security was used for analysis. We applied a citation-based network analysis approach, constructed an author citation graph, and used the Louvain community detection algorithm to identify 12 main research communities. Each community was further analyzed based on its keywords, most-cited publications, leading authors, and institutions. Our results provide a structured overview of the field, highlighting its key themes and evolution over time. This work can help researchers better navigate the smart home security landscape and identify future research opportunities.
Combating Intimate Partner Violence Through Emotion Detection in Smart Connected Homes
Kayode S. Adewole, Fazeleh Dehghani Ashkezari, Andreas Jacobsson
Lecture Notes in Networks and Systems, 2026
Enhancing IoT Security with Generative AI: Threat Detection and Countermeasure Design
Alex Oacheșu, Kayode S. Adewole, Andreas Jacobsson, Paul Davidsson
Electronics Switzerland, 2026
The rapid proliferation of Internet of Things (IoT) devices has increased the attack surface for cyber threats. Traditional intrusion detection systems often struggle to keep pace with novel or evolving threats. This study proposes an end-to-end generative AI-based intrusion detection and response pipeline designed for automated threat mitigation in smart home IoT environments. It leverages a Variational Autoencoder (VAE) trained on benign traffic to flag anomalies, a fine-tuned Bidirectional Encoder Representations from Transformers (BERT) model to classify anomalies into five attack categories (C&C, DDoS, Okiru, PortScan, and benign), and Grok3—a large language model—to generate tailored countermeasure recommendations. Using the Aposemat IoT-23 dataset, the VAE model achieves a recall of 0.999 and a precision of 0.961 for anomaly detection. The BERT model achieves an overall accuracy of 99.90% with per-class F1 scores exceeding 0.99. End-to-end prototype simulation involving 10,000 network traffic samples demonstrate a 98% accuracy in identifying cyber attacks and generating countermeasures to mitigate them. The pipeline integrates generative models for improved detection and automated security policy formulation in IoT settings, enhancing detection and enabling quicker and actionable security responses to mitigate cyber threats targeting smart home environments.
Evaluation of the Effects of Antenna Height and Bandwidth on Path Loss Exponent at Millimeter-Wave Frequencies 24, 38, and 66 GHz
Yusuf Olayinka Imam-Fulani, Aliyu D. Usman, Abdoulie M. S. Tekanyi, Abdulmalik S. Yaro, Abubakar Abdulkarim, Nasir Faruk, Emmanuel Alozie, Salisu Garba, Kayode S. Adewole, Abdulkarim A. Oloyede, Agbotiname Lucky Imoize
Lecture Notes in Networks and Systems, 2026
A Comparative Study of Path Loss Models for 5G Networks Across 28, 36, and 48 GHz in Urban Environments
Yusuf Olayinka Imam-Fulani, Aliyu D. Usman, Abdoulie M. S. Tekanyi, Abdulmalik S. Yaro, Abubakar Abdulkarim, Nasir Faruk, Emmanuel Alozie, Salisu Garba, Kayode S. Adewole, Abdulkarim A. Oloyede, Agbotiname Lucky Imoize, Bashir Abdullahi Baba
Lecture Notes in Networks and Systems, 2026
Intrusion Detection Framework for Internet of Things with Rule Induction for Model Explanation
Kayode S. Adewole, Andreas Jacobsson, Paul Davidsson
Sensors, 2025
As the proliferation of Internet of Things (IoT) devices grows, challenges in security, privacy, and interoperability become increasingly significant. IoT devices often have resource constraints, such as limited computational power, energy efficiency, bandwidth, and storage, making it difficult to implement advanced security measures. Additionally, the diversity of IoT devices creates vulnerabilities and threats that attackers can exploit, including spoofing, routing, man-in-the-middle, and denial-of-service. To address these evolving threats, Intrusion Detection Systems (IDSs) have become a vital solution. IDS actively monitors network traffic, analyzing incoming and outgoing data to detect potential security breaches, ensuring IoT systems remain safeguarded against malicious activity. This study introduces an IDS framework that integrates ensemble learning with rule induction for enhanced model explainability. We study the performance of five ensemble algorithms (Random Forest, AdaBoost, XGBoost, LightGBM, and CatBoost) for developing effective IDS for IoT. The results show that XGBoost outperformed the other ensemble algorithms on two publicly available datasets for intrusion detection. XGBoost achieved 99.91% accuracy and 99.88% AUC-ROC on the CIC-IDS2017 dataset, as well as 98.54% accuracy and 93.06% AUC-ROC on the CICIoT2023 dataset, respectively. We integrate model explainability to provide transparent IDS system using a rule induction method. The experimental results confirm the efficacy of the proposed approach for providing a lightweight, transparent, and trustworthy IDS system that supports security analysts, end-users, and different stakeholders when making decisions regarding intrusion and non-intrusion events.
