Qingzhao Zhang

The paper proposes a new cryptographic bearer token design enabling fully offline e-cash withdrawals from ATMs, thereby removing the central bank as a critical dependency.

The paper introduces a stealthy, scenario-realistic data fabrication attack that subtly manipulates object poses in shared perception data to induce unsafe driving behaviors in connected and autonomous vehicles, while evading existing defenses.

The paper introduces a novel adversarial attack that uses static, view-dependent camouflage on a vehicle to induce consistent feature drift, causing autonomous systems to predict false, yet plausible, trajectories like unnecessary cut-ins.

The paper introduces TrustFlip, a novel physical adversarial attack that exploits consistency-based trust defenses in vehicular collaborative perception by using genuine objects to induce inconsistencies among benign vehicles, thereby poisoning the trust scores of targeted vehicles.