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Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:STEVENS INSTITUTE OF TECHNOLOGY (INC)
Doing Business As Name:Stevens Institute of Technology
PD/PI:
  • Yingying Chen
  • (732) 547-1247
  • yingche@scarletmail.rutgers.edu
Award Date:02/18/2010
Estimated Total Award Amount: $ 488,812
Funds Obligated to Date: $ 504,791
  • FY 2014=$104,321
  • FY 2012=$195,938
  • FY 2010=$96,702
  • FY 2011=$107,830
Start Date:03/01/2010
End Date:02/29/2016
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:CAREER: EASE: Enhancing the Security of Pervasive Wireless Networks by Exploiting Location
Federal Award ID Number:0954020
DUNS ID:064271570
Parent DUNS ID:064271570
Program:Secure &Trustworthy Cyberspace
Program Officer:
  • Ralph Wachter
  • (703) 292-8950
  • rwachter@nsf.gov

Awardee Location

Street:CASTLE POINT ON HUDSON
City:HOBOKEN
State:NJ
ZIP:07030-5991
County:Hoboken
Country:US
Awardee Cong. District:08

Primary Place of Performance

Organization Name:Stevens Institute of Technology
Street:CASTLE POINT ON HUDSON
City:HOBOKEN
State:NJ
ZIP:07030-5991
County:Hoboken
Country:US
Cong. District:08

Abstract at Time of Award

Wireless systems have become an inseparable part of our social fabric, which allow users to move around and access the services from different locations while on the move. However, wireless security is often cited as a major technical barrier that must be overcome before widespread adoption of mobile services can occur. Traditional approaches have focused on addressing security threats on a case-by-case basis in an ad-hoc manner as new and specialized threats are uncovered. Furthermore, as wireless networks become increasingly pervasive, the ubiquity of wireless is redefining security challenges (e.g., attacks can be conducted by new and rapidly evolving adversaries with little effort). This project aims to build location-oriented information into any wireless network stack and serve as a promising new dimension across different layers to complement conventional security solutions and enhance wireless security. A suite of location-enabled techniques are integrated into wireless network stacks as a true partner to cope with attacks and collaboratively defend against adversaries. The solutions are developed generic enough to apply across heterogeneous mixes of wireless technologies through the interaction with industry collaborators. Project results are expected to assist conventional security methods and advance our knowledge in exploring generic security approaches across a wide-range of wireless technologies, which will contribute significantly to the successful deployment and adoption of emerging wireless services. The project also strengthens the education and research of undergraduate and graduate students in related areas of wireless networks and security, and helps to prepare students to face the challenges of future information technology.

Publications Produced as a Result of this Research

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Yingying Chen, Jie Yang, Wade Trappe, Richard P. Martin "Detecting and Localizing Identity-Based Attacks inWireless and Sensor" IEEE Transactions on Vehicular Technology, v.59, 2010, p.2418.

Xiaoyan Li, Yingying Chen, Jie Yang, and Xiuyuan Zheng "Achieving Robust Wireless Localization Resilient to Signal Strength Attacks" Springer Wireless Networks (WiNET), v.18, 2012, p.45.

Yingying Chen, Hui Wang, Xiuyuan Zheng, Jie Yang "A Reinforcement Learning-Based Framework for Prediction of Near Likely Nodes in Data-Centric Mobile Wireless Networks" EURASIP Journal on Wireless Communications and Networking, v.2010, 2010, p..

Zhenhua Liu, Hongbo Liu, Wenyuan Xu, and Yingying Chen "Exploiting Jamming-Caused Neighbor Changes for Jammer Localization" IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), v.23, 2011, p.547.

Yingying Chen, Jie Yang, Wade Trappe, Richard P. Martin "Detecting and Localizing Identity-Based Attacks inWireless and Sensor Networks" IEEE Transactions on Vehicular Technology, v.59, 2010, p.2418.

Hongbo Liu, Jie Yang, Yan Wang, Yingying Chen, and C. E. Koksal, "Group Secret Key Generation via Received Signal Strength: Protocols, Achievable Rates, and Implementation" IEEE Transactions on Mobile Computing, v.13, 2014, p.2820.

Hongbo Liu, Zhenhua Liu, Yingying Chen, Wenyuan Xu "Determining the Position of a Jammer Using a Virtual-Force Iterative Approach," Springer Wireless Networks (Springer WiNET), the Journal of Mobile Communication, Computation and Information, v.16, 2010, p.1.

