The wide range of research in InspiringGroup can be unified as data-centric systems and applications, where we strive to build next-generation infrastructures and data applications. We have published papers in top-tier venues and journals, covering Privacy Computing, Accountable and Trust AI, Internet Architecture, Blockchain Infrastructure, Datacenter Networking, Advanced Persistent Threat, Machine Learning Systems, etc. See our Publications for more detail.
AI/ML is the most important data-driven application. In our team, we focus on solving some of the biggest open-problems in AI security and safety, including
The certified robustness of various AI systems: we’ve worked on understanding the fundementals of AI safety and security in open-world and adversarial deployment.
Data security and privacy in AI training, inference and model-service: we’ve worked on various techniques (such as privacy-preserving machine learning, federated learning, ZKP) to ensure data security and privacy in AI.
Intelligent Network DataPlane (INDP): Our team is the world leader in embracing the flexibility of programmable dataplane (e.g., programmable switches, SmartNICs, and host networking) to execute application-desired and data-driven traffic shaping/analysis logic, while imposing negligible overhead on the network data plane.
Evolving the control-plane, data-plane, and management-plane for production-grade datacenter and WAN networks to enable various high-performance workloads, such as LLM training across large-scale data centers.
Blockchain is the fundamental infrastructure of the next-generation trust-based Web (the so-called Web3.0). Web3.0 is often cited to shape every aspect of our lives:
Build transparent and trustworthy computing and ground-breaking Web3.0/Metaverse applications, such as transforming the legal sector via smart contract.
Build security and trust systems to empower Internet architectural initiatives, such as verifiable routing and IP network.
Privacy Computing: we worked on various privacy computing techniques, including Federated Learning, Data Space, Secure Multi-party Computation, Secure Enclaves (i.e., trusted execution environments), Zero-knowledge Proofs, and Differential Privacy systems.
AI-Driven Network Traffic Analysis: networking security heavily depends on the insights into encrypted traffic. Our team built various algorithms and systems to enable accurate analysis.
Secure Inter-domain Routing: our team is leading in building a secure inter-domain routing protocol for the Internet.
The following are prior projects that have shown substantial impacts on either academia or industry or both.
Readily deployable and proactive DDoS prevention systems: CCS’16, ToN’18, TIFS’18, U.S. National NSF I-Corps Award.
Privacy Preserving access control for Tor Networks: ICNP’17. Acknowledge by the Tor Project and Cloudflare Inc.
Internet Source and Path Authentication: IWQoS’18.
World’s first production-grade SDN control-plane: NDSI’21 (Special acknowledgement), Google Feats of Engineering Award for High Network Availability.
World’s first production-grade automated management plane: leading author and under review, Google Feats of Engineering Award for WAN Capacity Augment.
Managing multi-tenancy and routing control in public Cloud: INFOCOM’18, TPDS’19, TPDS’21, One U.S. Patent, Product adoption by NEC, Acknowledgement by Huawei and Google.
Pioneering work in Blockchain Interoperability and Web3.0 definitions: CCS’19, TDSC’21, Invited Talks @ IEEE Blockchain Standards, Ant Group, IC3, etc.
Blockchain-empowered application innovations: IEEE Network’20, ICDCS’19.
Vulnerability discovery for large-scale RPC systems: ASIACCS’21, Adoption by Ant Group.
Advanced Persistent Threat: CCS’19.
Searchable Symmetric Encryption: TIFS’20.
Over the past few years, we have also worked on projects involving Programming Languages, High-perfomance Storage Systems, Database Systems, etc. We are extremely excited about interdisciplinary research because that is where creativity and disruptive initiatives come from.