Reaserch Projects

    Internet of Things

The Internet of things has wide applications in warehouse management, supply and logistics control, retail, transportation, manufacture, environment monitoring, and even our daily lives. From phones to smart phones, from electricity meters to smart meters, from cars to connected vehicles, new products have been developed with enhanced capabilities in data communications, sensing, and information exchange, thanks to rapid advance in embedded systems and sensor networks, which integrate miniaturized computing devices with the target objects. However, this approach of replacing old products with new designs can be expensive and sometimes inconvenient, which limits its scope of applicability in practice. Furthermore, the replacement takes time, during which the legacy products cannot benefit from the IoT applications.The goal of our research is to provide an alternative, convenient and non-intrusive approach that is capable of turning a vast number of existing objects in the world, without redesign, into semi-smart objects for some of the benefits promised by the IoT vision. We focus on low-cost methods that attach RFID tags to objects or place tags in the object's environment. By exploiting the rich information embedded in the physical-layer signals from tags, such as phase, amplitude, polarization, waveform, and coupling effect, we will be able to determine the objects' orientation, location, trajectory, spacing and oscillation, and to track their trajectory or even internal content, in support of IoT applications. Our research also covers security, devices and sensing, wireless communications, data and applications, as well as using IoT technologies to integrate people, computing and their environments.

  1. National Science Foundation (NeTS 1718708), PI, NeTS:Small:Collaborative Research: Low-cost, Convenient, Non-intrusive Methods for Enabling the Internet of Things, 07/15/2017-07/14/2020.
  2. Florida Center for Cybersecurity, PI, Anomity in Secure Tagged IoT Systems, 07/01/2018 – 12/31/2019.

Big Data

The objective is to develop algorithms/data structures/tools/applications for measuring and analyzing big data transferred over the Internet or other types of modern networks. (1) We develop virtualized bitmaps, sketches and vectors for extremely compact data structures that measure streaming data flows with less than 1 bit per flow, which enables big data processing by using commodity hardware. (2) We design hardware/software primitives that implement online network functions for routing, traffic measurement, packet scheduling, and quality of service at the line speed of core routers beyond terabits per second. In order to keep up with such high speed, one way is to implement online network functions using on-chip SRAM. However, fitting these network functions in fast but small on-chip memory represents a major technical challenge today. Our research efforts try to push the design of network functions to an unprecedented level of speed and compactness. The algorithms and statistical estimation approaches developed in the context of big network data are expected to have much wider scope of application for big data in other domains.

  1. National Science Foundation (NeTS 1719222), PI, NeTS:Small:Sketching Big Network Data, 07/15/2017-07/14/2020.
  2. National Institute of Health (2P30AG028740-11), Co-I, The UF Claude D. Pepper Older Americans Independence Center (OAIC) Renewal, 06/01/2017 - 03/31/2022.
  3. National Science Foundation (NeTS 1115548), PI, Making Online Network Functions Fast and Compact, 09/01/2011 – 08/31/2015.

Cybersecurity

This research thrust covers interdisciplinary research on cybersecurity in medical big-data systems, cloud computing systems, large-scale infrastructural RFID systems, and smart transportation systems. (1) For medical data security, we develop multi-staged matrix masking algorithms to provide full privacy protection of medical data for its entire lifecycle in an effort for free global exchange of masked medical data with full statistical utility and provable patient privacy. (2) For cloud security, we develop novel crypto structures and key management schemes that support integrity verification and guaranteed remote deletion of outsourced data, as well as privacy-preserving cloud computing. (3) For RFID security, we develop extremely light-weight ciphers and strongly-anonymous security protocols that expand the application scope of RFID tags into privacy-sensitive domains. (4) For cyber-physical system security, we develop one-time crypto tokens for anonymous toll payment and stochastic bitmap masking techniques for collecting sophisticated transportation traffic data without violating drivers' location privacy.

  1. Florida Center for Cybersecurity, Co-PI, Secure Multi-Agent Systems of Machine-to-Machine Communication, 07/01/2019 - 06/30/2020.
  2. National Science Foundation (STC 1562485), co-PI, TWC: Medium: Digital Healthcare-Associated Infection: Measurement, Defense and Prevention in a Modern Digital Healthcare Ecosystem, 06/01/2016-05/31/2020.
  3. National Institute of Health (R01GM118737), PI, New Statistical and Computing Technologies for Breaking the Barrier to Medical Data Sharing, 09/15/2017 - 09/14/2020.
  4. Florida Center for Cybersecurity, PI, Virtual Network/Wireless Labs for Cybersecurity Education and Training, 2018 – 2019.
  5. Florida Center for Cybersecurity, PI, Defensive and Resilient Cyberspace with Threat Tracking and Prediction based on Temporal-Spatial Network/Data Activity Profiling, 07/01/2017 – 12/31/2018.
  6. Florida Center for Cybersecurity, PI, New Technologies in Defense Maneuver against Distributed Denial-of-Service (DDoS) Attacks, 05/31/2016 – 12/31/2017.
  7. Florida Cybersecurity Center, PI, New Technologies for Network Defense Analysis based on Malware Behavior, 03/01/2015 – 04/30/2016.
  8. Cisco Systems Inc., PI, Dare you put your data in cloud? 09/01/2012 – 08/30/2013.
  9. Cisco Systems Inc., PI, Optimizing Access Control Lists, 09/01/2007 - 08/31/2008.

