6 papers
Toward Practical Decentralized Proof-of-Location via Physical Witnessing Zones
Tamor Tomson, Eduardo Brito, Amnir Hadachi +1
Digital services increasingly rely on claims that a person, device, or asset was in a specific place at a specific time. Today, those claims often depend on self-reported location…
Beyond Dark Knowledge: Mixup-Based Distillation for Reliable Predictions
José Medina, Paul Honeine, Abdelaziz Bensrhair +1
Knowledge Distillation (KD) and mixup have proven effective at inducing smoothness in class boundaries; KD captures inherent class relationships in probability distributions, and m…
Decentralized Proof-of-Location for Content Provenance: Towards Capture-Time Authenticity
Eduardo Brito, Fernando Castillo, Amnir Hadachi +2
Reliable use of real-world data requires confidence that recorded evidence reflects what actually occurred at the moment of capture. In adversarial or incentive-misaligned cyber-ph…
Mamba base PKD for efficient knowledge compression
José Medina, Amnir Hadachi, Paul Honeine +1
Deep neural networks (DNNs) have remarkably succeeded in various image processing tasks. However, their large size and computational complexity present significant challenges for d…
A Taxonomy and Methodology for Proof-of-Location Systems
Eduardo Brito, Fernando Castillo, Liina Kamm +2
Digital societies increasingly rely on trustworthy proofs of physical presence for services such as supply-chain tracking, e-voting, ride-sharing, and location-based rewards. Yet,…
Knowledge Distillation Neural Network for Predicting Car-following Behaviour of Human-driven and Autonomous Vehicles
Ayobami Adewale, Chris Lee, Amnir Hadachi +1
As we move towards a mixed-traffic scenario of Autonomous vehicles (AVs) and Human-driven vehicles (HDVs), understanding the car-following behaviour is important to improve traffic…