Stochastic Mixed-Signal Circuit Design for In-sensor Privacy : (Invited Paper)

The ubiquitous data acquisition and extensive data exchange of sensors pose severe security and privacy concerns for the end-users and the public. To enable real-time protection of raw data, it is demanding to facilitate privacy-preserving algorithms at data generation, or in-sensory privacy. Howeve...

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Published in:2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD) pp. 1 - 9
Main Authors: Cao, Ningyuan, Liu, Jianbo, Cheng, Boyang, Chang, Muya
Format: Conference Proceeding
Language:English
Published: ACM 29.10.2022
Subjects:
Analytical models
compressed sensing
Computational modeling
Computer architecture
Data protection
internet-of-things
mixed-signal computation
Privacy
privacy-by-default
privacy-by-design
privacy-preserving computation
Semiconductor device modeling
Stochastic processes
ISSN:1558-2434
Online Access:Get full text
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Abstract The ubiquitous data acquisition and extensive data exchange of sensors pose severe security and privacy concerns for the end-users and the public. To enable real-time protection of raw data, it is demanding to facilitate privacy-preserving algorithms at data generation, or in-sensory privacy. However, due to the severe sensor resource constraints and intensive computation/security cost, it remains an open question of how to enable data protection algorithms with efficient c ircuit techniques. To answer this question, this paper discusses the potential of a stochastic mixed-signal (SMS) circuit for ultra-low-power, small-foot-print data security. In particular, this paper discusses digitally-controlled-oscillators (DCO) and their advantages in (1) seamless analog interface, (2) stochastic computation efficiency, and (3) unified entropy generation over conventional digital circuit baselines. With DCO as an illustrative case, we target (1) SMS privacy-preserving architecture definition and systematic SMS analysis on its performance gains across various hardware/software configurations, and (2) revisit analog/mixed-signal voltage/transistor scaling in the context of entropy-based data protection.
AbstractList The ubiquitous data acquisition and extensive data exchange of sensors pose severe security and privacy concerns for the end-users and the public. To enable real-time protection of raw data, it is demanding to facilitate privacy-preserving algorithms at data generation, or in-sensory privacy. However, due to the severe sensor resource constraints and intensive computation/security cost, it remains an open question of how to enable data protection algorithms with efficient c ircuit techniques. To answer this question, this paper discusses the potential of a stochastic mixed-signal (SMS) circuit for ultra-low-power, small-foot-print data security. In particular, this paper discusses digitally-controlled-oscillators (DCO) and their advantages in (1) seamless analog interface, (2) stochastic computation efficiency, and (3) unified entropy generation over conventional digital circuit baselines. With DCO as an illustrative case, we target (1) SMS privacy-preserving architecture definition and systematic SMS analysis on its performance gains across various hardware/software configurations, and (2) revisit analog/mixed-signal voltage/transistor scaling in the context of entropy-based data protection.
Author Cheng, Boyang
Cao, Ningyuan
Liu, Jianbo
Chang, Muya
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  fullname: Liu, Jianbo
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  surname: Chang
  fullname: Chang, Muya
  organization: University of Notre Dame,Department of Electrical Engineering,South Bend,46556
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Snippet The ubiquitous data acquisition and extensive data exchange of sensors pose severe security and privacy concerns for the end-users and the public. To enable...
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SubjectTerms Analytical models
compressed sensing
Computational modeling
Computer architecture
Data protection
internet-of-things
mixed-signal computation
Privacy
privacy-by-default
privacy-by-design
privacy-preserving computation
Semiconductor device modeling
Stochastic processes
Title Stochastic Mixed-Signal Circuit Design for In-sensor Privacy : (Invited Paper)
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