A METHOD FOR IMPLEMENTING
PRIVACY-PRESERVING SECURITY
SURVEILLLANCE BY APPLYING
CRYPTOGRAPHIC TECHNIQUES ON A
REAL-TIME EMBEDDED DSP
FRAMEWORK
Presented ByAnkur Chattopadhyay
CS591 PROJECT SPRING 2007
Background Of The Problem
• Today’s
surveillance
mechanism leads to
“privacy invasion”
• Legal
issues
in
restricted places such
as restrooms, private
households
• Over
the
years,
instances
of
unmonitored crime on
the rise.
“Eyes” Of A Camera
Always Watching You
Everywhere
Examples Of Existing Surveillance
Cameras
Surveillance
Cameras
Existing
Monitoring
The Present Issue To Deal With
• Current surveillance systems displace
crime, rather than stop it
- Employment of CCTV moving crime out
of the camera boundaries
• Areas under surveillance become crimefree while unmonitored zones become
targets for illegal activity
- Criminal acts committed in a private
location, such as a locker room or
restroom
Some Interesting Facts
• Instances of crime rising in schools
- Most students avoid school restrooms out
of fear
- Almost 2000 students physically attacked
each hour of the school day
• The Unfortunate Truth
- Existing surveillance technology lowering
privacy for the average person
- Simultaneously, pushing crime further out
of the view of the cameras
The Challenge Faced
• So, the question posed to surveillance
system designers:
How to apply technology in the right way
and at the right place to enhance security
while protecting fundamental privacy rights
of individuals?
• The answer to this question lies in the
technology of PrivacyCam
- Future model of surveillance camera with
privacy protection
PrivacyCam
Blackfin DSP Module
Integrated System:
PrivacyCam
Omnivision CMOS
Camera Module
PrivacyCam: The Technology
• Uses
privacy
through
cryptographic
obscuration (PICO) technique
• PICO on a tiny Blackfin DSP processor chip,
integrated with a small Omnivision CMOS
camera module
• Application runs on a real-time operating
system (uCLinux under Linux) within the
chip
• Application performs the necessary tasks for
privacy enhancement
- detection of the region to protect
- encryption of that region
System Level Design Of The
Technology Implementation
Capture image from the camera
Detect the region to protect (using face detection,
skin detection, motion detection or other methods)
Use encryption key, generate session key and store
the secured key, along with the protected region
information, as embedded within the image
Carry out encryption on the region to protect, and
pass on the encrypted data to the image
compression process pipeline
Detection Of Region Of Interest
• Background Subtraction Model
- Two separate image frames, background model
and a captured one, compared against each
other
- Compute per coefficient (pixel wise) difference
for each 8 x 8 DCT block
- Compare the obtained difference with a model
threshold value. If the majority of the coefficient
differences are greater than the threshold, we
encrypt (encode) that block, otherwise we don’t
encrypt that block (for my research I have used
JPEG image compression)
Overview of Secret Key Cryptography
• To transmit data securely over an insecure medium, two
parties agree on a key in which to encrypt data.
– This key is usually exchanged through public-key
cryptographic methods
• User A encrypts a block of data X with key W and sends
this data to user B.
• By using the same key W, user B decrypts the ciphertext Y
back into X
X
Z
Y
W
A
Insecure Medium
Y
Z-1
B
W
X
Fundamental Concept: Due to algorithm Z, it’s nearly impossible to
recover data X from ciphertext Y without key W. “Guessing” the key W
through exhaustive search is generally infeasible.
Outline Diagram Of Applied Algorithm
The AES Algorithm
• The Advanced Encryption Standard
(AES)
- powerful standard cipher, that operates by
performing a set of steps for a number of
iterations called rounds
- AES is a symmetric block cipher, and it’s
better efficiency and effectiveness in
handling data blocks (bytes) makes it an
automatic choice over the vulnerable DES
(Data Encryption Standard)
• For my research I used the Rijndael Block
Cipher
AES Outline Diagram
Rijndael Algorithm
•
Rijndael Block Cipher Algorithm
–Developed by Joan Daemen and
Vincent Rijmen (pronounced “Rhinedoll”)
–An extremely fast, state-of-the-art,
highly secure symmetric algorithm
–Allows only 128, 192, and 256-bit key
sizes
–Variable block length supported
– A block is the smallest data size the
algorithm will encrypt
Some sample images from our PrivacyCam
application while monitoring a private
household. Each frame with a changing
object is followed by an encrypted version.
