Fatemeh Arkannezhad (UCLA), Justin Feng (UCLA), Nader Sehatbakhsh (UCLA)

Remote attestation has received much attention recently due to the proliferation of embedded and IoT devices. Among various solutions, methods based on hardware-software co-design (hybrid) are particularly popular due to their low overhead yet effective approaches. Despite their usefulness, hybrid methods still suffer from multiple limitations such as strict protections required for the attestation keys and restrictive operation and threat models such as disabling interrupts and neglecting time-of-check-time-of-use (TOCTOU) attacks.

In this paper, we propose a new hybrid attestation method called IDA, which removes the requirement for disabling interrupts and restrictive access control for the secret key and attestation code, thus improving the system's overall security and flexibility. Rather than making use of a secret key to calculate the response, IDA verifies the attestation process with trusted hardware monitoring and certifies its authenticity only if it was followed precisely. Further, to prevent TOCTOU attacks and handle interrupts, we propose IDA+, which monitors program memory between attestation requests or during interrupts and informs the verifier of changes to the program memory. We implement and evaluate IDA and IDA+ on open-source MSP430 architecture, showing a reasonable overhead in terms of runtime, memory footprint, and hardware overhead while being robust against various attack scenarios. Comparing our method with the state-of-the-art, we show that it has minimal overhead while achieving important new properties such as support for interrupts and DMA requests and detecting TOCTOU attacks.

View More Papers

Stacking up the LLM Risks: Applied Machine Learning Security

Dr. Gary McGraw, Berryville Institute of Machine Learning

Read More

WIP: Towards a Certifiably Robust Defense for Multi-label Classifiers...

Dennis Jacob, Chong Xiang, Prateek Mittal (Princeton University)

Read More

Strengthening Privacy in Robust Federated Learning through Secure Aggregation

Tianyue Chu, Devriş İşler (IMDEA Networks Institute & Universidad Carlos III de Madrid), Nikolaos Laoutaris (IMDEA Networks Institute)

Read More

dRR: A Decentralized, Scalable, and Auditable Architecture for RPKI...

Yingying Su (Tsinghua university), Dan Li (Tsinghua university), Li Chen (Zhongguancun Laboratory), Qi Li (Tsinghua university), Sitong Ling (Tsinghua University)

Read More