All Outputs (10)

A Hybrid Deep Learning Scheme for Intrusion Detection in the Internet of Things (2023)
Presentation / Conference Contribution
Momand, A., Jan, S. U., & Ramzan, N. (2023, May). A Hybrid Deep Learning Scheme for Intrusion Detection in the Internet of Things. Presented at ISPR'2023: The International Conference on Intelligent Systems and Pattern Recognition, Hammamet, Tunisia

The Internet of Things (IoT) is the connection of smart devices and objects to the internet, allowing them to share and analyze data, communicate with each other, and be controlled remotely. Several IoT devices are designed to collect, process, and s... Read More about A Hybrid Deep Learning Scheme for Intrusion Detection in the Internet of Things.

A Comparison of Ensemble Learning for Intrusion Detection in Telemetry Data (2023)
Presentation / Conference Contribution
Naz, N., Khan, M. A., Khan, M. A., Khan, M. A., Jan, S. U., Shah, S. A., Arshad, Abbasi, Q. H., & Ahmad, J. (2022, October). A Comparison of Ensemble Learning for Intrusion Detection in Telemetry Data. Presented at 3rd International Conference of Advanced Computing and Informatics, Casablanca, Morocco

The Internet of Things (IoT) is a grid of interconnected pre-programmed electronic devices to provide intelligent services for daily life tasks. However, the security of such networks is a considerable obstacle to successful implementation. Therefore... Read More about A Comparison of Ensemble Learning for Intrusion Detection in Telemetry Data.

Automated Grading of Diabetic Macular Edema Using Color Retinal Photographs (2022)
Presentation / Conference Contribution
Zubair, M., Ahmad, J., Alqahtani, F., Khan, F., Shah, S. A., Abbasi, Q. H., & Jan, S. U. (2022, May). Automated Grading of Diabetic Macular Edema Using Color Retinal Photographs. Presented at 2022 2nd International Conference of Smart Systems and Emerging Technologies (SMARTTECH), Riyadh, Saudi Arabia

Diabetic Macular Edema (DME) is an advanced indication of diabetic retinopathy (DR). It starts with blurring in vision and can lead to partial or even complete irreversible visual compromise. The only cure is timely diagnosis, prevention and treatmen... Read More about Automated Grading of Diabetic Macular Edema Using Color Retinal Photographs.

Transfer learning-based method for detection of COVID-19 using X-Ray Images (2021)
Presentation / Conference Contribution
Rehman, A., Tariq, Z., Jan, S. U., Aziz, S., Khan, M. U., & Chaudry, H. N. (2021, October). Transfer learning-based method for detection of COVID-19 using X-Ray Images. Presented at 2021 International Conference on Robotics and Automation in Industry (ICRAI), Rawalpindi, Pakistan

In this paper, we have performed transfer learning using different pre-trained convolutional neural networks for binary classification of X-ray images into COVID-19 disease and normal. The dataset is gathered from two open sources. Our dataset is con... Read More about Transfer learning-based method for detection of COVID-19 using X-Ray Images.

Machine Learning-based Real-Time Sensor Drift Fault Detection using Raspberry Pi (2020)
Presentation / Conference Contribution
Saeed, U., Ullah Jan, S., Lee, Y., & Koo, I. (2020, January). Machine Learning-based Real-Time Sensor Drift Fault Detection using Raspberry Pi. Presented at 2020 International Conference on Electronics, Information, and Communication (ICEIC), Barcelona, Spain

From smart industries to smart cities, sensors in the modern world plays an important role by covering a large number of applications. However, sensors get faulty sometimes leading to serious outcomes in terms of safety, economic cost and reliability... Read More about Machine Learning-based Real-Time Sensor Drift Fault Detection using Raspberry Pi.

Machine Learning for Detecting Drift Fault of Sensors in Cyber-Physical Systems (2020)
Presentation / Conference Contribution
Jan, S. U., Saeed, U., & Koo, I. (2020, January). Machine Learning for Detecting Drift Fault of Sensors in Cyber-Physical Systems. Presented at 2020 17th International Bhurban Conference on Applied Sciences and Technology (IBCAST), Islamabad, Pakistan

Cyber-Physical System (CPS) emerges as a potential direction to improve the applications relating to object-to-object, human-to-human and human-to-object communications in both the real world and virtual world. The examples of CPSs include Smart Gird... Read More about Machine Learning for Detecting Drift Fault of Sensors in Cyber-Physical Systems.

On Lightweight Method for Intrusions Detection in the Internet of Things (2019)
Presentation / Conference Contribution
Shakhov, V., Jan, S. U., Ahmed, S., & Koo, I. (2019, June). On Lightweight Method for Intrusions Detection in the Internet of Things. Presented at 2019 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), Sochi, Russia

Integration of the internet into the entities of the different domains of human society is emerging as a new paradigm called the Internet of Things. At the same time, the ubiquitous and wide-range systems make them prone to attacks. Security experts... Read More about On Lightweight Method for Intrusions Detection in the Internet of Things.

Performance Analysis of Support Vector Machine-Based Classifier for Spectrum Sensing in Cognitive Radio Networks (2018)
Presentation / Conference Contribution
Jan, S. U., Vu, V. H., & Koo, I. S. (2018, October). Performance Analysis of Support Vector Machine-Based Classifier for Spectrum Sensing in Cognitive Radio Networks. Presented at 2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), Zhengzhou, China

In this work, the performance of support vector machine (SVM)-based classifier, applied for spectrum sensing in cognitive radio (CR) networks, is analyzed. A single observation given input to classifier is composed of three statistical features extra... Read More about Performance Analysis of Support Vector Machine-Based Classifier for Spectrum Sensing in Cognitive Radio Networks.

Sensor faults detection and classification using SVM with diverse features (2017)
Presentation / Conference Contribution
Jan, S. U., & Koo, I. S. (2017). Sensor faults detection and classification using SVM with diverse features. In 2017 International Conference on Information and Communication Technology Convergence (ICTC). https://doi.org/10.1109/ictc.2017.8191044

Sensors in industrial systems fault frequently leading to serious consequences regarding cost and safety. The authors propose support vector machine-based classifier with diverse time- and frequency-domain feature models to detect and classify these... Read More about Sensor faults detection and classification using SVM with diverse features.

Comparative analysis of DIPPM scheme for Visible Light Communications (2015)
Presentation / Conference Contribution
Jan, S. U., Lee, Y., & Koo, I. (2015). Comparative analysis of DIPPM scheme for Visible Light Communications. In 2015 International Conference on Emerging Technologies (ICET). https://doi.org/10.1109/icet.2015.7389192

Visible Light Communications (VLC) uses solid-state light sources for data transmission in addition to its primary function of illumination. The dual functionality of light source provokes some challenges for VLC including dimming control and perceiv... Read More about Comparative analysis of DIPPM scheme for Visible Light Communications.