What’s Next in Security
is intrinsic protection
Cloud and AI have revolutionized the way the world computes — but they come with new security threats. We’re using AI to build intelligent threat detection, investigation, and response capabilities across enterprise, cloud, and the edge. We’re helping clients migrate to quantum-safe cryptography to protect against future threats from quantum computers. We’re enabling enterprises to deploy and run applications on encrypted data. Our pioneering technologies in confidential computing, decentralized trust and a secure supply chain will enable more secure, zero-trust infrastructures for all.
- Quantum-Safe Cryptography and Migration
- Fully Homomorphic Encryption
- Confidential Computing
- Threat Management
Our work
Protection against data-oriented attacks through selective data integrity
Technical noteHans Liljestrand, Hani Jamjoom, Matthew Hicks, N. Asokan, Danfeng (Daphne) Yao, and Salman Ahmed- Security
- Security Analysis
Securing telecoms networks for the post-quantum era
NewsRay Harishankar and Lory Thorpe- Quantum
- Quantum Safe
An open-source toolkit for debugging AI models of all data types
Technical noteKevin Eykholt and Taesung Lee- Adversarial Robustness and Privacy
- AI Testing
- Data and AI Security
IBM and NASA open source the largest geospatial AI foundation model on Hugging Face
NewsKim Martineau- Accelerated Discovery
- AI
- Climate
- Distributed Systems
- Foundation Models
- Hybrid Cloud
- Open Source
- Scaling AI
Expanding the quantum-safe cryptography toolbox
NewsWard Beullens and Luca De Feo- Cryptography
- Quantum
- Quantum Safe
Simplifying cloud security policies with AI
Technical noteJulian Stephen and Shriti Priya- Cloud Security
- Data and AI Security
- Security
- See more of our work on Security
Publication collections
Tools + code
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 →Kestrel Threat Hunting Language
Kestrel threat hunting language provides an abstraction for threat hunters to focus on the high-value and composable threat hypothesis development instead of specific realization of hypothesis testing with heterogeneous data sources, threat intelligence, and public or proprietary analytics.
View project →Virtual TPM
Libtpms-based Trusted Platform Module (TPM) emulator with socket, character device, and Linux CUSE interface.
View project →Open Quantum Safe
An open-source project to support the development and prototyping of quantum-resistant cryptography.
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 →
IBM Security Solutions
Innovations from our Security Research teams are regularly developed into cutting-edge new capabilities for IBM’s Security offerings.