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SHA-3 (Secure Hash Algorithm 3) is the latest member of the Secure Hash Algorithm family of standards, released by NIST on August 5, 2015. Although part of the same series of standards, SHA-3 is internally different from the MD5-like structure of SHA-1 and SHA-2.
The analysis highlights History, Standards and Art as prominent areas in the source structure around SHA-3.
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
The extracted context around SHA-3 shows recurring relationship patterns in the source. For example, SHA-3 → Because, Craig Clapp, Daemen, Gilles Van Assche, Guido Bertoni, In, It, Joan Daemen, MD5, Michaël Peeters, NIST, NIST Hash Workshop, PANAMA, Peeters, RadioGatún, Rijndael, SHA-0, SHA-1, SHA-2, The Another extracted example is SHA-3 → AMD Athlon, Duo, However, IA-32, IA-64, Intel Core, Intel Pentium, Keccak-f, MMX, NOP, Pi, SHA3-224, SHA3-256, SHA3-384, SHA3-512, SSE, The, XOR, XORed, XORing. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
hash bits keccak nist function security sha-2 bit functions message using permutation output hashing capacity state length different algorithm faster
TTTA extracted 132 structured relationships around SHA-3. Examples in this analysis include SHA-3 → is a → subset of the broader cryptographic primitive family Keccak and SHA-3 → is a → subset of the Keccak family. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| SHA-3 | is a | subset of the broader cryptographic primitive family Keccak | 0.90 | text |
| SHA-3 | is a | subset of the Keccak family | 0.90 | text |
| optimal asymmetric encryption padding | instance of | which is useful in applications | 0.80 | text |
| SHA-3 or ParallelHash | instance of | Such property is not exhibited by hash functions | 0.80 | text |
| ParallelHash128 | instance of | The processors support a complete implementation of the entire SHA-3 and SHAKE algorithms via the KIMD and KLMD instructions using a hardware assist engine built into each core.… | 0.80 | text |
| ParallelHash128 | instance of | Parallel variantsIt is easier to accelerate parallel variants of SHA-3 | 0.80 | text |
| SHA-3 | related to Additional instances | In December | 0.60 | section |
| SHA-3 | related to Additional instances | NIST | 0.60 | section |
| SHA-3 | related to Additional instances | NIST SP | 0.60 | section |
| SHA-3 | related to Additional instances | SHA-3-derived | 0.60 | section |
| SHA-3 | related to Additional instances | It | 0.60 | section |
| SHA-3 | related to Additional instances | When | 0.60 | section |
The concept neighborhoods around SHA-3 bring nearby vocabulary together. In this analysis, examples include Standard, Uses and Using. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For SHA-3, one of the stronger structural bridges in this analysis connects SHA-3 with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around SHA-3 to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Standards & Art, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — SHA-3 · EN edition · Analysis: TopicsToTalkAbout