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Found 4 papers, 1 papers with code
CloudShield: Real-time Anomaly Detection in the Cloud
Once an anomaly is detected, to reduce alert fatigue, CloudShield automatically distinguishes between benign programs, known attacks, and zero-day attacks, by examining the prediction error distributions.
Smartphone Impostor Detection with Behavioral Data Privacy and Minimalist Hardware Support
Impostors are attackers who take over a smartphone and gain access to the legitimate user's confidential and private information.
VerIDeep: Verifying Integrity of Deep Neural Networks through Sensitive-Sample Fingerprinting
Even small weight changes can be clearly reflected in the model outputs, and observed by the customer.
Privacy-preserving Machine Learning through Data Obfuscation
While it is prevalent to outsource model training and serving tasks in the cloud, it is important to protect the privacy of sensitive samples in the training dataset and prevent information leakage to untrusted third parties.
