Jelena Mirkovic
University of Southern California, CA·Computer Science
Cyberattacks increasingly hit national infrastructure, government systems and research facilities. Yet defenders often work alone, with private data and facilities, and their defenses are soon outpaced by new threats.
- Fields
Computer Science
Engineering
Education Research
- Topics
cybersecurity
privacy
data sharing
- Grants
- 3 known grants, through Sep 2028
What they work on
- Build SPHERE, a shared research infrastructure with diverse hardware, configurable networks and safe network policies, for reproducible cybersecurity and privacy experiments on IoT, edge computing and programmable networks.
- Develop user portals and reproducibility support in SPHERE, working with artifact evaluation committees so researchers can repeat and build on each other's experiments.
- Create TEPPIT, a modular framework of reusable evaluation scenarios for assessing privacy-preserving data-sharing technologies, including vulnerability analysis and privacy-utility trade-off analysis.
- Provide TEPPIT users with trusted-computing machines, GPU servers, and embedded and IoT devices linked by emulated networks, to test privacy technologies under realistic conditions.
- Develop free, hands-on data science for cybersecurity exercises on SPHERE at three difficulty levels, plus group projects in which students analyze real system and network data.
More about the research
Organizations also need to share sensitive data without exposing personal information. However, it is hard to tell which privacy-protection methods work best, or how much privacy they really provide. The three projects here center on SPHERE (Security and Privacy Heterogeneous Environment for Reproducible Experimentation). SPHERE is a shared research infrastructure for cybersecurity and privacy (CS&P) experiments. One project builds SPHERE, one extends it into a testbed for privacy technology, and one uses it for teaching.
Why it matters
Shared, reproducible testbeds could help cybersecurity and privacy researchers build defenses that keep pace with attackers. A privacy testbed could help government, healthcare and finance organizations pick data-sharing protections that actually work, enabling safer collaboration on sensitive data. Free hands-on teaching materials could help train professionals to fill the large cybersecurity workforce shortage.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
PDaSP: Track 3: TEPPIT: TEstbed for Privacy-PreservIng Technologies for Data Sharing and Analysis
NSF · Oct 2025 – Sep 2028
Collaborative Research: Data Science for Cybersecurity
NSF · Aug 2025 – Jul 2028
Research Infrastructure: Mid-scale RI-1 (M1:IP): SPHERE - Security and Privacy Heterogeneous Environment for Reproducible Experimentation
NSF · Oct 2023 – Sep 2027
Closest labs
Hailu Xu
California State University-Long Beach, CA·Computer Science
Develop hands-on virtual exercises that teach students to collect, clean, correlate, store and analyze real system and network data in order to make informed cybersecurity decisions.
Ramesh Karri
New York University, NY·Computer Science
Build a web infrastructure of virtual playgrounds where researchers share data, code and tools for studying cyberattacks on smart manufacturing machines and networks.
Yixin Sun
University of Virginia, VA·Computer Science
Build an extensible model that automatically detects personally identifiable information in structured and semi-structured campus network logs, fine-tune it on historical logs, and turn it into a tunable service for live feeds and archives.
The school
University of Southern California: 47 labs on PI Pages, $1.3B a year on research, 882 research doctorates a year.
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