39 citations · 58 across the 21 of their papers we have counts for
7 papers · 1 filter
From Description to Detection: LLM based Extendable O-RAN Compliant Blind DoS Detection in 5G and Beyond
Thusitha Dayaratne, Ngoc Duy Pham, Viet Vo +5
The quality and experience of mobile communication have significantly improved with the introduction of 5G, and these improvements are expected to continue beyond the 5G era. Howev…
Robust Anomaly Detection in O-RAN: Leveraging LLMs against Data Manipulation Attacks
Thusitha Dayaratne, Ngoc Duy Pham, Viet Vo +5
The introduction of 5G and the Open Radio Access Network (O-RAN) architecture has enabled more flexible and intelligent network deployments. However, the increased complexity and o…
Active Attack Resilience in 5G: A New Take on Authentication and Key Agreement
Nazatul H. Sultan, Xinlong Guan, Josef Pieprzyk +3
As 5G networks expand into critical infrastructure, secure and efficient user authentication is more important than ever. The 5G-AKA protocol, standardized by 3GPP in TS 33.501, is…
Self-Adaptive and Robust Federated Spectrum Sensing without Benign Majority for Cellular Networks
Ngoc Duy Pham, Thusitha Dayaratne, Viet Vo +5
Advancements in wireless and mobile technologies, including 5G advanced and the envisioned 6G, are driving exponential growth in wireless devices. However, this rapid expansion exa…
A Login Page Transparency and Visual Similarity Based Zero Day Phishing Defense Protocol
Gaurav Varshney, Akanksha Raj, Divya Sangwan +3
Phishing is a prevalent cyberattack that uses look-alike websites to deceive users into revealing sensitive information. Numerous efforts have been made by the Internet community a…
Setup Once, Secure Always: A Single-Setup Secure Federated Learning Aggregation Protocol with Forward and Backward Secrecy for Dynamic Users
Nazatul Haque Sultan, Yan Bo, Yansong Gao +10
Federated Learning (FL) enables multiple users to collaboratively train a machine learning model without sharing raw data, making it suitable for privacy-sensitive applications. Ho…
Quantum Down Sampling Filter for Variational Auto-encoder
Farina Riaz, Fakhar Zaman, Hajime Suzuki +2
Variational autoencoders (VAEs) are fundamental for generative modeling and image reconstruction, yet their performance often struggles to maintain high fidelity in reconstructions…