Privacy Preserving A-Priori and ECLAT with Local Differential Privacy
Christine Wong, Abdulrauf Gidado, Kayode S. Adewole
Proceedings 29th IEEE Acis International Conference on Software Engineering Artificial Intelligence Networking and Parallel Distributed Computing Snpd 2025 Summer, 2025
Privacy-preserving frequent itemset mining is crucial for extracting valuable patterns from high-dimensional user data while safeguarding sensitive information. This research investigates the performance of A-Priori and Equivalence Class Clustering and Bottom-Up Lattice Traversal (ECLAT) algorithms, such that Local Differential Privacy (LDP), a privacy preservation technique that obscures the true transactions generated from user activities, can be implemented to protect user privacy. We implement these algorithms for frequent itemset mining in two scenarios - one with LDP and the second without the use of LDP. The proposed approach shows promising results when compared with itemset mining from noisy data without any counter mechanisms. The performance trade-off between execution time and accuracy of the algorithm is also examined. The challenges and limitations of implementing the proposed approach for privacy-preserving frequent itemset mining are discussed, and future directions are highlighted.
Self-supervised Behavioral Anomaly Detection for Internet of Things Environments
Kayode S. Adewole, Andreas Jacobsson, Paul Davidsson
Proceedings 2025 IEEE Annual Congress on Artificial Intelligence of Things Aiot 2025, 2025
RAM-IoT: Risk Assessment Model for IoT-Based Critical Assets
Kayode Adewole, Andreas Jacobsson, Paul Davidsson
International Conference on Internet of Things Big Data and Security Iotbds Proceedings, 2025
: As the number of Internet of Things (IoT) devices continues to grow, understanding and mitigating potential vulnerabilities and threats is crucial. With IoT devices becoming ubiquitous in critical sectors like healthcare, transportation, energy, and industrial automation, identifying and addressing risks is increasingly important. A comprehensive risk management approach enables IoT stakeholders to safeguard user data and privacy, as well as system integrity. Existing risk assessment frameworks focus on qualitative risk analysis methodologies, such as operationally critical threat, asset, and vulnerability evaluation (OCTAVE). However, security risk assessment, particularly for IoT ecosystem, demands both qualitative and quantitative risk assessment. This paper proposes RAM-IoT, a risk assessment model for IoT-based critical assets that integrates qualitative and quantitative risk assessment approaches. A multi-criteria decision making (MCDM) approach based on fuzzy Analytic Hierarchy Process (fuzzy AHP) is proposed to address the subjective assessment of the IoT risk analysts and their corresponding stakeholders. The applicability of the proposed model is illustrated through a use case connected to service delivery in the IoT. The proposed model provides a guideline to researchers and practitioners on how to quantify the risks targeting assets in IoT, thereby providing adequate support for protecting IoT ecosystems.
A Framework for ML-Based Intrusion Detection and Prevention: A Containerized, Cloud-Native Approach
Nikolas Naydenov, Stela Ruseva, Naomy Jerono Chemungor, Kayode Sakariyah Adewole
Ismsit 2025 9th International Symposium on Multidisciplinary Studies and Innovative Technologies Proceedings, 2025
The operational deployment of machine learning (ML) based security systems in production cloud environments remains a significant challenge, often hindered by a disconnect between offline training and real-time inference known as train-serve skew. This paper presents a novel, dual-workflow, cloud-native architecture for an Intrusion Detection and Prevention System (IDPS) that bridges this gap. Our architecture builds upon a flexible ML framework from foundational research, which was validated in an offline-only proof-of-concept. The primary contributions of this paper are twofold: first, we provide a complete blueprint for orchestrating the framework as a containerized, microservice-based cluster using platforms like Kubernetes. Second, we introduce a minimal-overhead online workflow that uses high-performance, kernel-level probes and a real-time agent to replicate the feature-rich vectors required for accurate detection, thus solving the train-serve skew problem. This dual-workflow design separates low-latency real-time detection from deep offline analysis, which leverages the foundational two-stage ML pipeline and context-aware capture tools. This work provides a validated blueprint for an effective IDPS that achieves the scalability, resilience, and maintainability required for a modern cloud security service.
