Award Abstract # 1716500
SaTC: CORE: Small: Collaborative: Exploiting Physical Properties in Wireless Networks for Implicit Authentication

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: THE TRUSTEES OF THE STEVENS INSTITUTE OF TECHNOLOGY
Initial Amendment Date: August 30, 2017
Latest Amendment Date: August 30, 2017
Award Number: 1716500
Award Instrument: Standard Grant
Program Manager: Phillip Regalia
pregalia@nsf.gov
 (703)292-2981
CNS
 Division Of Computer and Network Systems
CSE
 Direct For Computer & Info Scie & Enginr
Start Date: September 1, 2017
End Date: January 31, 2018 (Estimated)
Total Intended Award Amount: $339,950.00
Total Awarded Amount to Date: $339,950.00
Funds Obligated to Date: FY 2017 = $0.00
History of Investigator:
  • Yingying Chen (Principal Investigator)
    yingche@scarletmail.rutgers.edu
Recipient Sponsored Research Office: Stevens Institute of Technology
1 CASTLEPOINT ON HUDSON
HOBOKEN
NJ  US  07030
(201)216-8762
Sponsor Congressional District: 08
Primary Place of Performance: Stevens Institute of Technology
NJ  US  07030-5991
Primary Place of Performance
Congressional District:
08
Unique Entity Identifier (UEI): JJ6CN5Y5A2R5
Parent UEI:
NSF Program(s): Secure &Trustworthy Cyberspace
Primary Program Source: 01001718DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 025Z, 065Z, 7434, 7923, 9102
Program Element Code(s): 8060
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

The rapid development of information technology not only leads to great convenience in our daily lives, but also raises significant concerns in the field of security and privacy. Particularly, the authentication process, which serves as the first line of information security by verifying the identity of a person or device, has become increasingly critical. An unauthorized access could result in detrimental impact on both corporation and individual in both secrecy loss and privacy leakage. Unlike many existing studies on user/device authentication, which either employ specialized or expensive hardware that needs experts for installation and calibration or require users' active involvement, the emerging low-cost and unobtrusive authentication solution without the users' participation is particularly attractive to effectively complement conventional security approaches. Due to the rich wireless connectivity and unique signal characteristics in pervasive wireless environments, this project takes a different view point by exploiting unique physical properties in wireless networks to facilitate implicit authentication for both human and mobile devices. The proposed research could advance our knowledge in exploiting the physical layer information in wireless networks to capture unique physiological and behavioral characteristics from human during their daily activities. It could also enhance our understanding in developing deep learning techniques to authenticate people based on their activities in the physical environments. Additionally, the educational efforts include curriculum development, K-12 and undergraduate involvement, and underrepresented student engagement in research.

This project focuses on building a holistic framework that leverages fine-grained radio signals available from the commercial wireless networks to perform implicit user/device authentication. The proposed framework aims to advance the foundation of integrating fine-grained physical properties in wireless networks to enhance wireless security. The research reveals that the fine-grained signal properties in wireless networks are capable to capture unique physiological and behavioral characteristics from human in both stationary and mobile daily activities. The proposed framework develops smart segmentation on the wireless signals and extract unique features that enable the capability of distinguishing individual. It further develops deep learning techniques to authenticate people based on their daily activities in the physical environments. The authentication process does not require active user involvement nor require the user to wear any device. This project also develops efficient techniques to detect the presence of user spoofing and localize attackers to facilitate the employment of a broad array of defending strategies.

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