Sensing Driver Phone Use to Reduce Driver Distraction.
Cell phone distractions have been a factor in high-profile accidents
and are associated with a large number of automobile accidents. This
project addresses the fundamental problem of distinguishing between a
driver and passenger using a mobile phone, which is the critical input
to enable numerous safety and interface enhancements for the driver
distraction problem. We are building a detection system that leverages
the existing car stereo infrastructure, e.g., the speakers and
Bluetooth network. Our solution seeks to address major challenges
including the complex multipath environment presented in the small
confided space inside a car, minimizing interference between the
speakers, and any sounds emitted should be unobtrusive to minimize
This project has received the Best Paper Award at the ACM
International Conference on Mobile Computing and Networking (MobiCom)
The Wall Street Journal,
MIT Technology Review,
Yahoo News, CSDN,
Mobile Healthcare Leveraging Smartphones.
Mobile phones have become
increasingly popular and gradually woven into our social lives.
Smartphones equipped with powerful embedded sensors (e.g.,
accelerometers, GPS, microphones, and etc.) can be used to monitor
multiple dimensions of human behaviors including physical, mental and
social behaviors of wellbeing. The collected sensing data can thus be
comprehensive enough to be mined not only for the understanding of
human behaviors or daily life activities but also for supporting a
broad range of mobile healthcare applications. We are designing a
smartphone based secure healthcare monitoring system which allows
users to be monitored for their mental, cognitive, and physical
well-being and hence facilitate early diagnosis of potential illnesses
and taking possible preventive measures. The communities extracted
from a mobile phone enabled social network in our system can also be
exploited for securing certain components of the system (e.g., coping
with clone attacks).
This project is partially funded by the National Science Foundation, PI: Yingying Chen.
Mobile Healthcare Information and Management Systems Society News,
Mobile Health in Stevens,
Fierce Mobile Healthcare,
Exploiting Location as a New Dimension to Assist Wireless Security.
As the increasingly pervasive wireless networks make it even easier to
conduct attacks for new and rapidly evolving adversaries, the ubiquity
of wireless is redefining security challenges. Thus, there is an
urgent need to seek security solutions that can defend against attacks
across the current heterogeneous mixes of wireless technologies.
Location will be the cornerstone of new wireless services as future
wireless services will support the access to resources and information
from anywhere at anytime, implying that people will request services
and information at different locations and at different times. In this
project, we exploit location as a powerful information source to
assist cryptographic-based methods to solve fundamental security
problems such as detecting identity-based attacks and providing
location-aware secure access of network resources.
This project is funded by the National Science Foundation, PI:
Utilizing Physical Layer Properties for Secret Key Extraction in Mobile Environments.
Information sharing and various data transactions on wireless devices have become an inseparable part of our daily lives. However, securing wireless communication remains challenging in dynamic mobile environments due to the shared nature of wireless medium and lacking of fixed key management infrastructures. Generating secret keys using physical layer information thus has drawn much attention to complement traditional cryptographic-based methods. This project is designing schemes of secret key generation among wireless devices using physical layer information of radio channel such as the Received Signal Strength (RSS) and the Channel State Information (CSI). We currently are focusing on exploring the fine-grained physical layer information (i.e., CSI) from multiple subcarriers of Orthogonal Frequency-Division Multiplexing (OFDM) to achieve higher secret bit generation rate and make the secret key extraction approaches (based on physical-layer characteristics) more practical.
SEMOIS: Secure Mobile
Information Sharing System.
This project aims to
build a secure mobile information sharing system (SEMOIS) that
supports secure and privacy-preserving real-time information sharing.
SEMOIS will have the ability to store secure data items with flexible
access control at insecure storage nodes and enables users to send
context-based messages with late-binding features. Specifically,
SEMOIS plans to achieve data confidentiality and privacy-preserving
through data encryption and encrypted search, and enable intentional
name based message dissemination without apriori knowledge of
recipients. Additionally, a set of smart learning methods will be
developed to extract short-term and long-term geo-social patterns from
multimodal sensing data collected by mobile devices for social
networking purposes, e.g., geo-social patterns are used to derive
hidden social communities.
This project is funded by the National Science Foundation, PI: Yingying Chen.
MILAN: Multi-Modal Passive
Intrusion Learning in Pervasive Wireless Environments.
This project seeks to
develop effective and scalable multi-modal passive intrusion learning
techniques that have the capability to detect and track device-free
moving objects in pervasive wireless environments through adaptive
learning. In contrast to traditional techniques, which require
pre-deployment of specialized hardware, and thus not easily deployed
for unscheduled tasks and may not be scalable, this project leads to
new insights into intrusion learning by mining on wireless
environmental data, as well as leading to new approaches to
device-free wireless localization, which can be used to assist a broad
array of applications, e.g., identification of people trapped in a
fire building during emergency evacuation.
This project is funded by the National Science Foundation, PI: Yingying Chen.
Securing Spectrum Usage in
Future Radio Systems.
of the lower-layer protocol stacks renders cognitive radios (CR) an
appealing solution to dynamic spectrum access (DSA). Its open nature
will increase the flexibility of spectrum utilization and promote
spectrally-efficient communication. Nevertheless, due to the exposure
of the protocol stacks to the public, CR platforms can become a
tempting target for adversaries or irresponsible secondary users. A
misuse of a CR can significantly compromise the benefits of DSA and
threaten the privileges of incumbent users. Therefore, having the
ability to enforce spectrum etiquettes is critical in future radio
systems. We are designing efficient mechanisms, and developing
effective frameworks that can both detect anomalous activities in
spectrum usage as well as localize adversaries without requiring
overhead on wireless devices.
This project is funded by the National Science Foundation,
PI: Yingying Chen.
Mobile apps, especially those location
based ones, are changing the way people work and live every day, and
many such apps have to deal with an indoor environment, e.g., shopping
malls and airports. In many such environments, the availability of
indoor location information can be used to help individuals
(directions, just-in-time coupons/promotions) and organizations
(passenger flow distribution in airports, customer shopping/movements' pattern in malls). All these apps would require a practical, robust
and efficient smartphone indoor localization solution. We are studying
a practical and energy efficient indoor localization solution
leveraging multiple sensing modalities enabled by
The increasing pervasiveness of wireless
technologies, combined with the limited number of unlicensed bands,
will continue to make the radio environment crowded, leading to
unintentional radio interference across devices with different
communication technologies that share the same spectrum. Meanwhile,
the emerging of software defined radios has enabled adversaries to
build intentional jammers to disrupt network communication with little
effort. To ensure the successful deployment of pervasive wireless
networks, we take the view point that it is crucial to localize
jammers, since the locations of jammers allow a better physical
arrangement of wireless devices that cause unintentional radio
interference, and enable a wide range of defense strategies for
combating malicious jamming attackers.