I had the pleasure of representing Webacy (https://webacy.com/) and presenting at EthCC (https://ethcc.io/) for a second time, this year in Brussels, Belgium. The AI x crypto space has been super hot, so for this talk I focused on practical applications and techniques.

Watch the full video here:

https://ethcc.io/archive/Predicting-Risk-Leveraging-AI-to-Analyze-Smart-Contracts (https://ethcc.io/archive/Predicting-Risk-Leveraging-AI-to-Analyze-Smart-Contracts)

Here are additional notes from the talk:

The number of deployed smart contracts is growing steadily. More smart contracts = more potential for hacks. We face two major challenges: the (increasing) complexity of smart contracts, and the limitations of manual analysis. Enter AI/ML.

GNNs help model complex structures. Great paper here: https://ijcai.org/proceedings/2020/0454.pdf… (https://t.co/TD5I9rX4Dk)

softer intro here: https://distill.pub/2021/gnn-intro/

Transformers bring context-aware analysis. deep learning: https://nature.com/articles/s41598-023-47219-0… (https://t.co/IgKiCng3iS)

vulnerability detection with NLP: https://ieeexplore.ieee.org/document/10420108 (https://t.co/nVxwgN5sjg)

Federated Learning ensures data privacy while improving security. FL enabled by Smart Contracts: https://arxiv.org/pdf/2107.10243 (https://t.co/62uOUbWDYs)

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