Tootfinder

from my link log —
Modern minimal perfect hashing: a survey.
https://arxiv.org/abs/2506.06536
saved 2025-06-11 https://dotat.at/:…

Modern Minimal Perfect Hashing: A Survey
Given a set $S$ of $n$ keys, a perfect hash function for $S$ maps the keys in $S$ to the first $m \geq n$ integers without collisions. It may return an arbitrary result for any key not in $S$ and is called minimal if $m = n$. The most important parameters are its space consumption, construction time, and query time. Years of research now enable modern perfect hash functions to be extremely fast to query, very space-efficient, and scale to billions of keys. Different approaches give different tr…

Contrastive Multi-View Graph Hashing
Yang Xu, Zuliang Yang, Kai Ming Ting
https://arxiv.org/abs/2508.12377 https://arxiv.org/pdf/2508.12377

Contrastive Multi-View Graph Hashing
Multi-view graph data, which both captures node attributes and rich relational information from diverse sources, is becoming increasingly prevalent in various domains. The effective and efficient retrieval of such data is an important task. Although multi-view hashing techniques have offered a paradigm for fusing diverse information into compact binary codes, they typically assume attributes-based inputs per view. This makes them unsuitable for multi-view graph data, where effectively encoding …

from my link log —
rapidhash: a very fast, high quality, platform-independent hashing algorithm.
https://github.com/Nicoshev/rapidhash
saved 2025-05-17

GitHub - Nicoshev/rapidhash: Very fast, high quality, platform-independent hashing algorithm.
Very fast, high quality, platform-independent hashing algorithm. - Nicoshev/rapidhash

DiffHash: Text-Guided Targeted Attack via Diffusion Models against Deep Hashing Image Retrieval
Zechao Liu, Zheng Zhou, Xiangkun Chen, Tao Liang, Dapeng Lang
https://arxiv.org/abs/2509.12824

DiffHash: Text-Guided Targeted Attack via Diffusion Models against Deep Hashing Image Retrieval
Deep hashing models have been widely adopted to tackle the challenges of large-scale image retrieval. However, these approaches face serious security risks due to their vulnerability to adversarial examples. Despite the increasing exploration of targeted attacks on deep hashing models, existing approaches still suffer from a lack of multimodal guidance, reliance on labeling information and dependence on pixel-level operations for attacks. To address these limitations, we proposed DiffHash, a no…

Crosslisted article(s) found for cs.IR. https://arxiv.org/list/cs.IR/new
[1/1]:
- Hashing-Baseline: Rethinking Hashing in the Age of Pretrained Models
Ilyass Moummad, Kawtar Zaher, Lukas Rauch, Alexis Joly

Succinct Oblivious Tensor Evaluation and Applications: Adaptively-Secure Laconic Function Evaluation and Trapdoor Hashing for All Circuits
Damiano Abram, Giulio Malavolta, Lawrence Roy
https://arxiv.org/abs/2508.09673

Succinct Oblivious Tensor Evaluation and Applications: Adaptively-Secure Laconic Function Evaluation and Trapdoor Hashing for All Circuits
We propose the notion of succinct oblivious tensor evaluation (OTE), where two parties compute an additive secret sharing of a tensor product of two vectors $\mathbf{x} \otimes \mathbf{y}$, exchanging two simultaneous messages. Crucially, the size of both messages and of the CRS is independent of the dimension of $\mathbf{x}$. We present a construction of OTE with optimal complexity from the standard learning with errors (LWE) problem. Then we show how this new technical tool enables a host o…

Definability of some $k$-ary Relations Over Second Order kinds of Logics
Simone Costa, Marco Dalai, Stefano Della Fiore, Anita Pasotti
https://arxiv.org/abs/2509.13063 https://

Definability of some $k$-ary Relations Over Second Order kinds of Logics
We consider the exprissibility in monadic second order logic of certain relations of importance in computer science. For integers $n\geq 1$ and $k\leq b$, a $k$-tuple of sequences in $\{0,1,\ldots, b-1\}^n$ are said to be $k$-hashed if there is a coordinate where they all differ. A set $\mathcal{C}$ of sequences is said to be a $k$-hash code if any $k$ distinct elements are $k$-hashed. Testing whether a code is $k$-hashing and determining the largest size of $k$-hash codes is an important probl…

from my link log —
Cuckoo hashing improves SIMD hash tables.
https://reiner.org/cuckoo-hashing
saved 2025-10-04 https://dotat.at/:/6GT24.html

Cuckoo hashing improves SIMD hash tables
Benchmarks and theoretical explanation of why and when cuckoo hashing beats sort beats hash tables.

