ROLoad-PMP: Securing Sensitive Operations for Kernels and Bare-Metal Firmware

A common way for attackers to compromise victim systems is hijacking sensitive operations e.g., control-flow transfers with attacker-controlled inputs. Existing solutions in general only protect parts of these targets and have high performance overheads, which are impractical and hard to deploy o...

RRAM-DP: Device-Calibrated Differential Privacy for In-Memory Edge Learning

Edge Artificial Intelligence of Things AIoT systems often collect sensitive data in situ, raising serious privacy concerns. Resistive-switching random-access memory RRAM is an attractive substrate for efficient AIoT thanks to its multi-bit storage and compute-in-memory CiM capabilities, while its...

Guillotine: Hypervisors for Isolating Malicious AIs

As AI models become more embedded in critical sectors like finance, healthcare, and the military, their inscrutable behavior poses ever-greater risks to society. To mitigate this risk, we propose Guillotine, a hypervisor architecture for sandboxing powerful AI models -- models that, by accident o...