Facial Biohashing Based Userdevice Physical Unclonable Function For Bring Your Own Device Security

• doi: 10.1109/ICCE.2018.8326074
• title: Facial biohashing based user-device physical unclonable function for bring your own device security
• publisher: IEEE
• isbn: 978-1-5386-3026-6
• issn: 2158-4001
• rank: 2480
• access_type: LOCKED
• content_type: Conferences
• abstract: Bring your own device (BYOD) is gaining popularity. Using multifarious personal devices in the workplace to perform work-related tasks brings new challenges to trust and privacy management. Existing authentication schemes usually target at user or device separately, while the BYOD system needs to ensure that only the authorized user with the trusted devices can be given access. This paper presents a novel biohashing based user-device physical unclonable function (UD PUF) to provide a bipartite authentication of both user and device for the BYOD system. Biometric features are extracted as user identity while PUF endows the device with an inseparable and unclonable “fingerprint”. Biohashing acts as an intermediary between these two incoherent macroscopic biometric and microscopic silicon entropy sources for security enhancement. The concept is demonstrated using a 64 × 64 image sensor PUF simulated in 180nm 3.3 V CMOS technology, and the ORL and yale databases of faces. Our preliminary experimental results showed that a genuine (user, device, challenge) combination exhibits a very low equal error rate of 0.032, and tampering of any elements of the tuple will cause the hamming distance between the “live” and enrolled templates to have nearly random distribution.
• article_number: 8326074
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8326074
• html_url: https://ieeexplore.ieee.org/document/8326074/
• abstract_url: https://ieeexplore.ieee.org/document/8326074/
• publication_title: 2018 IEEE International Conference on Consumer Electronics (ICCE)
• conference_location: Las Vegas, NV, USA
• conference_dates: 12-14 Jan. 2018
• publication_number: 8322492
• is_number: 8326045
• publication_year: 2018
• publication_date: 12-14 Jan. 2018
• start_page: 1
• end_page: 6
• citing_paper_count: 9
• citing_patent_count: 0
• download_count: 475
• insert_date: 20180329
• index_terms:
  • ieee_terms:
    • Feature extraction
    • Principal component analysis
    • CMOS image sensors
    • Authentication
    • Companies
    • Face recognition
  • dynamic_index_terms:
    • Physical Unclonable Functions
    • Bring Your
    • Fingerprint
    • Image Sensor
    • Camera Sensor
    • Hamming Distance
    • Personal Devices
    • Authentication Scheme
    • Biometric Characteristics
    • Biometric Features
    • Equal Error Rate
    • Random Variables
    • Linear Discriminant Analysis
    • Discriminant Function
    • Discriminant Function Analysis
    • Encryption
    • Ciphertext
    • Cost Savings
    • Face Recognition
    • Transformation Matrix
    • Transformation Matrices
    • Facial Features
    • Facial Characteristics
    • Face Images
    • Orthogonal Matrix
    • Orthonormal Matrix
    • Orthogonal Transformation
    • Orthogonal Matrices
    • Recognition Rate
    • Pre-defined Threshold
    • Verification Phase
    • Performance Verification
    • Gabor Filters
    • Random Projection
    • False Acceptance Rate
    • Face Database
• isbn_formats:
  • format: Print on Demand(PoD) ISBN, value: 978-1-5386-3026-6, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-5386-3025-9, isbnType: New-2005
• authors:
  • Author Name: Yue Zheng
    Affiliation: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
    Author URL: https://ieeexplore.ieee.org/author/37086051112
    ID: 37086051112
    Order: 1
    Author Affiliations:
    • School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
  • Author Name: Yuan Cao
    Affiliation: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
    Author URL: https://ieeexplore.ieee.org/author/37072459300
    ID: 37072459300
    Order: 2
    Author Affiliations:
    • School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
  • Author Name: Chip-Hong Chang
    Affiliation: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
    Author URL: https://ieeexplore.ieee.org/author/37276902700
    ID: 37276902700
    Order: 3
    Author Affiliations:
    • School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore

Image Sensor

• sensor_type: CMOS
• resolution: 64x64
• dynamic_range: Not explicitly stated
• pixel_size: Not explicitly stated
• dark_current: Not explicitly stated

Optical Data

• focal_length: Not explicitly stated
• aperture: Not explicitly stated
• field_of_view: Not explicitly stated
• distortion: Not explicitly stated

Performance Metrics

• frame_rate: Not explicitly stated
• signal_to_noise_ratio: Not explicitly stated
• sensitivity: Not explicitly stated
• shutter_speed: Not explicitly stated
• power_consumption: Not explicitly stated
• noise: Not explicitly stated

Applications & Benefits

• cell_imaging: Used for user-device pairing in biometric authentication and physical unclonable functions (PUFs).
• benefits: Higher security for BYOD regime; unique device identification.

Supporting Organizations

• supported_by: Singapore Ministry of Education AcRF Tier 1 Grant No. MOE 2014-T1-002-141 (RG186/14)

Manuscript Details

• publication_date: 12-14 Jan. 2018

Relevancy Score

• score: 8
• missing_fields:
  • dynamic_range
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • frame_rate
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption
  • noise

Processed JSON Filename

request_30267f71-a557-4852-854f-90309249ed3e-facial_biohashing_based_userdevice_physical_unclonable_function_for_bring_your_own_device_security.json