Backdoor Defense with Machine Unlearning

no code implementations • 24 Jan 2022 • Yang Liu, Mingyuan Fan, Cen Chen, Ximeng Liu, Zhuo Ma, Li Wang, Jianfeng Ma

First, trigger pattern recovery is conducted to extract the trigger patterns infected by the victim model.

backdoor defense Machine Unlearning

Learn to Forget: Machine Unlearning via Neuron Masking

no code implementations • 24 Mar 2020 • Yang Liu, Zhuo Ma, Ximeng Liu, Jian Liu, Zhongyuan Jiang, Jianfeng Ma, Philip Yu, Kui Ren

To this end, machine unlearning becomes a popular research topic, which allows users to eliminate memorization of their private data from a trained machine learning model. In this paper, we propose the first uniform metric called for-getting rate to measure the effectiveness of a machine unlearning method.

BIG-bench Machine Learning Federated Learning +2

Revocable Federated Learning: A Benchmark of Federated Forest

no code implementations • 8 Nov 2019 • Yang Liu, Zhuo Ma, Ximeng Liu, Zhuzhu Wang, Siqi Ma, Ken Ren

A learning federation is composed of multiple participants who use the federated learning technique to collaboratively train a machine learning model without directly revealing the local data.

Federated Learning

A Combination Method for Android Malware Detection Based on Control Flow Graphs and Machine Learning Algorithms

no code implementations • journal 2019 • Zhuo Ma, Haoran Ge, Yang Liu, Meng Zhao, Jianfeng Ma

In this paper, we present a combination method for Android malware detection based on the machine learning algorithm.

Android Malware Detection BIG-bench Machine Learning +3