Logic-Driven Cybersecurity: A Novel Framework for System Log Anomaly Detection using Answer Set ProgrammingPublished by apsathas on July 6, 2026July 6, 2026 Logic-Driven Cybersecurity: A Novel Framework for System Log Anomaly Detection using Answer Set Programming Li Fang, Zuo Fei, Gupta Gopal fang.li@oc.edu, fzuo@uco.edu, gopal.gupta@utdallas.edu 1views AIAI,Crisis and Risk Management,Cybersecurity and AI,Knowledge Acquisition and Representation Related Videos Leveraging AI for Enhanced Breast Cancer Detection: A Focus on Dimensionality Reduction and Imbalanced Learning Chaotic Explorers: Boosting Jaya’s Diversity to Escape Premature Convergence in Multimodal Optimization The Impact of AI Advancement on Software Development Labor Market: Empirical Evidence from the United States Context-Aware Embeddings of System Events via LLMs Towards Fine-Grained Threat Detection Health Alert Detection in Outdoor Environments Using Fog Computing, Embedded Machine Learning and Federated Learning with Model Poisoning Mitigation When Not to Trade: Hawkes Intensity Burst Detection for Regime-Aware Limit Order Book Prediction Structured Grounded Reasoning: Explainable AI over Contextual Knowledge Graphs Deep Learning-Based Ripeness Detection for Smart Refrigerators The strange case of XOR-CNF formulas: SAT Obfuscation and more Decision-Aware and Interpretable Machine Learning for Cardiovascular Risk Screening 12»Page 1 of 2 Categories:
