Deter

The National Science Foundation funds over seven billion dollars of research annually, nearly all of which relies heavily on information technology. The digital data produced and computing systems used by that research are subject to the same risks as other data and computing systems on the Internet. Appropriate cybersecurity is necessary both to make today's scientific discoveries possible and to ensure that the science is trustworthy. However, NSF science is often necessarily performed in open, collaborative environments that span organizational and national boundaries.

The Center for Encrypted Functionalities (CORE) tackles the deep and far-reaching problem of general-purpose "program obfuscation," which aims to enhance cybersecurity by making an arbitrary computer program unintelligible while preserving its functionality.

Ensuring the cyber-security of the smart grid raises significant interest amongst both general public and researchers. However, the corresponding education programs fall behind in many aspects. Very limited curriculum or hands-on learning resources are available for security education about the smart grid, especially for the mutual impacts between cyber and physical systems.

Data provenance refers to the history of the contents of an object and its successive transformations. Knowledge of data provenance is beneficial to many ends, such as enhancing data trustworthiness, facilitating accountability, verifying compliance, aiding forensics, and enabling more effective access and usage controls. Provenance data minimally needs integrity assurance to realize these benefits.

When data is outsourced at a cloud storage provider, data owners lose control over the integrity of their data and must trust the storage provider unconditionally. Coupled with numerous data loss incidents, this prevents organizations from assessing the risk posed by outsourcing data to untrusted clouds, making cloud storage unsuitable for applications that require long-term security and reliability guarantees. This project establishes a practical remote data checking (RDC) framework as a mechanism to provide long-term integrity and reliability for remotely stored data.