activity
20182021
most citedAn Adversarial Risk Analysis Framework for Cybersecurity

2 citations · 2 across the 3 of their papers we have counts for

collaborators

8 papers

stat.AP2021

Managing driving modes in automated driving systems

David Ríos Insua, William N. Caballero, Roi Naveiro

Current technologies are unable to produce massively deployable, fully autonomous vehicles that do not require human intervention. Such technological limitations are projected to p…

cs.CR2019

Insider threat modeling: An adversarial risk analysis approach

Chaitanya Joshi, David Rios Insua, Jesus Rios

Insider threats entail major security issues in geopolitics, cyber risk management and business organization. The game theoretic models proposed so far do not take into account som…

cs.CR2019

Protecting from Malware Obfuscation Attacks through Adversarial Risk Analysis

Alberto Redondo, David Rios Insua

Malware constitutes a major global risk affecting millions of users each year. Standard algorithms in detection systems perform insufficiently when dealing with malware passed thro…

cs.LG2019

Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs

Victor Gallego, David Rios Insua

A framework to boost the efficiency of Bayesian inference in probabilistic programs is introduced by embedding a sampler inside a variational posterior approximation. We call it th…

cs.CR20192 cited

An Adversarial Risk Analysis Framework for Cybersecurity

David Rios Insua, Aitor Couce Vieira, Jose Antonio Rubio +3

Cyber threats affect all kinds of organisations. Risk analysis is an essential methodology for cybersecurity as it allows organisations to deal with the cyber threats potentially a…

stat.ML2018

Stochastic Gradient MCMC with Repulsive Forces

Victor Gallego, David Rios Insua

We propose a unifying view of two different Bayesian inference algorithms, Stochastic Gradient Markov Chain Monte Carlo (SG-MCMC) and Stein Variational Gradient Descent (SVGD), lea…