Unsupervised Transformer-Based Anomaly Detection for IoT Networks
Piotr Kołpa, Kayode S. Adewole, Jan A. Persson, Fredrik Karlsson
Proceedings 2025 12th International Conference on Future Internet of Things and Cloud Ficloud 2025, 2025
Secure SDN-IOT Framework with Adaptive Gbell PRF-MAC and Convolutional GRU for IDS
Sri Harsha Grandhi, Dinesh Kumar Reddy Basani, Raj Kumar Gudivaka, Basava Ramanjaneyulu Gudivaka, Rajya Lakshmi Gudivaka, Kayode Sakariyah Adewole
IETE Journal of Research, 2025
Advances in the Design of Renewable Energy Power Supply for Rural Health Clinics, Case Studies, and Future Directions
Abubakar Abdulkarim, Nasir Faruk, Emmanuel Alozie, Hawau Olagunju, Ruqayyah Yusuf Aliyu, Agbotiname Lucky Imoize, Kayode S. Adewole, Yusuf Olayinka Imam-Fulani, Salisu Garba, Bashir Abdullahi Baba, Mustapha Hussaini, Abdulkarim A. Oloyede, Aminu Abdullahi, Rislan Abdulazeez Kanya, Dahiru Jafaru Usman
Clean Technologies, 2024
Energy disaggregation risk resilience through microaggregation and discrete Fourier transform
Kayode S. Adewole, Vicenç Torra
Information Sciences, 2024
HOMEFUS: A Privacy and Security-Aware Model for IoT Data Fusion in Smart Connected Homes
Kayode Adewole, Andreas Jacobsson
International Conference on Internet of Things Big Data and Security Iotbds Proceedings, 2024
LPM: A Lightweight Privacy-Aware Model for IoT Data Fusion in Smart Connected Homes
Kayode S. Adewole, Andreas Jacobsson
2024 9th International Conference on Smart and Sustainable Technologies Splitech 2024, 2024
ARAM: Assets-based Risk Assessment Model for Connected Smart Homes
Kayode S. Adewole, Andreas Jacobsson, Paul Davidsson
Proceedings 2024 11th International Conference on Future Internet of Things and Cloud Ficloud 2024, 2024
Segment Anything Model (SAM) Meets Object Detected Box Prompts
Erdal Akin, Héctor Caltenco, Kayode S. Adewole, Reza Malekian, Jan A. Persson
Proceedings of the IEEE International Conference on Industrial Technology, 2024
Privacy-aware Hydra (PA-Hydra) for 3D Scene Graph Construction
Erdal Akin, Kayode S. Adewole, Héctor Caltenco, Reza Malekian, Jan A. Persson
2024 IEEE 10th World Forum on Internet of Things Wf Iot 2024, 2024
Simulation and Modeling of NLOS P2P 5G and Future Wireless Communication Systems in FR2 within an Urban Environment
Nasir Faruk, Emmanuel Alozie, Abubakar Abdulkarim, Aliyu D. Usman, Yusuf Olayinka Imam-Fulani, Salisu Garba, Kayode S. Adewole, Agbotiname Lucky Imoize, Abdulkarim A. Oloyede, Bashir Abdullahi Baba, Hawau I. Olagunju
IEEE International Conference on Emerging and Sustainable Technologies for Power and ICT in A Developing Society Nigercon, 2024
A review of dust-induced electromagnetic waves scattering theories and models for 5G and beyond wireless communication systems
Emmanuel Alozie, Abdulwaheed Musa, Nasir Faruk, Agbotiname Lucky Imoize, Abubakar Abdulkarim, Aliyu D. Usman, Yusuf Olayinka Imam-Fulani, Kayode S. Adewole, Abdulkarim A. Oloyede, Olugbenga A. Sowande, Salisu Garba, Bashir Abdullahi Baba, Yinusa A. Adediran, Lawan S. Taura
Scientific African, 2023
A systematic review and Meta-data analysis on the applications of Deep Learning in Electrocardiogram
