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Intro

Conventional Paradigm: Supervised Learning

Key Challenge of Supervised Learning

Road Map

Background on Self-supervised Learning

Data Augmentation

Pre-training an Encoder - SimCLR [ICML'20]

Building a Downstream Classifier

Backdoor Attack

Key Idea of Our Attack

Quantifying Effectiveness Goal

Quantifying Condition I

Quantifying Utility Goal

Optimization Problem

Attack Setting

Attack Success Rate

Clean Accuracy and Backdoored Accuracy

Evaluation on Real-world Pre-trained Encoders

Existing Defenses are Insufficient

Summary

Motivation on Data Auditing

Auditing Unauthorized Data Use

Examples of Real-world Unauthorized Data Use

Our EncoderMI: Membership Inference based Data Auditing for Pre-trained Encoders

Revisiting Encoder Pre-training

Shadow Training Setup

Pre-training a Shadow Encoder

Constructing a Training Set for Inference Classifier

Building an Inference Classifier

Experimental Setup

Evaluation on CLIP

Conclusion

Description:

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore secure self-supervised learning in this Google TechTalk presented by Neil Gong as part of the Differential Privacy for ML series. Delve into the challenges of supervised learning and discover the potential of self-supervised learning techniques. Learn about data augmentation and pre-training encoders using methods like SimCLR. Examine backdoor attacks, their effectiveness, and strategies to quantify their impact. Investigate existing defenses and their limitations. Gain insights into data auditing techniques, including membership inference-based approaches for pre-trained encoders. Understand the process of shadow training and building inference classifiers. Evaluate the concepts presented through real-world examples and experimental setups, including an assessment of CLIP. Enhance your understanding of secure machine learning practices and their implications for privacy and data protection.

Secure Self-supervised Learning: Challenges and Solutions

Google TechTalks

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#Computer Science #Machine Learning #Self-supervised Learning #Information Security (InfoSec) #Cybersecurity #Privacy #Differential Privacy #Data Augmentation

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