InFuzz: An Efficient and Lightweight In-Memory-Computing Cryptographic Fuzzy Extractor for IoT Security

Jing Kou; He Jiang; Liang Zhang; Boyi Zhang; Yang Sun; Hua Guo; Wang Kang

doi:10.1109/ISCAS66217.2026.11562225

InFuzz: An Efficient and Lightweight In-Memory-Computing Cryptographic Fuzzy Extractor for IoT Security

Jing Kou
, He Jiang
, Liang Zhang
, Boyi Zhang
, Yang Sun
, Hua Guo
, Wang Kang^*

^*Corresponding author for this work

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

As a vital cryptographic primitive for IoT security, the fuzzy extractor is capable of deriving uniformly random and precisely reproducible keys from noisy sources. However, conventional hardware implementations are critically limited by the "von Neumann bottleneck": large parity-check matrices must be repeatedly shuttled between memory and processing units, which causes significant energy consumption and latency. In this work, we introduce InFuzz, the first in-memory cryptographic fuzzy extractor architecture. Our design realizes an in-situ fuzzy extractor using Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes directly within an SRAM array, eliminating costly data movement. Evaluated in a 28nm process, InFuzz achieves a total latency of 9.93 μs and an energy consumption of 8.43 nJ, improving energy efficiency by up to 68.0× over prior implementations. By integrating storage and computation, this work presents a novel, ultra-low-power pathway for secure key generation on resource-constrained edge devices.

Original language	English
Title of host publication	ISCAS 2026 - 2026 IEEE International Symposium on Circuits and Systems
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	365-369
Number of pages	5
ISBN (Electronic)	9798331577698
DOIs	https://doi.org/10.1109/ISCAS66217.2026.11562225
State	Published - 2026
Event	2026 IEEE International Symposium on Circuits and Systems, ISCAS 2026 - Shanghai, China Duration: 24 May 2026 → 27 May 2026

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)	0271-4310

Conference

Conference	2026 IEEE International Symposium on Circuits and Systems, ISCAS 2026
Country/Territory	China
City	Shanghai
Period	24/05/26 → 27/05/26

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Biometric Cryptosystem
Fuzzy Extractor
In-Memory-Computing
Physical Unclonable Function

Access to Document

10.1109/ISCAS66217.2026.11562225

Cite this

Kou, J., Jiang, H., Zhang, L., Zhang, B., Sun, Y., Guo, H., & Kang, W. (2026). InFuzz: An Efficient and Lightweight In-Memory-Computing Cryptographic Fuzzy Extractor for IoT Security. In ISCAS 2026 - 2026 IEEE International Symposium on Circuits and Systems (pp. 365-369). (Proceedings - IEEE International Symposium on Circuits and Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAS66217.2026.11562225

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title = "InFuzz: An Efficient and Lightweight In-Memory-Computing Cryptographic Fuzzy Extractor for IoT Security",

abstract = "As a vital cryptographic primitive for IoT security, the fuzzy extractor is capable of deriving uniformly random and precisely reproducible keys from noisy sources. However, conventional hardware implementations are critically limited by the {"}von Neumann bottleneck{"}: large parity-check matrices must be repeatedly shuttled between memory and processing units, which causes significant energy consumption and latency. In this work, we introduce InFuzz, the first in-memory cryptographic fuzzy extractor architecture. Our design realizes an in-situ fuzzy extractor using Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes directly within an SRAM array, eliminating costly data movement. Evaluated in a 28nm process, InFuzz achieves a total latency of 9.93 μs and an energy consumption of 8.43 nJ, improving energy efficiency by up to 68.0{\texttimes} over prior implementations. By integrating storage and computation, this work presents a novel, ultra-low-power pathway for secure key generation on resource-constrained edge devices.",

keywords = "Biometric Cryptosystem, Fuzzy Extractor, In-Memory-Computing, Physical Unclonable Function",

author = "Jing Kou and He Jiang and Liang Zhang and Boyi Zhang and Yang Sun and Hua Guo and Wang Kang",

note = "Publisher Copyright: {\textcopyright} 2026 IEEE.; 2026 IEEE International Symposium on Circuits and Systems, ISCAS 2026 ; Conference date: 24-05-2026 Through 27-05-2026",