Nehemiah Musa, Abdulsalam Ya’u Gital, Nahla Aljojo, Haruna Chiroma, Kayode S. Adewole, Hammed A. Mojeed, Nasir Faruk, Abubakar Abdulkarim, Ifada Emmanuel, Yusuf Y. Folawiyo, James A. Ogunmodede, Abdukareem A. Oloyede, Lukman A. Olawoyin, Ismaeel A. Sikiru, Ibrahim Katb
Journal of Ambient Intelligence and Humanized Computing, 2023
Large scale survey for radio propagation in developing machine learning model for path losses in communication systems
Haruna Chiroma, Ponman Nickolas, Nasir Faruk, Emmanuel Alozie, Imam-Fulani Yusuf Olayinka, Kayode S. Adewole, Abubakar Abdulkarim, Abdulkarim A. Oloyede, Olugbenga A. Sowande, Salisu Garba, Aliyu D. Usman, Lawan S. Taura, Yinusa A. Adediran
Scientific African, 2023
5G Frequency Standardization, Technologies, Channel Models, and Network Deployment: Advances, Challenges, and Future Directions
Yusuf Olayinka Imam-Fulani, Nasir Faruk, Olugbenga A. Sowande, Abubakar Abdulkarim, Emmanuel Alozie, Aliyu D. Usman, Kayode S. Adewole, Abdulkarim A. Oloyede, Haruna Chiroma, Salisu Garba, Agbotiname Lucky Imoize, Bashir Abdullahi Baba, Abdulwaheed Musa, Yinusa A. Adediran, Lawan S. Taura
Sustainability Switzerland, 2023
Privacy Protection of Synthetic Smart Grid Data Simulated via Generative Adversarial Networks
Kayode Adewole, Vicenç Torra
Proceedings of the International Conference on Security and Cryptography, 2023
Terrestrial Radio Propagation Research Datasets Repository
Kayode S. Adewole, Hawau Olagunju, Nasir Faruk, Agbotiname Lucky Imoize, Emmanuel Alozie, Olugbenga A. Sowande, Abubakar Abdulkarim, Aliyu D. Usman, Yusuf Olayinka Imam-Fulani, Abdulkarim A. Oloyede, Salisu Garba, Bashir Abdullahi Baba, Abdulwaheed Musa, Yinusa A. Adediran, Lawan S. Taura
2023 2nd International Conference on Multidisciplinary Engineering and Applied Science Icmeas 2023, 2023
Signal Attenuation Modeling and Simulation for 5G and Beyond P2P Wireless Communication Networks in FR2 Bands: Comparison within M-Region in Nigeria
Emmanuel Alozie, Nasir Faruk, Abubakar Abdulkarim, Aliyu D. Usman, Yusuf Olayinka Imam-Fulani, Salisu Garba, Kayode S. Adewole, Abdulkarim A. Oloyede, Olugbenga A. Sowande, Bashir Abdullahi Baba, Abdulwaheed Musa, Agbotiname Lucky Imoize, Yinusa A. Adediran, Hawau I. Olagunju, Lawan S. Taura
2023 2nd International Conference on Multidisciplinary Engineering and Applied Science Icmeas 2023, 2023
Modeling and Simulation of Total Attenuation of P2P NLOS 5G and Beyond Wireless Communication Systems Operating in FR2 Bands in Nigeria
Emmanuel Alozie, Nasir Faruk, Abubakar Abdulkarim, Aliyu D. Usman, Yusuf Olayinka Imam-Fulani, Salisu Garba, Kayode S. Adewole, Abdulkarim A. Oloyede, Olugbenga A. Sowande, Bashir Abdullahi Baba, Abdulwaheed Musa, Agbotiname Lucky Imoize, Yinusa A. Adediran, Hawau I. Olagunju, Lawan S. Taura
2023 2nd International Conference on Multidisciplinary Engineering and Applied Science Icmeas 2023, 2023
Investigation of the Impact of Height and Bandwidth on Path Loss Exponent of 5G FR1 Wireless Networks at 800, 3500, and 5900 MHz
Yusuf Olayinka Imam-Fulani, Nasir Faruk, Aliyu D. Usman, Abubakar Abdulkarim, Abdoulie M.S Tekanyi, Abdulmalik S. Yaro, Emmanuel Alozie, Salisu Garba, Kayode S. Adewole, Abdulkarim A. Oloyede, Olugbenga A. Sowande, Bashir Abdullahi Baba, Abdulwaheed Musa, Agbotiname Lucky Imoize, Yinusa A. Adediran, Hawau I. Olagunju, Lawan S. Taura
