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Found 4 papers, 3 papers with code
Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT
As the internet continues to be populated with new devices and emerging technologies, the attack surface grows exponentially.
Privacy and Trust Redefined in Federated Machine Learning
A common privacy issue in traditional machine learning is that data needs to be disclosed for the training procedures.
A Distributed Trust Framework for Privacy-Preserving Machine Learning
Privacy-preserving techniques distribute computation in order to ensure that data remains in the control of the owner while learning takes place.
Phishing URL Detection Through Top-level Domain Analysis: A Descriptive Approach
Phishing is considered to be one of the most prevalent cyber-attacks because of its immense flexibility and alarmingly high success rate.
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