Search Results for author:
Found 17 papers, 3 papers with code
Optimizing Cyber Response Time on Temporal Active Directory Networks Using Decoys
We proposed a novel metric called response time, to measure the effectiveness of our decoy placement in temporal attack graphs.
Symmetry-Breaking Augmentations for Ad Hoc Teamwork
In many collaborative settings, artificial intelligence (AI) agents must be able to adapt to new teammates that use unknown or previously unobserved strategies.
Evolutionary Multi-Objective Diversity Optimization
Creating diverse sets of high quality solutions has become an important problem in recent years.
Catch Me if You Can: Effective Honeypot Placement in Dynamic AD Attack Graphs
To solve the dynamic graph problem, we re-design the mixed-integer programming formulation by combining m MIP (dyMIP(m)) instances to produce a near-optimal blocking plan.
METAL: Metamorphic Testing Framework for Analyzing Large-Language Model Qualities
Through the experiments conducted with three prominent LLMs, we have confirmed that the METAL framework effectively evaluates essential QAs on primary LLM tasks and reveals the quality risks in LLMs.
On the Financial Consequences of Simplified Battery Sizing Models without Considering Operational Details
In this paper, we compare the most common existing sizing methods in the literature with a battery sizing model that incorporates the practical operation of a battery, that is, receding horizon operation.
Modelling Irrational Behaviour of Residential End Users using Non-Stationary Gaussian Processes
Demand response (DR) plays a critical role in ensuring efficient electricity consumption and optimal use of network assets.
Evolving Reinforcement Learning Environment to Minimize Learner's Achievable Reward: An Application on Hardening Active Directory Systems
The defender picks a specific environment configuration.
Limited Query Graph Connectivity Test
Given a source s and a destination t, we aim to test s-t connectivity by identifying either a path (consisting of only On edges) or a cut (consisting of only Off edges).
Multi-Forgery Detection Challenge 2022: Push the Frontier of Unconstrained and Diverse Forgery Detection
In this paper, we present the solutions from the Top 3 teams, in order to boost the research work in the field of image forgery detection.
Defending Active Directory by Combining Neural Network based Dynamic Program and Evolutionary Diversity Optimisation
We show that the problem is #P-hard and, therefore, intractable to solve exactly.
Niching-based Evolutionary Diversity Optimization for the Traveling Salesperson Problem
In this work, we consider the problem of finding a set of tours to a traveling salesperson problem (TSP) instance maximizing diversity, while satisfying a given cost constraint.
Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs
The other assumes a small number of splitting nodes (nodes with multiple out-going edges).
Dependency Structure for News Document Summarization
In this work, we develop a neural network based model which leverages dependency parsing to capture cross-positional dependencies and grammatical structures.
CelebA-Spoof Challenge 2020 on Face Anti-Spoofing: Methods and Results
It is the largest face anti-spoofing dataset in terms of the numbers of the data and the subjects.
Analysis of Evolutionary Diversity Optimisation for Permutation Problems
This work contributes to this line of research with an investigation on evolutionary diversity optimization for three of the most well-studied permutation problems, namely the Traveling Salesperson Problem (TSP), both symmetric and asymmetric variants, and Quadratic Assignment Problem (QAP).
Multi-document Summarization via Deep Learning Techniques: A Survey
Multi-document summarization (MDS) is an effective tool for information aggregation that generates an informative and concise summary from a cluster of topic-related documents.
