eigenfacex

parathyroidsanchovyAI and Robotics

Nov 17, 2013 (3 years and 8 months ago)

63 views

Privacy
-
Preserving Face
Recognition

Zekeriya

Erkin1, Martin Franz2, Jorge
Guajardo3,

Stefan Katzenbeisser2,
Inald

Lagendijk1,
and Tomas Toft4

Introduction

Alice

Bob

Owns a face image

Is neither willing to share the image
nor the detection result


Owns a face database

Is not willing to reveal his data


Run
face recognition
to determine


whether the face
image is in database



FIND

Paillier

cryptosystem


additively
homomorphic

public
-
key
encryption
schemes


[
a
+
b
] = [
a
][
b
],


[
ab
] = [
a
]
b
.

( b is a constant)

Face Recognition


Run Principal Component Analysis (PCA) from
a set of criminal images to obtain
eigenface


Projects
face images
onto
eigenfaces
.

Principal

Component Analysis (PCA)


Θ
1

2
, . . . , Θ
M

:
vectors
of length
N



average
of the training
images



covariance
matrix


Run PCA


To determine the face space, we select

K << M
eigenvectors
u
1
, . . . ,
u
K

that correspond
to the
K
largest eigenvalues.



criminal projection


Θ
1

2
, . . . , Θ
M

are projected onto the
subspace spanned by the
basis
u
1
, . . . ,
u
K

to
obtain their feature vector representation
Ω
1
, . . . , Ω
M
.

Suspect Projection


input image
Γ





Progection

in
the encrypted domain


input image

Calculating distances


Client’s

Calculating distances(
conti
)


Bob

Alice

Calculating distances



DEMO~

Paillier

cryptosystem


Two large prime number p, q


n

= p*q


Select random integer
g










Encryption


Decryption



Private key

Public key

Paillier

cryptosystem


Homomorphic

addition of
plaintexts



Homomorphic

multiplication of
plaintexts