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

PrintListener: Uncovering the Vulnerability of Fingerprint Authentication via the...

Man Zhou (Huazhong University of Science and Technology), Shuao Su (Huazhong University of Science and Technology), Qian Wang (Wuhan University), Qi Li (Tsinghua University), Yuting Zhou (Huazhong University of Science and Technology), Xiaojing Ma (Huazhong University of Science and Technology), Zhengxiong Li (University of Colorado Denver)

Read More

NODLINK: An Online System for Fine-Grained APT Attack Detection...

Shaofei Li (Key Laboratory of High-Confidence Software Technologies (MOE), School of Computer Science, Peking University), Feng Dong (Huazhong University of Science and Technology), Xusheng Xiao (Arizona State University), Haoyu Wang (Huazhong University of Science and Technology), Fei Shao (Case Western Reserve University), Jiedong Chen (Sangfor Technologies Inc.), Yao Guo (Key Laboratory of High-Confidence Software Technologies…

Read More

Inaudible Adversarial Perturbation: Manipulating the Recognition of User Speech...

Xinfeng Li (Zhejiang University), Chen Yan (Zhejiang University), Xuancun Lu (Zhejiang University), Zihan Zeng (Zhejiang University), Xiaoyu Ji (Zhejiang University), Wenyuan Xu (Zhejiang University)

Read More

CrowdGuard: Federated Backdoor Detection in Federated Learning

Phillip Rieger (Technical University of Darmstadt), Torsten Krauß (University of Würzburg), Markus Miettinen (Technical University of Darmstadt), Alexandra Dmitrienko (University of Würzburg), Ahmad-Reza Sadeghi (Technical University of Darmstadt)

Read More