Int
ern
at
i
onal
Journ
al of Ele
ctrical
an
d
Co
mput
er
En
gin
eeri
ng
(IJ
E
C
E)
Vo
l.
9
, No
.
5
,
Octo
ber
201
9
, pp.
4266
~4
276
IS
S
N: 20
88
-
8708
,
DOI: 10
.11
591/
ijece
.
v9
i
5
.
pp4266
-
42
76
4266
Journ
al h
om
e
page
:
http:
//
ia
es
core
.c
om/
journa
ls
/i
ndex.
ph
p/IJECE
Impl
emen
tatio
n
of AES us
ing biom
etr
i
c
Srividy
a R
1
,
Ramesh
B
2
1
Depa
rtment of
Te
l
ec
om
m
unic
ation
Eng
ine
er
ing,
K.S.
Inst
it
ut
e
of
Technol
og
y
,
In
dia
2
Depa
rtment of
Com
pute
r
Scie
n
ce
and Engi
ne
ering,
Maln
ad
Co
llege
of
Eng
ine
e
ri
ng
,
Indi
a
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
Des
4
, 2
01
8
Re
vised
A
pr
2
5
, 2
01
9
Accepte
d
Ma
y
4
, 2
01
9
Mobile
Adhoc
net
work
is
the
m
ost
adva
nce
d
emergi
ng
te
chn
olog
y
in
th
e
fie
ld
of
wire
l
e
ss
com
m
unic
at
i
on.
MA
NETs
m
ai
nl
y
hav
e
th
e
ca
pa
cit
y
of
self
-
form
ing,
self
-
healing,
enabling
pe
er
to
p
e
er
comm
unic
at
i
on
bet
wee
n
the
nod
es,
witho
ut
re
l
y
ing
on
an
y
ce
n
tra
l
ized
ne
t
work
arc
h
i
tectur
e.
MA
NETs
are
m
ade
appl
i
c
abl
e
m
ai
nl
y
to
m
il
it
ar
y
applic
ations,
resc
ue
ope
rat
ions
and
hom
e
net
workin
g.
Prac
t
ically
,
MA
NET
coul
d
be
attac
k
ed
b
y
seve
ral
wa
y
s
using
m
ult
ipl
e
m
et
hods.
Resea
r
ch
on
MA
NET
emphasize
s
on
dat
a
se
cur
i
t
y
issues,
as
the
Adhoc
net
work
d
oes
not
bef
it
se
cur
ity
m
ec
h
ani
s
m
associa
te
d
with
stat
i
c
net
w
orks.
Thi
s
pape
r
foc
uses
m
ai
nl
y
on
dat
a
se
cur
ity
te
chni
qu
e
s
inc
orpora
te
d
in
MA
NET.
Also
thi
s
pape
r
proposes
an
implem
ent
a
ti
on
of
Advanc
ed
Encr
y
pt
ion
Stand
a
rd
using
bio
m
et
ric
k
e
y
fo
r
MA
NETs.
AES
implementa
ti
on
inc
lud
es,
t
he
design
o
f
m
ost
robust
Subs
ti
tut
ion
-
Bo
x
implementa
t
ion
which
d
efi
n
es
a
non
li
ne
a
r
beha
v
ior
an
d
m
it
igates
m
al
ic
ious
atta
ck
s,
with
an
exten
ded
sec
uri
t
y
d
ef
ini
ti
on
.
Th
e
ke
y
for
AES
is
gene
ra
te
d
using
m
ost
rel
ia
ble,
robust
and
pre
ci
se
biometr
ic
proc
essing.
In
thi
s
p
ape
r
,
th
e
inpu
t
m
essage
is
en
cr
y
pt
ed
b
y
AES
po
were
d
b
y
sec
ure
d
nonli
ne
ar
S
-
box
using
finge
r
p
ri
nt
biometric
fe
a
ture
and
is
de
cr
y
pt
ed
using
the
r
eve
rse
proc
ess.
Ke
yw
or
d
s
:
AES
Bi
om
e
tric
MANET
Mi
nu
ti
ae
ext
ra
ct
ion
S
-
Bo
x
Copyright
©
201
9
Instit
ut
e
o
f Ad
vanc
ed
Engi
n
ee
r
ing
and
S
cienc
e
.
Al
l
rights re
serv
ed
.
Corres
pond
in
g
Aut
h
or
:
Sr
ivi
dya R
,
Dep
a
rtm
ent o
f Te
le
com
m
un
icati
on
E
nginee
ring,
K.
