Daniel G. Saab - US grants

This research investigates the generation of manufacturing tests for highly sequential VLSI circuits. The approach is based on combining the best features of deterministic and simulation based techniques. Deterministic techniques are mainly used to (1) identify untestable and redundant faults and (2) to correct the direction of the simulation based search. Simulation based test vector generation examines a set of test vectors to determine a new test sequence to detect some faults. This process, while accurate and fast, generates longer than necessary test vectors. The technique being explored is detecting and correcting the genetic search, using deterministic ATPG. This process involves an intricate exploration of the power of a switch-level logic and fault simulator in an combination with a genetic algorithm and the deterministic ATPG during the test generation process. The technique is being applied to design problems such as, circuit partitioning, initial test set finding, and circuit initialization- structure to determine performance and quality of generated test sets.

This planning grant award will be used to study the feasibility of establishing a multi-university-industry Center for High-Assurance Secure Systems and Internet-of-Things (CHASSI) that will focus on areas where both security and high assurance are necessary to support operations of high mission criticality, due to safety or economic impact. Examples include medical devices, manufacturing, the energy grid, real-time financial markets, construction, and defense. Combining security and high-assurance is hard, however, intentionally combining them will lead to new models, techniques, designs, architectures, and systems that will be applicable across a range of important U.S. industries.

CHASSI has five sites: University of Kansas, University of Minnesota, Syracuse University, Case Western Reserve University (CWRU), and Indiana University. CHASSI research falls into four main thrusts: (1) Architectures, design and formal modeling for systems-level security, privacy, stability, and performance; (2) Secure communication, sensing, and devices; (3) Scalable trust and privacy; and (4) Human behavior for privacy and security. CWRU brings expertise in industrial controls, Internet-of-Things (IoT), Industrial Internet-of-Things (IIoT), and manufacturing and energy applications. Complementary expertise at the other sites includes mission assurance and systems security, assurance of medical devices, networking, cyber-physical systems, mobile security, and human factors.

CHASSI faculty members will gain an understanding of the specific interests and actual needs/barriers of industrial companies. Likewise, companies will benefit from exposure to: cutting-edge university research across all sites; networking with and learning best practices from other industry colleagues in and out of their sector; students who may be potential hires; and faculty that might perform center projects or proprietary research. During the planning period, CWRU will explore ways to advance diversity and outreach with the Women in Science and Engineering Roundtable (WISER) and Women in Technology initiatives through recruiting prospective students, educating current students, and identifying student researchers.

The collaborators from this multi-university-industry Center will host a single Center-wide repository at: http://chassi.ku.edu. This shared repository will include meeting materials, program information, publications, etc., and will be made available for a minimum of five years after the conclusion of the award or until the Center transitions to the next phase.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.