EDBT 2026 Demo / reviewers in the wild / expert
Michal Rybár
dblp:148/2304
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 3
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 |
Cryptographic primitives and cryptanalysis · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cryptographic primitives and cryptanalysis › message authentication codes
HMAC |
0.2 | 1 | 2014 | The Exact PRF-Security of NMAC and HMAC · CRYPTO (1) 2014 |
Cryptographic primitives and cryptanalysis
message authentication codes |
0.2 | 1 | 2014 | The Exact PRF-Security of NMAC and HMAC · CRYPTO (1) 2014 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | On the Memory-Hardness of Data-Independent Password-Hashing FunctionsabstractWe show attacks on five data-independent memory-hard functions (iMHF) that were submitted to the password hashing competition (PHC). Informally, an MHF is a function which cannot be evaluated on dedicated hardware, like ASICs, at significantly lower hardware and/or energy cost than evaluating a single instance on a standard single-core architecture. Data-independent means the memory access pattern of the function is independent of the input; this makes iMHFs harder to construct than data-dependent ones, but the latter can be attacked by various side-channel attacks. Joël Alwen, Peter Gazi, Chethan Kamath, Karen Azari, Georg Osang, Krzysztof Pietrzak, Leonid Reyzin, Michal Rolínek, Michal Rybár |
AsiaCCS | 9 |
| 2014 | The Exact PRF-Security of NMAC and HMAC
Peter Gazi, Krzysztof Pietrzak, Michal Rybár |
CRYPTO (1) | 3 |
| 2014 | Differentially-Private Logistic Regression for Detecting Multiple-SNP Association in GWAS Databases
Fei Yu 0005, Michal Rybár, Caroline Uhler, Stephen E. Fienberg |
Privacy in Statistical Databases | 2 |