Search Results for author:
Found 7 papers, 5 papers with code
IoTGeM: Generalizable Models for Behaviour-Based IoT Attack Detection
In this paper we present an approach for modelling IoT network attacks that focuses on generalizability, yet also leads to better detection and performance.
Explainable Artificial Intelligence (XAI)
feature selection
+1
REFORMS: Reporting Standards for Machine Learning Based Science
Machine learning (ML) methods are proliferating in scientific research.
How to avoid machine learning pitfalls: a guide for academic researchers
This document outlines some of the common mistakes that occur when using machine learning, and what can be done to avoid them.
A Data-Driven Biophysical Computational Model of Parkinson's Disease based on Marmoset Monkeys
In this work we propose a new biophysical computational model of brain regions relevant to Parkinson's Disease based on local field potential data collected from the brain of marmoset monkeys.
Evolving Continuous Optimisers from Scratch
This work uses genetic programming to explore the space of continuous optimisers, with the goal of discovering novel ways of doing optimisation.
IoTDevID: A Behavior-Based Device Identification Method for the IoT
Device identification is one way to secure a network of IoT devices, whereby devices identified as suspicious can subsequently be isolated from a network.
Evolutionary Algorithms
However, this flexibility goes hand in hand with a cost: the tailoring of an EA's configuration and parameters, so as to provide robust performance for a given class of tasks, is often a complex and time-consuming process.