year = "2026",

doi = "10.1109/ISCAS66217.2026.11562225",

language = "英语",

series = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "365--369",

booktitle = "ISCAS 2026 - 2026 IEEE International Symposium on Circuits and Systems",

address = "美国",

}

Kou, J, Jiang, H, Zhang, L, Zhang, B, Sun, Y, Guo, H & Kang, W 2026, InFuzz: An Efficient and Lightweight In-Memory-Computing Cryptographic Fuzzy Extractor for IoT Security. in ISCAS 2026 - 2026 IEEE International Symposium on Circuits and Systems. Proceedings - IEEE International Symposium on Circuits and Systems, Institute of Electrical and Electronics Engineers Inc., pp. 365-369, 2026 IEEE International Symposium on Circuits and Systems, ISCAS 2026, Shanghai, China, 24/05/26. https://doi.org/10.1109/ISCAS66217.2026.11562225

InFuzz: An Efficient and Lightweight In-Memory-Computing Cryptographic Fuzzy Extractor for IoT Security. / Kou, Jing; Jiang, He; Zhang, Liang et al.
ISCAS 2026 - 2026 IEEE International Symposium on Circuits and Systems. Institute of Electrical and Electronics Engineers Inc., 2026. p. 365-369 (Proceedings - IEEE International Symposium on Circuits and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - InFuzz

T2 - 2026 IEEE International Symposium on Circuits and Systems, ISCAS 2026

AU - Kou, Jing

AU - Jiang, He

AU - Zhang, Liang

AU - Zhang, Boyi

AU - Sun, Yang

AU - Guo, Hua

AU - Kang, Wang

PY - 2026

Y1 - 2026

N2 - As a vital cryptographic primitive for IoT security, the fuzzy extractor is capable of deriving uniformly random and precisely reproducible keys from noisy sources. However, conventional hardware implementations are critically limited by the "von Neumann bottleneck": large parity-check matrices must be repeatedly shuttled between memory and processing units, which causes significant energy consumption and latency. In this work, we introduce InFuzz, the first in-memory cryptographic fuzzy extractor architecture. Our design realizes an in-situ fuzzy extractor using Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes directly within an SRAM array, eliminating costly data movement. Evaluated in a 28nm process, InFuzz achieves a total latency of 9.93 μs and an energy consumption of 8.43 nJ, improving energy efficiency by up to 68.0× over prior implementations. By integrating storage and computation, this work presents a novel, ultra-low-power pathway for secure key generation on resource-constrained edge devices.

AB - As a vital cryptographic primitive for IoT security, the fuzzy extractor is capable of deriving uniformly random and precisely reproducible keys from noisy sources. However, conventional hardware implementations are critically limited by the "von Neumann bottleneck": large parity-check matrices must be repeatedly shuttled between memory and processing units, which causes significant energy consumption and latency. In this work, we introduce InFuzz, the first in-memory cryptographic fuzzy extractor architecture. Our design realizes an in-situ fuzzy extractor using Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes directly within an SRAM array, eliminating costly data movement. Evaluated in a 28nm process, InFuzz achieves a total latency of 9.93 μs and an energy consumption of 8.43 nJ, improving energy efficiency by up to 68.0× over prior implementations. By integrating storage and computation, this work presents a novel, ultra-low-power pathway for secure key generation on resource-constrained edge devices.

KW - Biometric Cryptosystem

KW - Fuzzy Extractor

KW - In-Memory-Computing

KW - Physical Unclonable Function

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PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 24 May 2026 through 27 May 2026

ER -

Kou J, Jiang H, Zhang L, Zhang B, Sun Y, Guo H et al. InFuzz: An Efficient and Lightweight In-Memory-Computing Cryptographic Fuzzy Extractor for IoT Security. In ISCAS 2026 - 2026 IEEE International Symposium on Circuits and Systems. Institute of Electrical and Electronics Engineers Inc. 2026. p. 365-369. (Proceedings - IEEE International Symposium on Circuits and Systems). doi: 10.1109/ISCAS66217.2026.11562225

InFuzz: An Efficient and Lightweight In-Memory-Computing Cryptographic Fuzzy Extractor for IoT Security

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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