Demo Data from VLDB 2026 / reviewers in the wild / expert
Fitria Nur Andini
dblp:178/5280
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Hardware security and side channels › hardware security primitives › physical unclonable function
helper data algorithms |
0.3 | 1 | 2017 | Optimized Quantization in Zero Leakage Helper Data Systems · IEEE Trans. Inf. Forensics Secur. 2017 |
Cryptographic primitives and cryptanalysis › key generation
key extraction |
0.3 | 1 | 2017 | 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 |
0.3 | 1 | 2017 | Optimized Quantization in Zero Leakage Helper Data Systems · IEEE Trans. Inf. Forensics Secur. 2017 |
Hardware security and side channels
side-channel attack |
0.3 | 1 | 2017 | Optimized Quantization in Zero Leakage Helper Data Systems · IEEE Trans. Inf. Forensics Secur. 2017 |
Coding theory › source coding
quantization |
0.1 | 1 | 2017 | 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
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Optimized Quantization in Zero Leakage Helper Data SystemsabstractHelper 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 |