34 citations · 40 across the 4 of their papers we have counts for
5 papers
MLDS: A Dataset for Weight-Space Analysis of Neural Networks
John Clemens
Neural networks are powerful models that solve a variety of complex real-world problems. However, the stochastic nature of training and large number of parameters in a typical neur…
Technical Report: A Toolkit for Runtime Detection of Userspace Implants
J. Aaron Pendergrass, Nathan Hull, John Clemens +5
This paper presents the Userspace Integrity Measurement Toolkit (USIM Toolkit), a set of integrity measurement collection tools capable of detecting advanced malware threats, such…
Learning Device Models with Recurrent Neural Networks
John Clemens
Recurrent neural networks (RNNs) are powerful constructs capable of modeling complex systems, up to and including Turing Machines. However, learning such complex models from finite…
Automatic Classification of Object Code Using Machine Learning
John Clemens
Recent research has repeatedly shown that machine learning techniques can be applied to either whole files or file fragments to classify them for analysis. We build upon these tech…
Maat: A Platform Service for Measurement and Attestation
J. Aaron Pendergrass, Sarah Helble, John Clemens +1
Software integrity measurement and attestation (M&A) are critical technologies for evaluating the trustworthiness of software platforms. To best support these technologies, next ge…