6 papers
DoSQ: A Cross-Layer Denial of Service Quality Attack by Exploiting Side Channels in 5G NR
Mahmudul Hassan Ashik, Moinul Hossain
The 3rd Generation Partnership Project (3GPP)'s Fifth Generation New Radio (5G NR) is critical to supporting mission-critical services. However, 5G systems are vulnerable to smart…
FLINT: Fingerprinting Federated Learning Architectures from 5G PHY-Layer Side Channels
Md Nahid Hasan Shuvo, Mahmudul Hassan Ashik, Moinul Hossain
Federated Learning (FL) over 5G cellular networks protects raw data but remains vulnerable to side-channel leakage. Prior fingerprinting attacks assume packet-level network visibil…
Analyzing the Impact of Adversarial Attacks on C-V2X-Enabled Road Safety: An Age of Information Perspective
Mahmudul Hassan Ashik, Moinul Hossain
The Cellular Vehicle-to-Everything (C-V2X), introduced and developed by the 3GPP, is a promising technology for the Autonomous Driving System (ADS). C-V2X aims to fulfill the Servi…
PHANTOM: PHysical ANamorphic Threats Obstructing Connected Vehicle Mobility
Md Nahid Hasan Shuvo, Moinul Hossain
Connected autonomous vehicles (CAVs) rely on vision-based deep neural networks (DNNs) and low-latency (Vehicle-to-Everything) V2X communication to navigate safely and efficiently.…
FLARE: A Wireless Side-Channel Fingerprinting Attack on Federated Learning
Md Nahid Hasan Shuvo, Moinul Hossain, Anik Mallik +2
Federated Learning (FL) enables collaborative model training across distributed devices while safeguarding data and user privacy. However, FL remains susceptible to privacy threats…
Fingerprinting Deep Learning Models via Network Traffic Patterns in Federated Learning
Md Nahid Hasan Shuvo, Moinul Hossain
Federated Learning (FL) is increasingly adopted as a decentralized machine learning paradigm due to its capability to preserve data privacy by training models without centralizing…