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Innehåll tillhandahållet av Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.
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The Impact of Architecture on Cyber-Physical Systems Safety

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Manage episode 397423155 series 3018913
Innehåll tillhandahållet av Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

As developers continue to build greater autonomy into cyber-physical systems (CPSs), such as unmanned aerial vehicles (UAVs) and automobiles, these systems aggregate data from an increasing number of sensors. However, more sensors not only create more data and more precise data, but they require a complex architecture to correctly transfer and process multiple data streams. This increase in complexity comes with additional challenges for functional verification and validation, a greater potential for faults, and a larger attack surface. What’s more, CPSs often cannot distinguish faults from attacks. To address these challenges, researchers from the SEI and Georgia Tech collaborated on an effort to map the problem space and develop proposals for solving the challenges of increasing sensor data in CPSs. In this podcast from the Carnegie Mellon University Software Engineering Institute, Jerome Hugues, a principal researcher in the SEI Software Solutions Division, discusses this collaboration and its larger body of work, Safety Analysis and Fault Detection Isolation and Recovery (SAFIR) Synthesis for Time-Sensitive Cyber-Physical Systems.

  continue reading

429 episoder

Artwork
iconDela
 
Manage episode 397423155 series 3018913
Innehåll tillhandahållet av Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Carnegie Mellon University Software Engineering Institute and Members of Technical Staff at the Software Engineering Institute eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

As developers continue to build greater autonomy into cyber-physical systems (CPSs), such as unmanned aerial vehicles (UAVs) and automobiles, these systems aggregate data from an increasing number of sensors. However, more sensors not only create more data and more precise data, but they require a complex architecture to correctly transfer and process multiple data streams. This increase in complexity comes with additional challenges for functional verification and validation, a greater potential for faults, and a larger attack surface. What’s more, CPSs often cannot distinguish faults from attacks. To address these challenges, researchers from the SEI and Georgia Tech collaborated on an effort to map the problem space and develop proposals for solving the challenges of increasing sensor data in CPSs. In this podcast from the Carnegie Mellon University Software Engineering Institute, Jerome Hugues, a principal researcher in the SEI Software Solutions Division, discusses this collaboration and its larger body of work, Safety Analysis and Fault Detection Isolation and Recovery (SAFIR) Synthesis for Time-Sensitive Cyber-Physical Systems.

  continue reading

429 episoder

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