2023 2nd International Conference on Multidisciplinary Engineering and Applied Science Icmeas 2023, 2023
DFTMicroagg: a dual-level anonymization algorithm for smart grid data
Kayode S. Adewole, Vicenç Torra
International Journal of Information Security, 2022
Expert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions
Kayode S. Adewole, Hammed A. Mojeed, James A. Ogunmodede, Lubna A. Gabralla, Nasir Faruk, Abubakar Abdulkarim, Emmanuel Ifada, Yusuf Y. Folawiyo, Abdukareem A. Oloyede, Lukman A. Olawoyin, Ismaeel A. Sikiru, Musa Nehemiah, Abdulsalam Ya’u Gital, Haruna Chiroma
Applied Sciences Switzerland, 2022
Feature selection and computational optimization in high-dimensional microarray cancer datasets via InfoGain-modified bat algorithm
Moshood A. Hambali, Tinuke O. Oladele, Kayode S. Adewole, Arun Kumar Sangaiah, Wei Gao
Multimedia Tools and Applications, 2022
Empirical Analysis of Data Streaming and Batch Learning Models for Network Intrusion Detection
Kayode S. Adewole, Taofeekat T. Salau-Ibrahim, Agbotiname Lucky Imoize, Idowu Dauda Oladipo, Muyideen AbdulRaheem, Joseph Bamidele Awotunde, Abdullateef O. Balogun, Rafiu Mope Isiaka, Taye Oladele Aro
Electronics Switzerland, 2022
ANN-based model for multiband path loss prediction in built-up environments
Nasir Faruk, Quadri Ramon Adebowale, Imam-Fulani Yusuf Olayinka, Kayode S. Adewole, Abubakar Abdulkarim, Abdulkarim A. Oloyede, Haruna Chiroma, Olugbenga A. Sowande, Lukman A. Olawoyin, Salisu Garba, Aliyu D. Usman, Yinusa A. Adediran, Lawan S. Taura
Scientific African, 2022
A Review on Rain Signal Attenuation Modeling, Analysis and Validation Techniques: Advances, Challenges and Future Direction
Emmanuel Alozie, Abubakar Abdulkarim, Ibrahim Abdullahi, Aliyu D. Usman, Nasir Faruk, Imam-Fulani Yusuf Olayinka, Kayode S. Adewole, Abdulkarim A. Oloyede, Haruna Chiroma, Olugbenga A. Sowande, Lukman A. Olawoyin, Salisu Garba, Agbotiname Lucky Imoize, Abdulwaheed Musa, Yinusa A. Adediran, Lawan S. Taura
Sustainability Switzerland, 2022
Privacy Issues in Smart Grid Data: From Energy Disaggregation to Disclosure Risk
Kayode Sakariyah Adewole, Vicenç Torra
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2022
Performance Analysis of Machine Learning Methods with Class Imbalance Problem in Android Malware Detection
Abimbola Ganiyat Akintola, Abdullateef Balogun, Hammed Adeleke Mojeed, Fatima Usman-Hamza, Shakirat Aderonke Salihu, Kayode Sakariyau Adewole, Ghaniyyat Bolanale Balogun, Peter Ogirima Sadiku
International Journal of Interactive Mobile Technologies, 2022
An Empirical Study on Data Sampling Methods in Addressing Class Imbalance Problem in Software Defect Prediction
Babajide J. Odejide, Amos O. Bajeh, Abdullateef O. Balogun, Zubair O. Alanamu, Kayode S. Adewole, Abimbola G. Akintola, Shakirat A. Salihu, Fatima E. Usman-Hamza, Hammed A. Mojeed
Lecture Notes in Networks and Systems, 2022
Effect of Training Algorithms and Network Architecture on the Performance of Multi-Band ANN-Based Path Loss Prediction Model
Quadri Ramon Adebowale, Nasir Faruk, Kayode S. Adewole, Abubakar Abdulkarim, Abdulkarim A. Oloyede, Haruna Chiroma, Olugbenga. A. Sowande, Aliyu D. Usman, Imam-Fulani Yusuf Olayinka, Abduljalal Yusharu Kassim, Lawan S. Taura
