Adapt

As companies collect consumer data in increasingly larger quantity and mine the data more deeply, trade-offs arise with respect to companies' practices about information privacy. A company may choose practices that augment targeted advertisements or services. However, the financial rewards associated with privacy practices are highly uncertain, since they are affected by a company's competition with rivals.

The ever-growing malware threats call for effective, yet efficient, mitigation techniques. Machine learning offers a promising solution to malware defense due to the scalability and automation that it brings. Machine learning techniques are however not a panacea for advanced malware attacks where cyber criminals can carefully craft malware features to evade detection. The root cause of such attacks can be attributed to the passive nature of existing machine learning-based malware defense systems.

The 2011 Federal Cybersecurity Research and Development Plan cites "Accelerating Transition to Practice (TTP)" as one of five strategic objectives in the Cyber Security and Information Assurance (CSIA) Program Component Area. TTP remains a strategic objective of Agencies which fund cybersecurity research, including NSF. However, the NSF cybersecurity portfolio contains only a small amount of security research that has been transitioned into operational activities.

This project addresses the need to train students, researchers, and practitioners on diverse hardware security and trust issues as well as emergent solutions. The primary goal is establishing a set of hardware security courseware and enabling adoption of these courseware through the development of an online Hardware Attack and Countermeasure Evaluation (HACE) Lab.

Today's software remains vulnerable to attack. Despite decades of advances in areas ranging from testing to static analysis and verification, all large real-world software is deployed with errors. Because this software is either written in or underpinned by unsafe languages, errors often translate to security vulnerabilities. Although techniques exist that could prevent or limit the risk of exploits, high performance overhead blocks their adoption, leaving today's systems open to attack.