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Fitria Nur Andini

dblp:178/5280 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Hardware security and side channels · 75% Cryptographic primitives and cryptanalysis · 25%
Theoretical computer science
1 paper
Coding theory · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Hardware security and side channels › hardware security primitives › physical unclonable function
helper data algorithms
0.312017
Optimized Quantization in Zero Leakage Helper Data Systems · IEEE Trans. Inf. Forensics Secur. 2017
Cryptographic primitives and cryptanalysis › key generation
key extraction
0.312017
Optimized Quantization in Zero Leakage Helper Data Systems · IEEE Trans. Inf. Forensics Secur. 2017
Hardware security and side channels › hardware security primitives
physical unclonable function
0.312017
Optimized Quantization in Zero Leakage Helper Data Systems · IEEE Trans. Inf. Forensics Secur. 2017
Hardware security and side channels
side-channel attack
0.312017
Optimized Quantization in Zero Leakage Helper Data Systems · IEEE Trans. Inf. Forensics Secur. 2017
Coding theory › source coding
quantization
0.112017
Optimized Quantization in Zero Leakage Helper Data Systems · IEEE Trans. Inf. Forensics Secur. 2017

Methods — techniques the papers use, named apart from their topics

zero leakage quantization · 0.6error correction · 0.6
YearPublicationVenuePosition
2017 Optimized Quantization in Zero Leakage Helper Data Systems
abstract
Helper data systems are a cryptographic primitive that allows for the reproducible extraction of secrets from noisy measurements. Redundancy data called helper data makes it possible to do error correction while leaking little or nothing (Zero Leakage) about the extracted secret string. We study the case of non-discrete measurement outcomes. In this case, a quantization step is required. Recently, de Grootet al.described a generic method to perform the quantization in a Zero Leakage manner. We extend their work and show how the quantization intervals should be set to maximize the amount of extracted secret key material when noise is taken into account.
Taras Stanko, Fitria Nur Andini, Boris Skoric
IEEE Trans. Inf. Forensics Secur.2