Security and privacy for data-intensive computing


Threats on conventional computing systems create a serious vulnerability for the pertinent programs, applications, and data. With the recent trends to extend the boundary of the Internet to include a wide spectrum of nonconventional computing devices, a.k.a., the Internet-of-Things (IoT), as well as emergence of intelligent vehicles and grids, the attack domain is being further expanded to the physical world. The typical design objective for these systems is performance optimization while meeting the real-world/physical resources and constraints. Adding security to the device's in the constrained settings is a challenge. In this regard, the ACES lab researchers are actively involved with establishing practical algorithms and frameworks:


IoT security Scalable privacy-preserving computing Trust-Hub



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