Characterizing Security Monitor and Embedded System Performance Across Distinct RISC-V IP-Cores

Abstract

Embedded systems have seen a rapid integration into all forms of industry as they continue to shrink in size and cost. The increased demand has highlighted a need for secure systems that are robust to attacks and demonstrate reliable performance, especially if the system operation is time-critical. Efforts to characterize the performance of secure systems have been obstructed either by proprietary restrictions or ineffective analysis. Proprietary technology limits a comprehensive validation of a system's security and the implications it might have on performance. Performance analysis that is disclosed often lacks sufficient statistical rigor needed for a complex system. A non-proprietary processor standard, called RISC-V, may allow sufficient transparency to thoroughly model performance trade-offs. This research shows that a security platform and embedded system performance can be characterized through non-parametric statistics methodology, and provides a substantive foundation to scrutinize system design considerations that impact performance. This work proposes a new framework, the SPARC, that pioneers a synthesis of difference and equivalence hypothesis testing to provide relevant conclusions. SPARC is used to characterize performance of three RISC-V embedded systems with and without a security platform, Keystone, instantiated on an FPGA.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2021
Accession Number
AD1135181

Entities

People

  • Justin C. Tullos

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Cyber
  • Engineered Resilient Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Application-Specific Integrated Circuits
  • Complex Systems
  • Computational Science
  • Computer Programming
  • Computers
  • Data Analysis
  • Data Science
  • Experimental Design
  • Field Programmable Gate Arrays
  • Information Science
  • Instruction Set Architecture
  • Integrated Circuits
  • Knowledge Management
  • Operating Systems
  • Performance Tests
  • Statistical Analysis

Fields of Study

  • Computer science

Readers

  • Cybersecurity.
  • Parallel and Distributed Computing.
  • Systems Analysis and Design