Tootfinder

physics_collab: Multilayer physicist collaborations (2015)
Two multiplex networks of coauthorships among the Pierre Auger Collaboration of physicists (2010-2012) and among researchers who have posted preprints on arXiv.org (all papers up to May 2014). Layers represent different categories of publication, and an edge's weight indicates the number of reports written by the authors. These layers are one-mode projections from the underlying author-paper bipartite network.
This n…

Researchers at German cybersecurity company Security Research Labs discovered that a vast network of fake shops originating in China touting designer brands took money and personal details from 800,000 people in Europe and US.
Chinese network behind one of world’s ‘largest online scams’
https://www.theguardian.com/money/article/2024/may/08/chinese-network-behind-one-of-worlds-largest-online-scams

Combinational Nonuniform Timeslicing of Dynamic Networks
Seokweon Jung, DongHwa Shin, Hyeon Jeon, Jinwook Seo
https://arxiv.org/abs/2404.06021 https://

Combinational Nonuniform Timeslicing of Dynamic Networks
Dynamic networks represent the complex and evolving interrelationships between real-world entities. Given the scale and variability of these networks, finding an optimal slicing interval is essential for meaningful analysis. Nonuniform timeslicing, which adapts to density changes within the network, is drawing attention as a solution to this problem. In this research, we categorized existing algorithms into two domains -- data mining and visualization -- according to their approach to the probl…

TIM Red Team Research scopre un Bug di CSV Injection su Ericsson Network Manager (ENM)
https://poliverso.org/display/0477a01e-dbc7a77c-d77c63eea06823b8
TIM Red Team Research scopre un Bug di CSV Injection su Ericsson Network Manager (ENM) Nel contin…

This https://arxiv.org/abs/2307.12833 has been replaced.
link: https://scholar.google.com/scholar?q=a

When can networks be inferred from observed groups?
Collecting network data directly from network members can be challenging. One alternative involves inferring a network from observed groups, for example, inferring a network of scientific collaboration from researchers' observed paper authorships. In this paper, I explore when an unobserved undirected network of interest can accurately be inferred from observed groups. The analysis uses simulations to experimentally manipulate the structure of the unobserved network to be inferred, the number o…

A software engineer who transitioned into cybersecurity shares tips for success: Target specific cyber areas, obtain relevant certifications, have a robust and error-free resume, use LinkedIn for networking, be confident in interviews, thoroughly research the job and interviewers, and remain persistent. https://reddit.com/r/cybersecurity/comments/1bzz6xf/

PLLM-CS: Pre-trained Large Language Model (LLM) for Cyber Threat Detection in Satellite Networks
Mohammed Hassanin, Marwa Keshk, Sara Salim, Majid Alsubaie, Dharmendra Sharma
https://arxiv.org/abs/2405.05469

PLLM-CS: Pre-trained Large Language Model (LLM) for Cyber Threat Detection in Satellite Networks
Satellite networks are vital in facilitating communication services for various critical infrastructures. These networks can seamlessly integrate with a diverse array of systems. However, some of these systems are vulnerable due to the absence of effective intrusion detection systems, which can be attributed to limited research and the high costs associated with deploying, fine-tuning, monitoring, and responding to security breaches. To address these challenges, we propose a pretrained Large La…

Unifying Low Dimensional Observations in Deep Learning Through the Deep Linear Unconstrained Feature Model
Connall Garrod, Jonathan P. Keating
https://arxiv.org/abs/2404.06106

Unifying Low Dimensional Observations in Deep Learning Through the Deep Linear Unconstrained Feature Model
Modern deep neural networks have achieved high performance across various tasks. Recently, researchers have noted occurrences of low-dimensional structure in the weights, Hessian's, gradients, and feature vectors of these networks, spanning different datasets and architectures when trained to convergence. In this analysis, we theoretically demonstrate these observations arising, and show how they can be unified within a generalized unconstrained feature model that can be considered analytically…

CARNET, the Croatian Academic and Research Network, is leading the way to inclusive and digitally advanced educational landscape with transformative projects such as ATTEND, e-Universities, BrAIn, and CroQCI.
Read how the Croatian NREN is shaping the future of the country:

CARNET’s Cutting-Edge Projects: Empowering Education for all and building a Secure Communication Infrastructure | GÉANT CONNECT Online
Words by: Anja Korda, CARNET In the pursuit of an inclusive and digitally advanced education landscape, the Croatian Academic and Research Network - CARNET – is leading the way with transformative projects. ATTEND, e-Universities, BrAIn, and CroQCI demonstrate a commitment to innovation, accessibility, and the integration of emerging technologies. ATTEND – Bridging Gaps for Pupils

dom: Animal dominance archive (2022)
Animal dominance interaction data published over a century of research. The archive contains 434 agonistic interaction datasets, totaling over 241,000 interactions. A directed edge (i,j) corresponds to an antagonist interaction between i (winner) and j (loser). If a 'weight' edge property map exists, it counts the number of such interactions.
This network has 14 nodes and 54 edges.
Tags: Social, Animal, Weighted