RFID Technologies

RFID (radio frequency identification) tags are becoming ubiquitously available in object tracking, access control, and toll payment. In the future, tags may be embedded in library books, passports, driver licenses, car plates, medical products, etc. They are an indispensable part in the vision of bringing everyday objects into cyberspace, and play critical roles in many practical cyber-physical systems. However, the current application model treats tags simply as ID carriers and deals with each tag individually for the purpose of identifying the object that the tag is attached to. The uniqueness of our research is to change the traditional individual view to a collective view that treats universally-deployed tags as a new infrastructure, a new wireless platform on which novel applications can be developed for large-scale automated warehouse management, inventory control, and even transportation traffic monitoring on the streets of a city. Such an RFID infrastructure can be further enhanced by integrating miniaturized sensors into tags for real-time information collection, by exploiting the mobility of tags, by supporting security functions, etc. These new developments will greatly expand not only the scope of applications but also the scope of fundamental research in RFID systems.

  1. National Science Foundation (CNS 1409797), PI, NeTS:Medium: New Technologies for Next-generation Infrastructural Tagged Systems, 08/01/2014 – 07/31/2018.

Intelligent Cyber-transportation Systems

The objective of this inter-disciplinary research is to develop new technologies to transform the streets of a city into a hybrid transportation/communication system, called the Intelligent Road (iRoad). First, with autonomous wireless devices co-locating with traffic signals, they form a wireless network that is designed to fuse real-time transportation data from all over the city to make a wide range of new applications possible. Our research attempts to build new capacities of quantitative bandwidth distribution, rate/delay assurance, and location-dependent security on a pervasive wireless platform through distributed queue management, adaptive rate control, and multi-layered trust. These new capacities lead to transformative changes in the way the transportation monitoring and control functions are designed and operated. Second, we try to integrate vehicles and the Intelligent Road into a cyber-transportation system that can self-monitor road conditions in order to improve both infrastructure performance and vehicle performance.

  1. U.S. Department of Transportation, Center for Multimodal Solutions for Congestion Mitigation (a U.S. DOT Tier 1 University Transportation Center grantee), Co-PI, Privacy Preserving Methods to Retrieve Origin-Destination Information from InteliDriveSM Vehicles, 4/1/2011 – 6/30/2013.
  2. National Science Foundation (CPS 0931969), PI, Transforming a City's Transportation Infrastructure through an Embedded Pervasive Communication Network, 09/01/2009 – 08/31/2013.
  3. University of Florida, Research Opportunity Fund Award, PI, Smart Street Network --- Transforming a City's Transportation Infrastructure into a High-Speed Communication Infrastructure, 05/01/2008 to 04/30/2010.
  4. National Science Foundation (NeTS 0721731), PI, New Technologies for Real-Time Wireless Mesh Networks with Transportation Applications, 09/01/2007 – 08/31/2009.

Wireless Networks

After WLAN's phenomenal commercial success, multihop wireless networks, including wireless sensor networks, wireless mesh networks, and mobile ad-hoc networks, are expected to lead in the next wave of deployment. From a user's perspective, not only do these networks enable ubiquitous communication, but also they should provide means to support diverse application requirements, particularly, the ability to differentiate various types of data flows and ensure quality of service. Our objective is to design distributed algorithms and network protocols to solve several fundamental problems in multihop wireless networks, including end-to-end weighted bandwidth allocation, bandwidth assurance, and performance/overhead tradeoff in traffic differentiation. The study covers a variety of network conditions, including single-commodity or multi-commodity flows, single-path or multi-path routing, and static or highly-dynamic wireless networks. We focus on light-weight approaches that do not maintain any per-flow state and are able to implement traffic differentiation under aggregate or weighted maxmin models, with great flexibility in adaptation based on network/traffic conditions. Wireless sensor networks, mesh networks, and mobile ad-hoc networks will provide a pervasive communication infrastructure for modern societies and dramatically change the way people interact with cyberspace and physical environment. Traffic-differentiation capability allows these networks to meet diverse application requirements, which will promote their entrance into the marketplace.

  1. National Science Foundation (NeTS 0644033), PI, CAREER: Traffic Differentiation in Multihop Wireless Networks, 05/01/2007 - 04/30/2012.
  2. Achiema Systems Inc., PI, A Global Overlay Service against Distributed Denial-of-Service Attacks, 200