SaTC: STARSS: Small: Design of Low-Power True Random Number Generator based on Adaptive Post-Processing
SaTC: STARSS: Small: Design of Low-Power True Random Number Generator based on Adaptive Post-Processing
批准号:
1714496
负责人:
Visvesh Sathe
金额:
$24.67万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-10-01 至 2020-09-30
中文摘要
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英文摘要
Nearly all security protocols rely on random numbers. A hardware True Random Number Generator (TRNG) is a circuit implemented within an Integrated Circuit (IC). If a TRNG is not truly random, an adversary may be able to break into the security of a protocol. Hence true randomness is an important property. TRNG circuits are often large and power hungry. There is a need for low-power TRNG in battery operated devices or in energy constrained environments. This proposal addresses that need. The proposed research explores an alternative to traditional TRNG designs. Instead of taking on considerable design complexity and energy dissipation by directly turning circuits to generate high quality random numbers, it starts with a sufficiently good physical circuit random number generator, and then combines it with a robust low-power statistical post-processing unit to address both bias, and correlation between TRNG outputs. This results in a design where the first component is only required to provide some randomness, while the second component refines this randomness through decorrelation and bias removal to extract provably perfectly random sequence of bits akin to identical and independent fair coin flips. This design will be implemented in a silicon prototype. The proposed research is interdisciplinary involving applied probability, network security, and VLSI design.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
A 65-nm CMOS 3.2-to-86 Mb/s 2.58 pJ/bit Highly Digital True-Random-Number Generator With Integrated De-Correlation and Bias Correction
具有集成去相关和偏差校正功能的 65 nm CMOS 3.2 至 86 Mb/s 2.58 pJ/bit 高度数字化真随机数发生器
DOI:
10.1109/lssc.2019.2896777
发表时间:
2018
期刊:
IEEE Solid-State Circuits Letters
影响因子:
2.7
作者:
[Pamula, Venkata Rajesh, Sun, Xun, Kim, Sung Min, Rahman, Fahim ur, Zhang, Baosen, Sathe, Visvesh S.]
通讯作者:
Sathe, Visvesh S.
CAREER: Transforming Implantable Neural Interfaces through Computing: From Circuits to Systems
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批准号:2317764
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项目类别:Continuing Grant
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资助金额:$51.41万
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财政年份:2023
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负责人:Visvesh Sathe
-
依托单位:
CAREER: Transforming Implantable Neural Interfaces through Computing: From Circuits to Systems
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批准号:1844791
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项目类别:Continuing Grant
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资助金额:$51.41万
-
财政年份:2019
-
负责人:Visvesh Sathe
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依托单位:
海外基金