Shelby Hall Research Forum Posters
Posters from 2026
Explainable Deep Reinforcement Learning for Real-Time Network Intrusion Detection, Sebastian Bustamante
Deconstructing Digital Disinformation: Social media Data Preparation and Analysis for Healthcare Research, Russell W. Cantrell and Matt Campbell
Evaluating Software-based Hardware Abstraction as a Fault Injection Countermeasure, Tristan Clark and J. Todd McDonald
Algorithm For Detecting LUKS2-Encrypted Containers In Forensic Images, Nicholas Flynn and Michael Black
A Framework for Adaptive Anomaly Detection in Industrial Control Systems, Barbara Gladney
Detecting Sensor Data Manipulation, Ricky Green and Michael Black
Cellebrite Reliability in Digital Forensics, Christina Huynh
Temporal Eclectic Rule Extraction: Exploring Trustworthy Explainable Artificial Intelligence for Recurrent Neural Networks, Micah Israel
Text Corpus Combined Method and Tools For Music Textual Analysis, Yuwei Lu
Evaluating the Effects of Anti-Forensic Activities in Additive Manufacturing Devices, Daniel B. Miller
Comparative Analysis of NIST-Approved Random Number Generators, Lindsay Nadobny and Michael Black
Improving Consensus in Blockchain, Nelson Navas
Stock Market Price Prediction Using Big Data Models Comparison Analysis, Vibhor Pal
Detecting Sophisticated Cyberattacks on Public Water Infrastructure, Ayrton Purdy
Brain Computer Interfaces: Enhancing Low-Cost EEG Performance through Deep, Anwar Rassoul
Machine Learning on the Edge: Performance and Security Evaluation of CNN Implementations in Embedded Systems, Krista Stacey
Integrating Nonlinear Phase Space Analysis and Image-Based Representation for Network Intrusion Detection, Chakriya Suon
Posters from 2025
Security Vulnerabilities of a Field Programmable Gate Array, Kylie Arnett
False Narratives, Real Consequences, Russell W. Cantrell and Matt Campbell
Application of Graph Neural Networks with Phase Space Graphs, Parker H. Cole, Ryan Benton, Ralf Riedel, and David Bourrie
A Framework for Design Recovery, Eric Diep
Development of an Algorithm to Identify the Presence of LUKS-Encrypted Volumes on a Forensic Image of a Drive, Nicholas Flynn and Michael Black
Learning Without Labels: A Self-Supervised Learning Approach for Anomaly Detection in Control Systmes, Barbara Gladney
Detecting Sensor Data Manipulation, Ricky Green and Michael Black
Out-of-band Anomaly Detection for Real Time Operating Systems, Jeff K. Holifield
Heterogenous Gross Device Deep Learning Power Analysis Attack, Berk Kivilcim
Using Machine Learning Models to Improve the Cyber Physical Security of Drones, Sean Lee and Aviv Segev
Topical Text Segmentation for Stream of Consciousness Writing, Yuwei Lu and Ryan Benton
Analysis of Forensic Techniques for Additive Manufacturing Devices, Daniel B. Miller, Brad Glisson, Mark Yampolskiy, and J Todd McDonald
Directing Sophisticated Cyberattacks on Public Water Infrastructure, Ayrton C. Purdy and Jordan Shropshire
Turbulence Prediction Using Non-Linear Phase Space Analysis, Jeremy Quijano
Preserving Privacy in Senior Care at Home Monitoring Systems, Sam Russel, Ryan Benton, Amy Campbell, and Scott Sittig
Establishing a Framework for Evaluating Machine Learning Performance and Security across Computational Ecosystems, Krista Stacey and Todd R. Andel
Polyglot File Detection for Forensics, Chase Stevens and Michael Black
Unified Adaptive Cross-Attention Multimodal Network, Mahesh Sunuwar
Using Image-Based Representation for Network Intrusion Detection, Chakriya Suon and J. Todd McDonald