Zero-knowledge proof is a powerful cryptographic primitive that has found various
applications in the real world. However, existing schemes with succinct proof size suffer from …

Deep learning techniques with neural networks are developing prominently in recent years
and have been deployed in numerous applications. Despite their great success, in many …

Federated machine learning (FL) allows to collectively train models on sensitive data as only
the clients' models and not their training data need to be shared. However, despite the …

Elections are an important corner stone of democratic processes. In addition to publishing
the final result (eg, the overall winner), elections typically publish the full tally consisting of all …

We propose a new doubly efficient interactive proof protocol for general arithmetic circuits.
The protocol generalizes the interactive proof for layered circuits proposed by Goldwasser …

Machine unlearning aims to remove points from the training dataset of a machine learning
model after training; for example when a user requests their data to be deleted. While many …

Zero knowledge Neural Networks draw increasing attention for guaranteeing computation
integrity and privacy of neural networks (NNs) based on zero-knowledge Succinct Non …

The recent advancements in deep learning have brought about significant changes in
various aspects of people's lives. Meanwhile, these rapid developments have raised …

We are witnessing the emergence of decentralized AI pipelines wherein different
organisations are involved in the different steps of the pipeline. In this paper, we introduce a …

Abstract Blockchain and Decentralized Applications (DApps) are increasingly important for
creating trust and transparency in data storage and computation. However, on-chain …