Differential privacy (DP) is the state-of-the-art framework for formal privacy protection, but many available DP methods are designed primarily for estimation. On the other hand, in many scientific ...

Data privacy on edge devices has become a significant concern, given the widespread use of mobile phones. There is a potential risk of sensitive personal data being leaked through an insecure network ...

Advances in AI and big data analytics rely on data sharing, which can be impeded by privacy concerns. Most challenging in privacy protection is protection of data-in-use, since even encrypted data ...

As more personal data is collected and analyzed, there is a growing need for formal privacy protection. Differential privacy (DP) has arisen as the state-of-the-art method in privacy protection, but ...

Differential privacy (DP) has arisen as the state-of-the-art framework for formal privacy protection when analyzing sensitive data. However, the fundamentals of DP are still not well understood. There ...

The development and training of deep learning models have become increasingly costly and complex. Consequently, software engineers are adopting pre-trained models (PTMs) for their downstream ...

Many software applications incorporate third-party packages distributed by package registries. Guaranteeing package provenance – knowledge of authorship – along this supply chain is a necessary part ...

The goal of this project is to help software engineers incorporate the lessons learned from prior failures throughout the software development lifecycle. Since all engineered systems fail, one ...

Researchers at Purdue University have developed a simplified runway status light system to prevent runway incursion incidents. Currently, technologies to prevent these incidents are usually limited to ...

Bridge inspections are an expensive and time-consuming process, varying significantly with the bridge's style, height, width, and length. Inspections create interruptions that interfere with bridge ...

Computing systems face diverse and substantial cybersecurity threats. To mitigate these cybersecurity threats while developing software, engineers need to be competent in the skill of threat modeling.

Conflicts and errors are unavoidable disruptions in complex networks such as energy grids, supply chains, and collaborative decision support systems. We aim to design and implement real-time, AI-based ...