Our team of researchers from IBM Haifa and Dublin has developed software to help assess privacy risk of AI as well as reduce the amount of personal data in AI training. This software could be of use for fintech, healthcare, insurance, security – or any other industry relying on sensitive data for training.
IBM delivers first-of-its-kind security homomorphic encryption services offering for companies to begin experimenting with FHE.
Deep learning may have revolutionized AI – boosting progress in computer vision and natural language processing and impacting nearly every industry. But even deep learning isn’t immune to hacking.
In 2021, our hybrid cloud predictions show that we expect businesses to address challenges in ways that will apply new resources and strategies to drive business outcomes, in a world that will continue to require new advances in cloud and AI research.
IBM Research has initiated focused efforts called Code Risk Analyzer to bring security and compliance analytics to DevSecOps. Code Risk Analyzer is a new feature of IBM Cloud Continuous Delivery, a cloud service that helps provision toolchains, automate builds and tests, and control quality with analytics.
Your team has spent months developing, tuning and perfecting a complex deep neural network to classify important financial, medical or government data. The application has been containerized, packaged, and is finally ready to deploy as a public service on the cloud, but one thing stands in the way. How do you get assurance that your […]
This is our fifth and final blog post in a series for Women’s History Month 2020 focused on women innovating the future of IBM Research. The tremendous power of digital technology also introduces risk. If it’s hacked, or falls into the wrong hands, it can be used against us. That’s why security research is indispensable. The four women we meet here represent every aspect of it, from blockchain and open source defense to erecting cloud-based fortifications around digital crown jewels.
The promise of the Internet of Things: This integration should ideally map to a decentralized hardware and software platform.
A new release of the Adversarial Robustness Toolbox provides a method for defending against poisoning and "backdoor" attacks in machine learning models.
Recent years have seen tremendous advances in the development of artificial intelligence (AI). Modern AI systems achieve human-level performance on cognitive tasks such as recognizing objects in images, annotating videos, converting speech to text, or translating between different languages. Many of these breakthrough results are based on Deep Neural Networks (DNNs). DNNs are complex machine […]
“The prettiest thing I had ever seen” is not how IBM researcher Shai Halevi describes the beaches in Israel where he grew up. Or the sunset after a long day of hiking in Mitzpe Ramon desert. Rather, he saves these words to describe the first time he saw a cryptographic equation as an undergrad student. […]