1 citations · 1 across the 2 of their papers we have counts for
3 papers
Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Information Security
Michael R. Smith, Nicholas T. Johnson, Joe B. Ingram +6
Despite the potential of Machine learning (ML) to learn the behavior of malware, detect novel malware samples, and significantly improve information security (InfoSec) we see few,…
Dynamic Analysis of Executables to Detect and Characterize Malware
Michael R. Smith, Joe B. Ingram, Christopher C. Lamb +4
It is needed to ensure the integrity of systems that process sensitive information and control many aspects of everyday life. We examine the use of machine learning algorithms to d…
A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines
Michael R. Smith, Aaron J. Hill, Kristofor D. Carlson +7
Information in neural networks is represented as weighted connections, or synapses, between neurons. This poses a problem as the primary computational bottleneck for neural network…