Proceedings of the 2022 IEEE Nigeria 4th International Conference on Disruptive Technologies for Sustainable Development Nigercon 2022, 2022
Application of Machine Learning Algorithms to Path Loss Modeling: A Review
Abubakar Abdulkarim, Nasir Faruk, Emmanuel Alozie, Olugbenga. A. Sowande, Imam-Fulani Yusuf Olayinka, Aliyu D. Usman, Kayode S. Adewole, Abdulkarim A. Oloyede, Haruna Chiroma, Salisu Garba, Agbotiname Lucky Imoize, Abdulwaheed Musa, Lawan S. Taura
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
Improving the phishing website detection using empirical analysis of Function Tree and its variants
Abdullateef O. Balogun, Kayode S. Adewole, Muiz O. Raheem, Oluwatobi N. Akande, Fatima E. Usman-Hamza, Modinat A. Mabayoje, Abimbola G. Akintola, Ayisat W. Asaju-Gbolagade, Muhammed K. Jimoh, Rasheed G. Jimoh, Victor E. Adeyemo
Heliyon, 2021
Improved cloud-based n-primes model for symmetric-based fully homomorphic encryption using residue number system
K. J. Muhammed, R. M. Isiaka, A. W. Asaju-Gbolagade, K. S. Adewole, K. A. Gbolagade
Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics Theories and Applications, 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 comprehensive survey on low-cost ECG acquisition systems: Advances on design specifications, challenges and future direction
Nasir Faruk, Abubakar Abdulkarim, Ifada Emmanuel, Yusuf Y. Folawiyo, Kayode S. Adewole, Hammed A. Mojeed, Abdukareem A. Oloyede, Lukman A. Olawoyin, Ismaeel A. Sikiru, Musa Nehemiah, Abdulsalam Ya'u Gital, Haruna Chiroma, James A. Ogunmodede, Mubarak Almutairi, Ibraheem A. Katibi
Biocybernetics and Biomedical Engineering, 2021
Cascade Generalization Based Functional Tree for Website Phishing Detection
Abdullateef O. Balogun, Kayode S. Adewole, Amos O. Bajeh, Rasheed G. Jimoh
Communications in Computer and Information Science, 2021
Investigative Study of Unigram and Bigram Features for Short Message Spam Detection
Rasheed G. Jimoh, Kayode S. Adewole, Tunbosun E. Aderemi, Abdullateef O. Balogun
Lecture Notes in Networks and Systems, 2021
Ensemble-Based Logistic Model Trees for Website Phishing Detection
Victor E. Adeyemo, Abdullateef O. Balogun, Hammed A. Mojeed, Noah O. Akande, Kayode S. Adewole
Communications in Computer and Information Science, 2021
Hybrid Algorithm for Symmetric Based Fully Homomorphic Encryption
Kamaldeen Jimoh Muhammed, Rafiu Mope Isiaka, Ayisat Wuraola Asaju-Gbolagade, Kayode Sakariyah Adewole, Kazeem Alagbe Gbolagade
Communications in Computer and Information Science, 2021
Optimized Decision Forest for Website Phishing Detection
Abdullateef O. Balogun, Hammed A. Mojeed, Kayode S. Adewole, Abimbola G. Akintola, Shakirat A. Salihu, Amos O. Bajeh, Rasheed G. Jimoh
Lecture Notes in Networks and Systems, 2021
Deep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions
Haruna Chiroma, Shafi’i M. Abdulhamid, Ibrahim A. T. Hashem, Kayode S. Adewole, Absalom E. Ezugwu, Saidu Abubakar, Liyana Shuib
Mathematical Problems in Engineering, 2021
Data Sampling-Based Feature Selection Framework for Software Defect Prediction
