Dr Harsha Kalutarage's Outputs (6)

Improving federated learning performance with similarity guided feature extraction and pruning. (2024)
Thesis
PALIHAWADANA, C. 2024. Improving federated learning performance with similarity guided feature extraction and pruning. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-2801100

Federated Learning (FL) is a Machine Learning (ML) paradigm that learns from distributed clients to collaboratively train a global model in a privacy-preserved manner without sharing their private data. Traditional centralised ML approaches require a... Read More about Improving federated learning performance with similarity guided feature extraction and pruning..

Enhancing Android application security through source code vulnerability mitigation using artificial intelligence: a privacy-preserved, community-driven, federated-learning-based approach. (2024)
Thesis
SENANAYAKE, J.M.D. 2024. Enhancing Android application security through source code vulnerability mitigation using artificial intelligence: a privacy-preserved, community-driven, federated-learning-based approach. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-2801183

As technology advances, Android devices and apps are rapidly increasing. It is crucial to adhere to security protocols during app development, especially as many apps lack sufficient safeguards. Despite the use of automated tools for risk mitigation,... Read More about Enhancing Android application security through source code vulnerability mitigation using artificial intelligence: a privacy-preserved, community-driven, federated-learning-based approach..

Protecting vehicles from cyberattacks: context aware AI-based intrusion detection for vehicle CAN bus security. (2024)
Thesis
RAJAPAKSHA, S. 2024. Protecting vehicles from cyberattacks: context aware AI-based intrusion detection for vehicle CAN bus security. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-2801124

Modern automobiles are equipped with a large number of electronic control units (ECUs), which are interconnected through the controller area network (CAN) bus for real-time data exchange. However, the CAN bus lacks security measures, rendering it sus... Read More about Protecting vehicles from cyberattacks: context aware AI-based intrusion detection for vehicle CAN bus security..

Lightweight intrusion detection of attacks on the Internet of Things (IoT) in critical infrastructures. (2024)
Thesis
OTOKWALA, U.J. 2024. Lightweight intrusion detection of attacks on the Internet of Things (IoT) in critical infrastructures. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-2571244

Critical Infrastructures (CI) are essential for various aspects of human activities, spanning across different sectors. However, the integration of Internet of Things (IoT) devices into CI has introduced a new dimension to security challenges due to... Read More about Lightweight intrusion detection of attacks on the Internet of Things (IoT) in critical infrastructures..

A reliable trust-aware reinforcement learning based routing protocol for wireless medical sensor networks. (2022)
Thesis
HAJAR, M.S. 2022. A reliable trust-aware reinforcement learning based routing protocol for wireless medical sensor networks. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1987863

Interest in the Wireless Medical Sensor Network (WMSN) is rapidly gaining attention thanks to recent advances in semiconductors and wireless communication. However, by virtue of the sensitive medical applications and the stringent resource constraint... Read More about A reliable trust-aware reinforcement learning based routing protocol for wireless medical sensor networks..

Towards a robust, effective and resource efficient machine learning technique for IoT security monitoring. [Thesis] (2022)
Thesis
ZAKARIYYA, I. 2022. Towards a robust, effective and resource efficient machine learning technique for IoT security monitoring. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-1987917

Internet of Things (IoT) devices are becoming increasingly popular and an integral part of our everyday lives, making them a lucrative target for attackers. These devices require suitable security mechanisms that enable robust and effective detection... Read More about Towards a robust, effective and resource efficient machine learning technique for IoT security monitoring. [Thesis].