Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

MD6

The MD6 Message-Digest Algorithm is a cryptographic hash function. It uses a Merkle tree-like structure to allow for immense parallel computation of hashes for very long inputs. Authors claim a performance of 28 cycles per byte for MD6-256 on an Intel Core 2 Duo and provable resistance against differential cryptanalysis. The source code of the reference…

Overview, Tool & MD6 hash test vectors

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Research this topic

Explore the main themes, entities and connections around MD6. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

Designers
Ronald Rivest, Benjamin Agre, Dan Bailey, Sarah Cheng, Christopher Crutchfield, Yevgeniy Dodis, Kermin Fleming, Asif Khan, Jayant Krishnamurthy, Yuncheng Lin, Leo Reyzin, Emily…
Digest sizes
Variable, 0<d≤512 bits
First published
2008
Rounds
Variable. Default, Unkeyed=40+[d/4], Keyed=max(80,40+(d/4))
Series
MD2, MD4, MD5, MD6
Structure
Merkle tree

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

MD6 hash test vectors

Tool

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

MD6

Nodes19
Edges18
Triples9
Avg. degree1.89
Density0.105263
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

MD6

Top relations

related to External links · 3
MD6 → Archived, Wayback Machine, Wayback MachineMD6
Designers · 1
MD6 → Ronald Rivest, Benjamin Agre, Dan Bailey, Sarah Cheng, Christopher Crutchfield, Yevgeniy Dodis, Kermin Fleming, Asif Khan, Jayant Krishnamurthy, Yuncheng Lin, Leo Reyzin, Emily…
Digest sizes · 1
MD6 → Variable, 0d≤512 bits
First published · 1
MD6 → 2008
Rounds · 1
MD6 → Variable. Default, Unkeyed=40+[d/4], Keyed=max(80,40+(d/4))
Series · 1
MD6 → MD2, MD4, MD5, MD6
Structure · 1
MD6 → Merkle tree

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

reference hash differential implementation sha-3 rivest website function long fortify 2009 advance submitted nist competition posted proof resistant attacks faster

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
MD6DesignersRonald Rivest, Benjamin Agre, Dan Bailey, Sarah Cheng, Christopher Crutchfield, Yevgeniy Dodis, Kermin Fleming, Asif Khan, Jayant Krishnamurthy, Yuncheng Lin, Leo Reyzin, Emily…1.00infobox
MD6Digest sizesVariable, 0<d≤512 bits1.00infobox
MD6First published20081.00infobox
MD6RoundsVariable. Default, Unkeyed=40+[d/4], Keyed=max(80,40+(d/4))1.00infobox
MD6SeriesMD2, MD4, MD5, MD61.00infobox
MD6StructureMerkle tree1.00infobox
MD6related to External linksArchived0.60section
MD6related to External linksWayback MachineMD60.60section
MD6related to External linksWayback Machine0.60section

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.