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#hash-functions

SequenceHash: multihashing for the rest of us

Lobsters Hottest ↗ · 2026-10-02 Cached

Trail of Bits introduces SequenceHash and SequenceMAC, open-source multihashing constructions that work with any standard cryptographic hash function (SHA2, BLAKE, RIPEMD) rather than being tied to Keccak like NIST's TupleHash. The C2SP-approved spec ships with Rust, Go, and Python implementations plus test vectors, aimed at preventing ambiguous-input attacks in protocols like the Fiat-Shamir transform.

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#hash-functions

Adversarial examples for fast hash functions

Lobsters Hottest ↗ · 2026-09-20 Cached

This blog post provides an in-depth analysis of adversarial examples targeting fast hash functions, comparing their speed and collision resistance, and detailing vulnerabilities across multiple implementations.

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#hash-functions

From One Seed to a Thousand Leaves – Merkle's Authentication Tree

Hacker News Top ↗ · 2026-08-04 Cached

An educational blog post explaining Merkle's authentication tree and the Lamport-Diffie one-time signature scheme, covering the history of digital signatures and how one-way functions enable secure authentication.

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#hash-functions

Chopped, Stored, Secured – The Story of the Hash Function

Hacker News Top ↗ · 2026-06-10 Cached

A detailed historical and mathematical explanation of hash functions, from their invention by Arnold Dumey in 1956 as a memory indexing technique to modern cryptographic hashes, including Python implementations.

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#hash-functions

Only 17% of all 64-bit Integers are products of two 32-bit integers

Lobsters Hottest ↗ · 2026-05-22 Cached

Daniel Lemire explores what fraction of 64-bit integers can be expressed as the product of two 32-bit integers, finding that only about 17% are, with implications for hash function design.

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#hash-functions

#Exploration: A study of count-based exploration for deep reinforcement learning

OpenAI Blog ↗ · 2016-11-15 Cached

OpenAI researchers demonstrate that a simple count-based exploration approach using hash codes can achieve near state-of-the-art performance on high-dimensional deep RL benchmarks, challenging the assumption that count-based methods cannot scale to continuous state spaces.

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