Hybrid architectures for efficient and secure face authentication in embedded systems

Najwa Aaraj, Srivaths Ravi, Anand Raghunathan, Niraj Kumar Jha

Research output: Contribution to journalArticle

9 Scopus citations

Abstract

In this paper, we propose an efficient and secure embedded processing architecture that addresses various challenges involved in using face-based biometrics for authenticating a user to an embedded system. Our paper considers the use of robust face verifiers (PCA-LDA, Bayesian), and analyzes the computational workload involved in running their software implementations on an embedded processor. We then present a suite of hardware and software enhancements to accelerate these algorithms - fixed-point arithmetic, various code optimizations, generic custom instructions and dedicated coprocessors, and exploitation of parallel processing capabilities in multiprocessor systems-on-chip (SoCs). We also identify attacks targeted against the authentication process, and develop security measures to ensure the integrity of biometric code/data. We evaluated the proposed architectures in the context of popular open-source software implementations of face authentication algorithms running on a commercial embedded processor (Xtensa from Tensilica). Our paper shows that fast, in-system verification is possible even in the context of many resource-constrained embedded systems. We also demonstrate that the security of the authentication process for the given attack model can be achieved with minimum hardware overheads.

Original languageEnglish (US)
Pages (from-to)296-308
Number of pages13
JournalIEEE Transactions on Very Large Scale Integration (VLSI) Systems
Volume15
Issue number3
DOIs
StatePublished - Mar 1 2007

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Electrical and Electronic Engineering

Keywords

  • Coprocessors
  • Custom instructions
  • Embedded systems
  • Face biometrics
  • Multiprocessor systems
  • Security

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