Here the human face region has been
protected for hiding individual identity,
thereby enhancing privacy.
Uniqueness Of Our Technology
• Protects privacy - hides individual identity
- Encrypts the image-region to protect with
AES (Advanced Encryption Standard)
using an encryption key
• Enhances security against any possible
crime scenario
- Upon legal authorization, recovery of the
full original image possible
- Recovery process through decryption by
accessing the encryption key
Technology Features/Advantages
• Unlike other existing technologies
- PrivacyCam allows general surveillance to
continue, without disrupting the privacy of
an individual
• Compared to existing commercial privacyenhancing applications like Emmitall
- Provides better system stability and free
from the typical vulnerabilities of software
implementation
- Forms a network based ethereal webcam
sensor
Analysis Of Technology
• Low cost of embedded system hardware
makes technology affordable
• Smallness in size of system components
makes technology space-optimized
• Involves balanced DSP processors with
minimum CPU overhead and very fast
peripheral interfaces
• System provides embedded real-time
application with performance in the order
of microseconds
Target Application Areas
• As a general-purpose
security camera
- in public places
- In restricted areas like
restrooms, locker-rooms
to name a few
• As a special vigilance
camera
- in bathrooms of school
buildings
Locker Room
Rest Room
Application Areas
• As a surveillance
camera for monitoring
- old home centers for
elder care
- trouble-prone zones of
school/university
Elder Care Center
Examples of incidents of violence and trespassing at campus
Recommendations
• Need to test PrivacyCam in more realistic
conditions like restrooms and locker rooms
• Need to show more results of real-time
performance in testing conditions
• Potential research work in improving the
mechanism of detecting the privacy region
• Potential research work in trying out other
public-key block cipher techniques
• Need to build on the technology by
extending to audio & audio-video
surveillance
Conclusion
• Novel technology addressing the critical
issue of “privacy invasion” in an efficient
and cost-effective way in optimized space
• Strikes fine balance between privacy
protection and security enhancement
• Meets all the ideal requirements of today’s
surveillance
• Growing and significant market
• Our technology challenges existing
privacy-enhancing
applications
and
surveillance systems
References
• Ankur Chattopadhyay, T.E. Boult, Privacy Cam:
a Privacy Preserving Camera Using uCLinux on
the Blackfin DSP – IEEE CVPR Embedded
Computer Vision Workshop, 2007
• T.E. Boult, PICO: Privacy Through Invertible
Cryptographic Obscuration - IEEE Computer
Vision
for
Interactive
and
Intelligent
Environments, 2005
• Michael Hennerich, Linux on the Blackfin DSP
Architecture - Embedded Systems Conference
Silicon Valley 2006
• Marc Van Droogenbroeck, Partial Encryption of
Images for Real-time Applications - Fourth IEEE
Signal Processing Symposium, April 2004
References
• J.M. Rodriguez, W. Puech and A.G. Borsb, A
Selective Encryption for Heterogeneous Color
JPEG Images Based on VLC and AES Stream
Cipher - Third European Conference on Color in
Graphics, Imaging and Vision, June, 2006
• W. Puech, P. Meuel, J.C. Bajard and M.
Chaumont, Face Protection by Fast Selective
Encryption in a Video - IET,Crime Security
Conference June, 2006
• Andrew Senior, Sharath Pankanti, Arun
Hampapur, Lisa Brown, Ying-Li Tian, Ahmet
Ekin, Blinkering Surveillance: Enabling Video
Privacy through Computer Vision - IEEE
Security & Privacy, 2005