Jian Liu, Yan Wang, Gorkem Kar, Yingying Chen, Jie Yang, Marco Gruteser "Snooping Keystrokes with mm-level Audio Ranging on a Single Phone" the 21st Annual International Conference on Mobile Computing and Networking (ACM MobiCom), v., 2015, p..

Zhenhua Liu, Hongbo Liu, Wenyuan Xu, Yingying Chen "An Error Minimizing Framework for Localizing Jammers in Wireless Networks" IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), v.25, 2014, p.508.

Hongbo Liu, Hui Wang, Yingying Chen, and Dayong Jia "Defending against Frequency-Based Attacks on Distributed Data Storage in Wireless Networks" ACM Transactions on Sensor Networks, v.10, 2014, p.49:1.

Jie Yang, Yingying Chen, Wade Trappe, and Jerry Cheng "Detection and Localization of Multiple Spoofing Attackers in Wireless Networks" IEEE Transactions on Parallel and Distributed Systems (IEEE TPDS), v.24, 2013, p.44.

Chen Wang, Xiaonan Guo, Yan Wang, Yingying Chen, Bo Liu "Friend or Foe? Your Wearable Devices Reveal Your Personal PIN" the 11th ACM symposium on Information, Computer and Communications Security (ACM AsiaCCS), v., 2016, p..

Yingying Chen, Hui Wang, Xiuyuan Zheng, Jie Yang "A Reinforcement Learning-Based Framework for Prediction of Near Likely Nodes in Data-Centric Mobile Wireless Networks" EURASIP Journal on Wireless Communications and Networking, v., 2010, p..

Hongbo Liu, Zhenhua Liu, Yingying Chen, Wenyuan Xu "Determining the Position of a Jammer Using a Virtual-Force Iterative Approach" Springer Wireless Networks (WiNET), v.16, 2010, p.1.


Project Outcomes Report

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

This project takes an unique viewpoint of exploring the opportunities for cross-layer solutions that utilize the correlation information inherited from location across network stacks to collaboratively defend against security threats. The key insights of this project are: location should be integrated into any wireless network stack as a true partner to cope with attacks and effectively defend against adversaries, and security solutions that can leverage the knowledge provided by location across different network layers is promising to collaboratively enhance wireless security.

This project results in multiple publications centered around four main areas: (1) detecting attacks involving the claimed identity of a mobile device; (2) localizing attackers while coping with the localization infrastructure threats; and (3) utilizing the knowledge combined from lower layers, e.g., the detection of attacks and localization of adversaries, to provide attack resilient secure access to network resources by coping with access violations.

(1) Due to the shared nature of the wireless medium, attackers can gather useful identity information during passive monitoring and further utilize the identity information to launch identity-based attacks, in particular, the two most harmful but easy to launch attacks: spoo?ng attacks and sybil attacks. Identity-based attacks will have a serious impact to the normal operation of wireless and sensor networks. We take a different approach by using the physical properties associated with wireless transmissions to detect identity-based attacks, as well as localizing the adversaries in wireless and sensor networks. We formulate a generalized attack detection model using statistical signi?cance testing. We then provide theoretical analysis of exploiting the spatial correlation of Received Signal Strength (RSS) inherited from wireless nodes for attack detection.

(2) To ensure the availability of wireless networks, mechanisms are needed for the wireless networks to cope with jamming attacks. Most existing anti-jamming work does not consider the location information of radio interferers and jammers. However, this information can provide important insights for networks to manage its resource in different layers and to defend against radio interference. We examine two jamming models, region-based and signal-to-noise-ratio (SNR) based, to illustrate the underlying principles that govern the state of a node. We develop mechanisms to localize both single jammer as well as multiple jammers. The two main components in our framework, namely automatic network topology partitioner and intelligent multi-jammer localizer, work together to derive different categories of node clusters and achieve high localization accuracy even under overlapping jammed areas.

(3) The usage of wireless devices (e.g., PDAs, smartphones, and laptops) has become an inseparable part of our daily lives, which actively involves in information sharing and various data transactions in ways that previously were not possible. However, to ensure the successful deployment and adoption of these emerging applications, secure communication is crucial to support data transmission confidentiality, data integrity, and device authentication among multiple wireless devices. We examine secure group communication among multiple wireless devices by exploiting physical layer information of radio channel (e.g., Received Signal Strength and Channel State Information) instead of using the traditional cryptographic-based methods. The main advantage of the secret key generation utilizing physical layer information of radio channel is that it allows any two wireless devices within transmission range of each other to extract a shared symmetric cryptographic key while do not require a fixed infrastructure or a secure communication channel. To enable secure group communication, two proto...

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