NIST is done standardizing #ASCON, an encryption and hashing algorithm. I count that as a big win for #IoT security, in particular because the last review round's raised concerns were heeded and there is now a 32-bit tag mode usable for applications such as 802.15.4 link-layer security.
Congratulations…

NIST Finalizes ‘Lightweight Cryptography’ Standard to Protect Small Devices
Four related algorithms are now ready for use to protect data created and transmitted by the Internet of Things and other electronics

from my link log —
A new approach to analyzing Robin Hood hashing. (2014)
https://arxiv.org/abs/1401.7616
saved 2025-10-05 https://dotat.at/:/HOGQW.html…

A New Approach to Analyzing Robin Hood Hashing
Robin Hood hashing is a variation on open addressing hashing designed to reduce the maximum search time as well as the variance in the search time for elements in the hash table. While the case of insertions only using Robin Hood hashing is well understood, the behavior with deletions has remained open. Here we show that Robin Hood hashing can be analyzed under the framework of finite-level finite-dimensional jump Markov chains. This framework allows us to re-derive some past results for the in…

Probability distributions over CSS codes: two-universality, QKD hashing, collision bounds, security
Pete Rigas
https://arxiv.org/abs/2510.02402 https://arx…

Probability distributions over CSS codes: two-universality, QKD hashing, collision bounds, security
We characterize novel probability distributions for CSS codes. Such classes of error correcting codes, originally introduced by Calderbank, Shor, and Steane, are of great significance in advancing the fidelity of Quantum computation, with implications for future near term applications. Within the context of Quantum key distribution, such codes, as examined by Ostrev in arXiv: 2109.06709 along with two-universal hashing protocols, have greatly simplified Quantum phases of computation for uncondi…

Locality-Sensitive Hashing-Based Efficient Point Transformer for Charged Particle Reconstruction
Shitij Govil, Jack P. Rodgers, Yuan-Tang Chou, Siqi Miao, Amit Saha, Advaith Anand, Kilian Lieret, Gage DeZoort, Mia Liu, Javier Duarte, Pan Li, Shih-Chieh Hsu
https://arxiv.org/abs/2510.07594

Locality-Sensitive Hashing-Based Efficient Point Transformer for Charged Particle Reconstruction
Charged particle track reconstruction is a foundational task in collider experiments and the main computational bottleneck in particle reconstruction. Graph neural networks (GNNs) have shown strong performance for this problem, but costly graph construction, irregular computations, and random memory access patterns substantially limit their throughput. The recently proposed Hashing-based Efficient Point Transformer (HEPT) offers a theoretically guaranteed near-linear complexity for large point …

Spotlight Attention: Towards Efficient LLM Generation via Non-linear Hashing-based KV Cache Retrieval
Wenhao Li, Yuxin Zhang, Gen Luo, Haiyuan Wan, Ziyang Gong, Fei Chao, Rongrong Ji
https://arxiv.org/abs/2508.19740

Spotlight Attention: Towards Efficient LLM Generation via Non-linear Hashing-based KV Cache Retrieval
Reducing the key-value (KV) cache burden in Large Language Models (LLMs) significantly accelerates inference. Dynamically selecting critical KV caches during decoding helps maintain performance. Existing methods use random linear hashing to identify important tokens, but this approach is inefficient due to the orthogonal distribution of queries and keys within two narrow cones in LLMs. We introduce Spotlight Attention, a novel method that employs non-linear hashing functions to optimize the emb…

Hash chaining degrades security at Facebook
Thomas Rivasseau
https://arxiv.org/abs/2510.12665 https://arxiv.org/pdf/2510.12665

Hash chaining degrades security at Facebook
Modern web and digital application password storage relies on password hashing for storage and security. Ad-hoc upgrade of password storage to keep up with hash algorithm norms may be used to save costs but can introduce unforeseen vulnerabilities. This is the case in the password storage scheme used by Meta Platforms which services several billion monthly users worldwide. In this paper we present the first example of an exploit which demonstrates the security weakness of Facebook's password st…

from my link log —
Rendezvous hashing explained.
https://randorithms.com/2020/12/26/rendezvous-hashing.html
saved 2025-09-16 https://

Protecting Small Organizations from AI Bots with Logrip: Hierarchical IP Hashing
Rama Carl Hoetzlein
https://arxiv.org/abs/2508.03130 https://arxiv.org/pdf…

Protecting Small Organizations from AI Bots with Logrip: Hierarchical IP Hashing
Small organizations, start ups, and self-hosted servers face increasing strain from automated web crawlers and AI bots, whose online presence has increased dramatically in the past few years. Modern bots evade traditional throttling and can degrade server performance through sheer volume even when they are well-behaved. We introduce a novel security approach that leverages data visualization and hierarchical IP hashing to analyze server event logs, distinguishing human users from automated enti…

A blunt question: Which hashing algorithm do you prefer to use or even another unpopular algorithm? 🤔
I would be grateful for sharing the toot.
(we just discuss it without argument)
#hash #code #sha

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[2/2]:
- Spotlight Attention: Towards Efficient LLM Generation via Non-linear Hashing-based KV Cache Retri...
Wenhao Li, Yuxin Zhang, Gen Luo, Haiyuan Wan, Ziyang Gong, Fei Chao, Rongrong Ji

