Data and AI Security
As organizations move to the hybrid cloud, they must protect sensitive data and comply with regulations that allow them to take advantage of AI. We’re designing systems to monitor and protect data, building trust in AI through robust evaluation, certification, and hardening against attacks.
Our work
Securing AI systems with adversarial robustness
Deep DiveResearchers develop defenses against deep learning hack attacks
ReleaseAI goes anonymous during training to boost privacy protection
ReleaseAdversarial Robustness Toolbox: One Year Later with v1.4
ReleaseIBM Differential Privacy Library: The single line of code that can protect your data
Release
Tools + code
ART: Adversarial Robustness Toolbox
A Python library for machine learning security that enables developers and researchers to defend and evaluate machine learning models and applications against the adversarial threats of evasion, poisoning, extraction, and inference.
View project →AI Privacy 360
Tools to support the assessment of privacy risks of AI-based solutions, and to help them adhere to any relevant privacy requirements. Tradeoffs between privacy, accuracy, and performance can be explored at different stages in the machine learning lifecycle.
View project →Diffprivlib: The IBM Differential Privacy Library
A general-purpose library for experimenting with, investigating, and developing applications in differential privacy.
View project →IBM Federated Learning - Community Edition
A Python framework for federated learning in an enterprise environment.
View project →HELayers – Community Edition
SDKs for computing on encrypted data without decrypting it, provided via Docker container. Equipped with C++ and Python API’s and includes Jupyter Notebooks and VS Code IDEs with demonstrations, tutorials and documentation for AI/ML and encrypted search applications. Support for Linux, Intel, MacOS and s390x platforms.
View project →
Publications
- 2022
- ACM CCS 2022
- 2022
- AMIA Annual Symposium 2022
- 2022
- MICRO 2022
- 2022
- MICRO 2022
- 2022
- ESORICS 2022
- 2022
- USENIX Security 2022
IBM Solution: IBM Cloud Pak for Data
Our research is regularly incorporated into new security features for IBM Cloud Pak for Data.