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Kim Laine

2 accepted papers

2020

Privacy-Preserving Phishing Web Page Classification Via Fully Homomorphic Encryption

ICASSP 2020accepted

This work introduces a fast and lightweight homomorphic-encryption pipeline that enables privacy-preserving machine learning for phishing web page recognition. The primary goals are to use visual features to train an accurate model and to implement an inference pipeline with practical runtime and co…

Cited by 0SourceScholar
2016

CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy

ICML 2016poster

Applying machine learning to a problem which involves medical, financial, or other types of sensitive data, not only requires accurate predictions but also careful attention to maintaining data privacy and security. Legal and ethical requirements may prevent the use of cloud-based machine learning s…

Cited by 2367SourcePDFScholar