At its most recent General Assembly in Kiev, Ukraine, the International Federation for Information Processing (IFIP) elected Chancellor’s Professor of Computer Science Michael Franz to its inaugural cohort of 48 IFIP Fellows. The Fellow Award recognizes individuals of the highest professional standing and expertise in one of IFIP’s constituent societies (which includes ACM) who have also contributed directly to IFIP.

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At the most recent General Assembly of the International Federation for Information Processing (IFIP) in Kiev, Ukraine, the Fellows Selection Committee reviewed nominations and elected the inaugural cohort of IFIP Fellows. Included in this cohort is Distinguished Professor of Computer Science Gene Tsudik, elected in recognition of his professional standing and expertise as well as his contributions to IFIP through working groups and technical committees.

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Distinguished Professor of Computer Science Gene Tsudik received a grant from the Semiconductor Research Corp. (SRC) in the amount of $270,000 for a project titled: “Formally Verified Remote Attestation and Related Services for Low-End IoT Devices.” It is funded through the SRC’s Trustworthy and Secure Semiconductors and Systems (T3S) program. The project aims to develop a first-of-its-kind suite of formally verified basic security services for low-end embedded, Internet of Things (IoT), and cyber-physical system (CPS) devices. Such services include remote attestation, memory erasure, device reset, as well as software update and code execution. Proposed research will use “state-of-the-art automated formal verification tools” and will produce “detailed design specs for each service,” along with a functional prototype implementation of each service.

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Chancellor’s Professor Michael Franz and two of his former Post-Doctoral researchers were awarded a fundamental United States Patent (No. 10,430,265) that makes software diversity viable as a cyber-defensive technology. As the patent explains:

“Error report reporting errors that occur during software execution may be normalized to account for diversification of single software program. A method for useful providing error reports comprises receiving information regarding computer system status at a time of failure of proper execution of a diversified implementation of a computer program, the computer program having a plurality of diversified implementations; and transforming the information regarding the computer system status using metadata indicative of differences between the diversified implementation of the computer program and a canonical implementation of the computer program.”

Congratulations to Professor Franz and his co-authors.

Professor Michael Franz‘s 2009 paper “Optimization of Dynamic Languages Using Hierarchical Layering of Virtual Machines” was selected to receive the Most Notable Paper of DLS 2009 at this years edition of the Dynamic Languages Symposium, the main academic conference on dynamic programming language design and implementation.

As the jury writes, “we believe the last 10 years have shown this paper to be one of the early notable works on Meta VMs and Tracing.”

Congratulations to Professor Franz and his co-authors.

Assistant Professor of Computer Science Sang-Woo Jun recently received funding for two new projects, furthering his research into high-performance and high-efficiency systems. He was awarded $500,000 over three years from the National Science Foundation (NSF) for his grant, “MintCloud: An Elastic Multitenant FPGA Cloud.” The MintCloud project aims to design a cloud platform for elastic allocation of field-programmable gate array (FPGA) resources and implement a development and execution environment for distributed FPGA acceleration in such a cloud environment.

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Back in 1987, when David Aha was still a Ph.D. student in UCI’s Department of Computer Science, he had an idea. “My plan was to provide a location where datasets — and descriptions of them — could be shared with researchers studying supervised learning,” recalls Aha, now the director of the Navy Center for Applied Research in AI (NCARAI) at the Naval Research Laboratory. He started with a small number of datasets gathered by fellow Ph.D. student Jeff Schlimmer and then waited to publicize the repository until it had at least 25 datasets. “Once it caught on,” he says, “it became clear that the collection had to live on with the dedicated help of subsequent UCI student librarians, and they’ve been outstanding.”

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