Pablo Moriano Staff Scientist | AI | ML | Cybersecurity Contact 865.341.2768 | MORIANO@ORNL.GOV All Publications Adaptive Anomaly Detection for Identifying Attacks in Cyber-Physical Systems: A Systematic Literature Review A traffic accident dataset for Chattanooga, Tennessee Spatiotemporal features of traffic help reduce automatic accident detection time A comprehensive guide to CAN IDS data and introduction of the ROAD dataset Robustness of community structure under edge addition CANShield: Deep Learning-Based Intrusion Detection Framework for Controller Area Networks at the Signal-Level DEVELOPING AND DEPLOYING SECURITY APPLICATIONS FOR IN-VEHICLE NETWORKS... Graph-based machine learning improves just-in-time defect prediction CANShield: Signal-based Intrusion Detection for Controller Area Networks Detecting CAN Masquerade Attacks with Signal Clustering Similarity Using bursty announcements for detecting BGP routing anomalies Time-Based CAN Intrusion Detection Benchmark On the Robustness of Network Community Structure Under Addition of Edges Lessons Learnt from Comparing WhatsApp Privacy Concerns Across Saudi and Indian Populations Key Links Curriculum Vitae Google Scholar Web of Science ORCID LinkedIn IMPACT@ORNL GitHub Personal Website ResearchGate DBLP Organizations Computing and Computational Sciences Directorate Computer Science and Mathematics Division Mathematics in Computation Section Systems and Decision Sciences Group
