Explores machine learning security, including model stealing, altering outputs, adversarial conditions, and privacy challenges, emphasizing the importance of addressing biases in machine learning models.
Explores the significance of anonymous communications in safeguarding privacy and security, covering challenges, applications, system design, and quantifying anonymity levels.