Tootfinder

From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs
Alsharif Abuadbba, Chris Hicks, Kristen Moore, Vasilios Mavroudis, Burak Hasircioglu, Diksha Goel, Piers Jennings
https://arxiv.org/abs/2506.13434

From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs
Large Language Models (LLMs) are set to reshape cybersecurity by augmenting red and blue team operations. Red teams can exploit LLMs to plan attacks, craft phishing content, simulate adversaries, and generate exploit code. Conversely, blue teams may deploy them for threat intelligence synthesis, root cause analysis, and streamlined documentation. This dual capability introduces both transformative potential and serious risks. This position paper maps LLM applications across cybersecurity fram…

**Deadline Extended** (CFP: PAMLA 2025) Haunted Belonging: Memory, Erasure, and Identity in Diasporic Literatures
https://ift.tt/mVurDfg
updated: Tuesday, June 17, 2025 - 9:41amfull name / name of organization: Wenyuan Wang / Pacific…
via Input 4 RELCFP

A NICER view of the 1.4 solar-mass edge-on pulsar PSR J0614--3329
Lucien Mauviard, Sebastien Guillot, Tuomo Salmi, Devarshi Choudhury, Bas Dorsman, Denis Gonz\'alez-Caniulef, Mariska Hoogkamer, Daniela Huppenkothen, Christine Kazantsev, Yves Kini, Jean-Francois Olive, Pierre Stammler, Anna L. Watts, Melissa Mendes, Nathan Rutherford, Achim Schwenk, Isak Svensson, Slavko Bogdanov, Matthew Kerr, Paul S. Ray, Lucas Guillemot, Isma\"el Cognard, Gilles Theureau

A NICER view of the 1.4 solar-mass edge-on pulsar PSR J0614--3329
Four neutron star radius measurements have already been obtained by modeling the X-ray pulses of rotation-powered millisecond pulsars observed by the Neutron Star Interior Composition ExploreR (NICER). We report here the radius measurement of PSR J0614$-$3329 employing the same method with NICER and XMM-Newton data using Bayesian Inference. For all different models tested, including one with unrestricted inclination prior, we retrieve very similar non-antipodal hot regions geometries and radii.…

The Poisson-Dirichlet problem in domains with Ahlfors regular boundary
Ariel Barton, Svitlana Mayboroda, Alberto Pacati
https://arxiv.org/abs/2506.14639 ht…

The Poisson-Dirichlet problem in domains with Ahlfors regular boundary
We present an announcement of some recent results concerning well-posedness of the Poisson-Dirichlet problem with boundary data in Besov spaces with fractional smoothness. This is a far-reaching generalization as previously known theorems concerning well-posedness of the Poisson problem in such intermediate smoothness classes were mostly restricted to the context of Lipschitz domains and coefficients satisfying strong regularity assumptions.

From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs
Alsharif Abuadbba, Chris Hicks, Kristen Moore, Vasilios Mavroudis, Burak Hasircioglu, Diksha Goel, Piers Jennings
https://arxiv.org/abs/2506.13434

From Promise to Peril: Rethinking Cybersecurity Red and Blue Teaming in the Age of LLMs
Large Language Models (LLMs) are set to reshape cybersecurity by augmenting red and blue team operations. Red teams can exploit LLMs to plan attacks, craft phishing content, simulate adversaries, and generate exploit code. Conversely, blue teams may deploy them for threat intelligence synthesis, root cause analysis, and streamlined documentation. This dual capability introduces both transformative potential and serious risks. This position paper maps LLM applications across cybersecurity fram…

An Efficient Candidate-Free R-S Set Similarity Join Algorithm with the Filter-and-Verification Tree and MapReduce
Yuhong Feng, Fangcao Jian, Yixuan Cao, Xiaobin Jian, Jia Wang, Haiyue Feng, Chunyan Miao
https://arxiv.org/abs/2506.03893

An Efficient Candidate-Free R-S Set Similarity Join Algorithm with the Filter-and-Verification Tree and MapReduce
Given two different collections of sets, the exact set similarity R-S Join finds all set pairs with similarity no less than a given threshold, which has widespread applications. While existing algorithms accelerate large-scale R-S Joins using a two-stage filter-and-verification framework along with the parallel and distributed MapReduce framework, they suffer from excessive candidate set pairs, leading to significant I/O, data transfer, and verification overhead, and ultimately degrading the pe…

Enforcing tail calibration when training probabilistic forecast models
Jakob Benjamin Wessel, Maybritt Schillinger, Frank Kwasniok, Sam Allen
https://arxiv.org/abs/2506.13687

Enforcing tail calibration when training probabilistic forecast models
Probabilistic forecasts are typically obtained using state-of-the-art statistical and machine learning models, with model parameters estimated by optimizing a proper scoring rule over a set of training data. If the model class is not correctly specified, then the learned model will not necessarily issue forecasts that are calibrated. Calibrated forecasts allow users to appropriately balance risks in decision making, and it is particularly important that forecast models issue calibrated predicti…

"You are a software worker. And you are able to do your job in more or less good conditions only because you are standing on the shoulders of countless others. We are talking about the fact that if you have 20 days of holidays, if you only work 5 days a week, if you are able to take some days or weeks off after the birth of your child, it is because some others before you have sacrificed their lives so you can work in decent conditions."

grrrrr. Ich wollte nicht Zahlen ausprobieren und habe mich drumrum gestümpert.
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https://www.pastpuzzle.de

Quantifying Mix Network Privacy Erosion with Generative Models
Vasilios Mavroudis, Tariq Elahi
https://arxiv.org/abs/2506.08918 https://

Quantifying Mix Network Privacy Erosion with Generative Models
Modern mix networks improve over Tor and provide stronger privacy guarantees by robustly obfuscating metadata. As long as a message is routed through at least one honest mixnode, the privacy of the users involved is safeguarded. However, the complexity of the mixing mechanisms makes it difficult to estimate the cumulative privacy erosion occurring over time. This work uses a generative model trained on mixnet traffic to estimate the loss of privacy when users communicate persistently over a per…