1,992 research outputs found
User microprogrammable processors for high data rate telemetry preprocessing
The use of microprogrammable processors for the preprocessing of high data rate satellite telemetry is investigated. The following topics are discussed along with supporting studies: (1) evaluation of commercial microprogrammable minicomputers for telemetry preprocessing tasks; (2) microinstruction sets for telemetry preprocessing; and (3) the use of multiple minicomputers to achieve high data processing. The simulation of small microprogrammed processors is discussed along with examples of microprogrammed processors
ScaRR: Scalable Runtime Remote Attestation for Complex Systems
The introduction of remote attestation (RA) schemes has allowed academia and
industry to enhance the security of their systems. The commercial products
currently available enable only the validation of static properties, such as
applications fingerprint, and do not handle runtime properties, such as
control-flow correctness. This limitation pushed researchers towards the
identification of new approaches, called runtime RA. However, those mainly work
on embedded devices, which share very few common features with complex systems,
such as virtual machines in a cloud. A naive deployment of runtime RA schemes
for embedded devices on complex systems faces scalability problems, such as the
representation of complex control-flows or slow verification phase.
In this work, we present ScaRR: the first Scalable Runtime Remote attestation
schema for complex systems. Thanks to its novel control-flow model, ScaRR
enables the deployment of runtime RA on any application regardless of its
complexity, by also achieving good performance. We implemented ScaRR and tested
it on the benchmark suite SPEC CPU 2017. We show that ScaRR can validate on
average 2M control-flow events per second, definitely outperforming existing
solutions.Comment: 14 page
C-FLAT: Control-FLow ATtestation for Embedded Systems Software
Remote attestation is a crucial security service particularly relevant to
increasingly popular IoT (and other embedded) devices. It allows a trusted
party (verifier) to learn the state of a remote, and potentially
malware-infected, device (prover). Most existing approaches are static in
nature and only check whether benign software is initially loaded on the
prover. However, they are vulnerable to run-time attacks that hijack the
application's control or data flow, e.g., via return-oriented programming or
data-oriented exploits. As a concrete step towards more comprehensive run-time
remote attestation, we present the design and implementation of Control- FLow
ATtestation (C-FLAT) that enables remote attestation of an application's
control-flow path, without requiring the source code. We describe a full
prototype implementation of C-FLAT on Raspberry Pi using its ARM TrustZone
hardware security extensions. We evaluate C-FLAT's performance using a
real-world embedded (cyber-physical) application, and demonstrate its efficacy
against control-flow hijacking attacks.Comment: Extended version of article to appear in CCS '16 Proceedings of the
23rd ACM Conference on Computer and Communications Securit
LO-FAT: Low-Overhead Control Flow ATtestation in Hardware
Attacks targeting software on embedded systems are becoming increasingly
prevalent. Remote attestation is a mechanism that allows establishing trust in
embedded devices. However, existing attestation schemes are either static and
cannot detect control-flow attacks, or require instrumentation of software
incurring high performance overheads. To overcome these limitations, we present
LO-FAT, the first practical hardware-based approach to control-flow
attestation. By leveraging existing processor hardware features and
commonly-used IP blocks, our approach enables efficient control-flow
attestation without requiring software instrumentation. We show that our
proof-of-concept implementation based on a RISC-V SoC incurs no processor
stalls and requires reasonable area overhead.Comment: Authors' pre-print version to appear in DAC 2017 proceeding
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