Abdullateef O. Balogun, Fatimah B. Lafenwa-Balogun, Hammed A. Mojeed, Fatimah E. Usman-Hamza, Amos O. Bajeh, Victor E. Adeyemo, Kayode S. Adewole, Rasheed G. Jimoh
Lecture Notes in Networks and Systems, 2021
Application of Computational Intelligence Algorithms in Radio Propagation: A Systematic Review and Metadata Analysis
Quadri Ramon Adebowale, Nasir Faruk, Kayode S. Adewole, Abubakar Abdulkarim, Lukman A. Olawoyin, Abdulkarim A. Oloyede, Haruna Chiroma, Aliyu D. Usman, Carlos T. Calafate
Mobile Information Systems, 2021
Hybrid feature selection framework for sentiment analysis on large corpora
Kayode Adewole, Abdullateef Balogun, Muiz Raheem, Muhammed Jimoh, Rasheed Jimoh, Modinat Mabayoje, Fatima Hamza, Abimbola Akintola, Ayisat Gbolagade
Jordanian Journal of Computers and Information Technology, 2021
Deep Learning Solutions for Protein: Recent Development and Future Directions
Haruna Chiroma, Ali Muhammad Usman, Fatsuma Jauro, Lubna A. Gabralla, Kayode S. Adewole, Emmanuel Gbenga Dada, Fatima Shittu, Aishatu Yahaya Umar, Julius O. Okesola, Awodele Oludele
Lecture Notes in Networks and Systems, 2021
Twitter spam account detection based on clustering and classification methods
Kayode Sakariyah Adewole, Tao Han, Wanqing Wu, Houbing Song, Arun Kumar Sangaiah
Journal of Supercomputing, 2020
Microarray cancer feature selection: Review, challenges and research directions
Moshood A. Hambali, Tinuke O. Oladele, Kayode S. Adewole
International Journal of Cognitive Computing in Engineering, 2020
Cloud-based IoMT framework for cardiovascular disease prediction and diagnosis in personalized E-health care
Kayode S. Adewole, Abimbola G. Akintola, Rasheed Gbenga Jimoh, Modinat A. Mabayoje, Muhammed K. Jimoh, Fatima E. Usman-Hamza, Abdullateef O. Balogun, Arun Kumar Sangaiah, Ahmed O. Ameen
Intelligent Iot Systems in Personalized Health Care, 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
Temporal Variation of Duty Cycle in the GSM Bands
Ganiyu A. Ishola, Balogun V. Segun, Nasir Faruk, Kayode S. Adewole, Abdulkarim A. Oloyede, Lukman A. Olawoyin, Rasheed. G. Jimoh
2019 2nd International Conference of the IEEE Nigeria Computer Chapter Nigeriacomputconf 2019, 2019
SMSAD: a framework for spam message and spam account detection
Kayode Sakariyah Adewole, Nor Badrul Anuar, Amirrudin Kamsin, Arun Kumar Sangaiah
Multimedia Tools and Applications, 2019
Hybrid Rule-Based Model for Phishing URLs Detection
Kayode S. Adewole, Abimbola G. Akintola, Shakirat A. Salihu, Nasir Faruk, Rasheed G. Jimoh
Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst, 2019
Multi-objective scheduling of MapReduce jobs in big data processing
Ibrahim Abaker Targio Hashem, Nor Badrul Anuar, Mohsen Marjani, Abdullah Gani, Arun Kumar Sangaiah, Adewole Kayode Sakariyah
Multimedia Tools and Applications, 2018
Malicious accounts: Dark of the social networks
Kayode Sakariyah Adewole, Nor Badrul Anuar, Amirrudin Kamsin, Kasturi Dewi Varathan, Syed Abdul Razak
Journal of Network and Computer Applications, 2017
The role of big data in smart city
Ibrahim Abaker Targio Hashem, Victor Chang, Nor Badrul Anuar, Kayode Adewole, Ibrar Yaqoob, Abdullah Gani, Ejaz Ahmed, Haruna Chiroma
International Journal of Information Management, 2016

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