Probabilistic Guarantees to Explicit Constructions: Local Properties of Linear Codes
Fernando Granha Jeronimo, Nikhil Shagrithaya
https://arxiv.org/abs/2510.06185 https://

Probabilistic Guarantees to Explicit Constructions: Local Properties of Linear Codes
We present a general framework for derandomizing random linear codes with respect to a broad class of permutation-invariant properties, known as local properties, which encompass several standard notions such as distance, list-decoding, list-recovery, and perfect hashing. Our approach extends the classical Alon-Edmonds-Luby (AEL) construction through a modified formalism of local coordinate-wise linear (LCL) properties, introduced by Levi, Mosheiff, and Shagrithaya (2025). The main theorem demo…

Learning-Based Hashing for ANN Search: Foundations and Early Advances
Sean Moran
https://arxiv.org/abs/2510.04127 https://arxiv.org/pdf/2510.04127

Learning-Based Hashing for ANN Search: Foundations and Early Advances
Approximate Nearest Neighbour (ANN) search is a fundamental problem in information retrieval, underpinning large-scale applications in computer vision, natural language processing, and cross-modal search. Hashing-based methods provide an efficient solution by mapping high-dimensional data into compact binary codes that enable fast similarity computations in Hamming space. Over the past two decades, a substantial body of work has explored learning to hash, where projection and quantisation funct…

Wrangling Entropy: Next-Generation Multi-Factor Key Derivation, Credential Hashing, and Credential Generation Functions
Colin Roberts, Vivek Nair, Dawn Song
https://arxiv.org/abs/2509.05893

Wrangling Entropy: Next-Generation Multi-Factor Key Derivation, Credential Hashing, and Credential Generation Functions
The Multi-Factor Key Derivation Function (MFKDF) offered a novel solution to the classic problem of usable client-side key management by incorporating multiple popular authentication factors into a key derivation process, but was later shown to be vulnerable to cryptanalysis that degraded its security over multiple invocations. In this paper, we present the Entropy State Transition Modeling Framework (ESTMF), a novel cryptanalytic technique designed to reveal pernicious leaks of entropy across …

@… at https://cryptpad.fr/login/ I get the error described at

Secure and practical Quantum Digital Signatures
Federico Grasselli, Gaetano Russo, Massimiliano Proietti
https://arxiv.org/abs/2508.05355 https://arxiv.org…

Secure and practical Quantum Digital Signatures
Digital signatures represent a crucial cryptographic asset that must be protected against quantum adversaries. Quantum Digital Signatures (QDS) can offer solutions that are information-theoretically (IT) secure and thus immune to quantum attacks. In this work, we analyze three existing practical QDS protocols based on preshared secure keys (e.g., established with quantum key distribution) and universal hashing families. For each protocol, we make amendments to close potential loopholes and prov…

Crosslisted article(s) found for cs.IR. https://arxiv.org/list/cs.IR/new
[1/1]:
- Semantic-Cohesive Knowledge Distillation for Deep Cross-modal Hashing
Changchang Sun, Vickie Chen, Yan Yan

from my link log —
foldhash: A fast, non-cryptographic, minimally DoS-resistant hashing algorithm for Rust.
https://github.com/orlp/foldhash
saved 2025-09-14 https://…

GitHub - orlp/foldhash: A fast, non-cryptographic, minimally DoS-resistant hashing algorithm for Rust.
A fast, non-cryptographic, minimally DoS-resistant hashing algorithm for Rust. - orlp/foldhash

Privacy-Preserving Anonymization of System and Network Event Logs Using Salt-Based Hashing and Temporal Noise
Shreyas Bargale, Akshit Vakati Venkata, Jaimandeep Singh, Chester Rebeiro
https://arxiv.org/abs/2507.21904

Privacy-Preserving Anonymization of System and Network Event Logs Using Salt-Based Hashing and Temporal Noise
System and network event logs are essential for security analytics, threat detection, and operational monitoring. However, these logs often contain Personally Identifiable Information (PII), raising significant privacy concerns when shared or analyzed. A key challenge in log anonymization is balancing privacy protection with the retention of sufficient structure for meaningful analysis. Overly aggressive anonymization can destroy contextual integrity, while weak techniques risk re-identificatio…

Sentry: Authenticating Machine Learning Artifacts on the Fly
Andrew Gan, Zahra Ghodsi
https://arxiv.org/abs/2510.00554 https://arxiv.org/pdf/2510.00554

Sentry: Authenticating Machine Learning Artifacts on the Fly
Machine learning systems increasingly rely on open-source artifacts such as datasets and models that are created or hosted by other parties. The reliance on external datasets and pre-trained models exposes the system to supply chain attacks where an artifact can be poisoned before it is delivered to the end-user. Such attacks are possible due to the lack of any authenticity verification in existing machine learning systems. Incorporating cryptographic solutions such as hashing and signing can m…