7 papers
A Resource Estimation Model for the Hardware-Software Co-Design of Distributed Quantum Architectures
Raymond P. H. Wu, Chathurika Ranaweera, Sutharshan Rajasegarar +3
In distributed quantum computing (DQC), executing monolithic quantum circuits across multiple interconnected quantum processing units (QPUs) requires dedicated communication qubits…
Modeling Quantum Federated Autoencoder for Anomaly Detection in IoT Networks
Devashish Chaudhary, Sutharshan Rajasegarar, Shiva Raj Pokhrel
We propose a Quantum Federated Autoencoder for Anomaly Detection, a framework that leverages quantum federated learning for efficient, secure, and distributed processing in IoT net…
Q-AGNN: Quantum-Enhanced Attentive Graph Neural Network for Intrusion Detection
Devashish Chaudhary, Sutharshan Rajasegarar, Shiva Raj Pokhrel
With the rapid growth of interconnected devices, accurately detecting malicious activities in network traffic has become increasingly challenging. Most existing deep learning-based…
In-network Attack Detection with Federated Deep Learning in IoT Networks: Real Implementation and Analysis
Devashish Chaudhary, Sutharshan Rajasegarar, Shiva Raj Pokhrel +2
The rapid expansion of the Internet of Things (IoT) and its integration with backbone networks have heightened the risk of security breaches. Traditional centralized approaches to…
Efficient Time-Aware Partitioning of Quantum Circuits for Distributed Quantum Computing
Raymond P. H. Wu, Chathu Ranaweera, Sutharshan Rajasegarar +3
To overcome the physical limitations of scaling monolithic quantum computers, distributed quantum computing (DQC) interconnects multiple smaller-scale quantum processing units (QPU…
Modeling Wavelet Transformed Quantum Support Vector for Network Intrusion Detection
Swati Kumari, Shiva Raj Pokhrel, Swathi Chandrasekhar +5
Network traffic anomaly detection is a critical cybersecurity challenge requiring robust solutions for complex Internet of Things (IoT) environments. We present a novel hybrid quan…