Biblio

Unlike traditional processors, Internet of Things (IoT) devices are short of resources to incorporate mature protections (e.g. MMU, TrustZone) against modern control-flow attacks. Remote (control-flow) attestation is fast becoming a key instrument in securing such devices as it has proven the effectiveness on not only detecting runtime malware infestation of a remote device, but also saving the computing resources by moving the costly verification process away. However, few control-flow attestation schemes have been able to draw on any systematic research into the software specificity of bare-metal systems, which are widely deployed on resource-constrained IoT devices. To our knowledge, the unique design patterns of the system limit implementations of such expositions. In this paper, we present the design and proof-of-concept implementation of LAPE, a lightweight attestation of program execution scheme that enables detecting control-flow attacks for bare-metal systems without requiring hardware modification. With rudimentary memory protection support found in modern IoT-class microcontrollers, LAPE leverages software instrumentation to compartmentalize the firmware functions into several ”attestation compartments”. It then continuously tracks the control-flow events of each compartment and periodically reports them to the verifier. The PoC of the scheme is incorporated into an LLVM-based compiler to generate the LAPE-enabled firmware. By taking experiments with several real-world IoT firmware, the results show both the efficiency and practicality of LAPE.

Control-flow attacks cause powerful threats to the software integrity. Remote attestation for control flow is a crucial security service for ensuring the software integrity on embedded platforms. The fine-grained remote control-flow attestation with execution-profiling Control-Flow Graph (CFG) is applied to defend against control-flow attacks. It is a safe scheme but it may influence the runtime efficiency. In fact, we find out only the vulnerable parts of a program need being attested at costly fine-grained level to ensure the security, and the remaining normal parts just need a lightweight coarse-grained check to reduce the overhead. We propose Mutable Granularity Control-Flow Attestation (MGC-FA) scheme, which bases on a probabilistic model, to distinguish between the vulnerable and normal parts in the program and combine fine-grained and coarse-grained control-flow attestation schemes. MGC-FA employs the execution-profiling CFG to apply the remote control-flow attestation scheme on embedded devices. MGC-FA is implemented on Raspberry Pi with ARM TrustZone and the experimental results show its effect on balancing the relationship between runtime efficiency and control-flow security.