Nilo Redini
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Nilo Redini has a total of 15 co-authors. Here are the top co-authors by number of shared publications:
- Christopher Kruegel
University of California, Santa Barbara, Santa Barbara, USA
2 shared publications - Giovanni Vigna
University of California, Santa Barbara, Santa Barbara, USA
2 shared publications - Andrea Continella
University of Twente, Enschede, Netherlands
1 shared publication - Aravind Machiry
Purdue University, West Lafayette, USA
1 shared publication Chad Spensky
Allthenticate, University of California, Santa Barbara & Massachusetts Institute of Technology, Goleta, CA, USA
1 shared publicationColin Unger
University of California, Santa Barbara, GOLETA, CA, USA
1 shared publication
Latest Publications
- Open Access
- 16 October 2023
- Published by Association for Computing Machinery (ACM)
- p. 32-45
Shimware: Toward Practical Security Retrofitting for Monolithic Firmware Images
- 16 October 2023
- Published by Association for Computing Machinery (ACM)
- p. 32-45
Open AccessShimware: Toward Practical Security Retrofitting for Monolithic Firmware Images
- Open Access
- 24 May 2021
- Published by Association for Computing Machinery (ACM)
- p. 95-109
Conware: Automated Modeling of Hardware Peripherals
Emulation is at the core of many security analyses. However, emulating embedded systems is still not possible in most cases. To facilitate this critical analysis, we present Conware, a hardware emulation framework that can automatically generate models for hardware peripherals, which alleviates one of the major challenges currently hindering embedded systems emulation. Conware enables individual peripherals to be modeled, exported, and combined with other peripherals in a pluggable fashion. Conware achieves this by first obtaining a recording of the low-level hardware interactions between the firmware and the peripheral, using either existing methods or our source-code instrumentation technique. These recordings are then used to create high-fidelity automata representations of the peripheral using novel automata-generation techniques. The various models can then be merged to facilitate full-system emulation of any embedded firmware that uses any of the modeled peripherals, even if that specific firmware or its target hardware was never directly instrumented. Indeed, we demonstrate that Conware is able to successfully emulate a peripheral-heavy firmware binary that was never instrumented, by merging the models of six unique peripherals that were trained on a development board using only the vendor-provided example code.
- 24 May 2021
- Published by Association for Computing Machinery (ACM)
- p. 95-109
Open AccessConware: Automated Modeling of Hardware Peripherals
Emulation is at the core of many security analyses. However, emulating embedded systems is still not possible in most cases. To facilitate this critical analysis, we present Conware, a hardware emulation framework that can automatically generate models for hardware peripherals, which alleviates one of the major challenges currently hindering embedded systems emulation. Conware enables individual peripherals to be modeled, exported, and combined with other peripherals in a pluggable fashion. Conware achieves this by first obtaining a recording of the low-level hardware interactions between the firmware and the peripheral, using either existing methods or our source-code instrumentation technique. These recordings are then used to create high-fidelity automata representations of the peripheral using novel automata-generation techniques. The various models can then be merged to facilitate full-system emulation of any embedded firmware that uses any of the modeled peripherals, even if that specific firmware or its target hardware was never directly instrumented. Indeed, we demonstrate that Conware is able to successfully emulate a peripheral-heavy firmware binary that was never instrumented, by merging the models of six unique peripherals that were trained on a development board using only the vendor-provided example code.