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Explores cybersecurity vulnerabilities, exploits, and attacks, including nation agent motivations, vulnerability types, exploit processes, and phishing tactics during crises.
Explores challenges and solutions for scalable and trustworthy learning in heterogeneous networks, emphasizing data heterogeneity, privacy, fairness, and robustness.
Explores the intersection of machine learning and privacy, discussing confidentiality, attacks, differential privacy, and trade-offs in federated learning.
Explores botnets, networks of compromised hosts controlled by a single entity, and defense strategies against them, highlighting the impact of malicious software.