2 citations · 3 across the 5 of their papers we have counts for
5 papers
A Survey of Machine Learning Algorithms for Detecting Malware in IoT Firmware
Erik Larsen, Korey MacVittie, John Lilly
This work explores the use of machine learning techniques on an Internet-of-Things firmware dataset to detect malicious attempts to infect edge devices or subsequently corrupt an e…
Intrusion Detection: Machine Learning Baseline Calculations for Image Classification
Erik Larsen, Korey MacVittie, John Lilly
Cyber security can be enhanced through application of machine learning by recasting network attack data into an image format, then applying supervised computer vision and other mac…
Virus-MNIST: Machine Learning Baseline Calculations for Image Classification
Erik Larsen, Korey MacVittie, John Lilly
The Virus-MNIST data set is a collection of thumbnail images that is similar in style to the ubiquitous MNIST hand-written digits. These, however, are cast by reshaping possible ma…
A Survey of Machine Learning Algorithms for Detecting Ransomware Encryption Activity
Erik Larsen, David Noever, Korey MacVittie
A survey of machine learning techniques trained to detect ransomware is presented. This work builds upon the efforts of Taylor et al. in using sensor-based methods that utilize dat…
Overhead-MNIST: Machine Learning Baselines for Image Classification
Erik Larsen, David Noever, Korey MacVittie +1
Twenty-three machine learning algorithms were trained then scored to establish baseline comparison metrics and to select an image classification algorithm worthy of embedding into…