D
David Ellis Newton
Researcher at University of Salford
Publications - 3
Citations - 325
David Ellis Newton is an academic researcher from University of Salford. The author has contributed to research in topics: Malware & Ransomware. The author has an hindex of 3, co-authored 3 publications receiving 185 citations.
Papers
More filters
Journal ArticleDOI
Fuzzy Pattern Tree for Edge Malware Detection and Categorization in IoT
Enisieh Modiri Dovom,Amin Azmoodeh,Ali Dehghantanha,David Ellis Newton,Reza M. Parizi,Hadis Karimipour +5 more
TL;DR: This study transmute the programs’ OpCodes into a vector space and employ fuzzy and fast fuzzy pattern tree methods for malware detection and categorization, obtaining a high degree of accuracy during reasonable run-times especially for the fast fuzzypattern tree.
Journal ArticleDOI
DRTHIS: Deep ransomware threat hunting and intelligence system at the fog layer
Sajad Homayoun,Ali Dehghantanha,Marzieh Ahmadzadeh,Sattar Hashemi,Raouf Khayami,Kim-Kwang Raymond Choo,David Ellis Newton +6 more
TL;DR: The Deep Ransomware Threat Hunting and Intelligence System (DRTHIS), a deep learning system to distinguish ransomware from goodware and identify their families, uses Long Short-Term Memory and Convolutional Neural Network, two deep learning techniques, for classification using the softmax algorithm.
Journal ArticleDOI
An improved two-hidden-layer extreme learning machine for malware hunting
Amir Namavar Jahromi,Sattar Hashemi,Ali Dehghantanha,Kim-Kwang Raymond Choo,Hadis Karimipour,David Ellis Newton,Reza M. Parizi +6 more
TL;DR: A modified Two-hidden-layered Extreme Learning Machine (TELM) is built, which uses the dependency of malware sequence elements in addition to having the advantage of avoiding backpropagation when training neural networks, to speed up the training and detection steps of malware hunting.