S
. Instit
ute
of Tec
hnology
,
#14, Ra
gh
uv
a
na
halli
, K
a
na
ka
pura
m
ai
n
ro
a
d, Ba
ngal
ore
-
109
, I
nd
ia
.
Em
a
il
: srividya.ram
ise
t
ty
@g
m
ai
l.co
m
1.
INTROD
U
CTION
MANET
is
a
wireless
Adh
oc
Netw
ork
wh
i
ch
is
dy
nam
ic
in
natu
re.
It
ha
s
the
capa
bili
ty
to
transm
it
sign
al
s
i
n
between
m
ob
il
e
node
s.
Its
sel
f
-
c
onfig
ur
at
io
n
pr
op
e
rty
esse
ntial
ly
deals
with
dynam
ic
pr
ope
rty
of
m
ov
ing
no
des.
MANE
T
does
no
t
have
orga
nized
netw
ork
infr
a
struct
ur
e
i
n
or
der
t
o
est
ablish
c
omm
un
i
cat
io
n,
because
of
it
s
agili
ty
.
This
i
m
po
ses
lim
it
ation
s
on
netw
ork
in
fr
ast
ru
ct
ure,
data
sec
ur
it
y,
processin
g
abili
ty
,
thr
oughput
an
d
pe
rfo
rm
ance
of
the
syst
em
[1
]
.
Data
s
ecur
it
y
for
M
AN
E
T
is
to
be
de
sig
ned
ke
epi
ng
processi
ng
po
wer
a
nd
s
pee
d
into
c
onside
r
at
ion
.
He
nce
t
he
dep
l
oym
ent
en
vir
on
m
ent
def
i
nes
a
n
e
xtensiv
e
secur
it
y
at
th
e
cost
of
l
ow
proces
sin
g
pow
er
a
nd
at
high
data
rate.
M
A
NET
has
on
-
dem
and
nee
d
for
high
le
vel
secu
rity
syst
e
m
s
incorp
or
at
e
d
in
netw
ork
in
f
ra
struct
ur
e
.
T
he
li
te
ratur
e
stream
li
nes
wide
num
ber
of
secur
it
y sy
ste
m
s
ap
plica
ble to n
et
w
ork
syst
e
m
s.
Most po
pula
r
Crypt
ogra
ph
ic
syst
em
ill
us
trat
ed
in li
te
r
at
ur
e is
adv
a
nce
d
enc
r
ypti
on
syst
em
(A
E
S)
.
AES
is
disti
nguish
e
d
encr
y
ption
a
nd
decr
ypti
on
sy
stem
u
sed
wide
ly
in
vital
co
m
pu
te
r
network
i
ng
a
pp
li
cat
io
ns
.
K
ey
gen
erati
on
us
e
d
to
encr
y
pt
input
m
essage
is
again
a
ver
y
i
m
po
rtant
as
pe
ct
in
data
e
nc
r
ypti
on
/dec
rypti
on
syst
em
s.
Use
of
sym
m
et
ri
c
key
a
nd
asy
m
m
e
tric
key
r
e
m
ark
s
it
s o
w
n
m
erit
s an
d dem
erit
s in
sec
ur
i
ng d
at
a
and
data m
ob
il
it
y i
n
MANE
Ts.
Ma
in
m
otivatio
n
be
hind
data
secur
it
y
in
co
ntext
of
MA
N
ET
is
not
only
to
secu
re
data
at
hig
h
sp
ee
d,
bu
t
al
s
o
at
re
duced
pr
ocessin
g
powe
r.
He
nc
e
the
us
a
ge
of
key
ge
ner
at
io
n
is
li
m
i
te
d
to
i
m
ple
m
entat
i
on
of
sy
m
m
e
tric
key
g
ene
rati
on.
H
ow
e
ve
r
sy
m
m
et
ric
key
gen
e
r
at
ion
is
al
so
m
ade
com
plex
by
gen
erati
ng
th
e
key
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
Impleme
nta
ti
on
of AE
S usin
g bio
metri
c
(
Sr
i
vi
dya
R
)
4267
inco
rpor
at
in
g
bio
m
et
ric
inp
ut
[2
-
5].
S
ub
sti
tuti
on
-
Bo
x
(
S
-
Box)
is
i
m
plem
ented
in
va
riou
s
m
et
ho
ds.
The
m
os
t
widely
use
d
m
et
ho
d
is
L
ookup
ta
ble
m
eth
od.
I
n
l
ooku
p
ta
ble
m
et
h
od
the
ha
r
dw
a
r
e
desi
gn
co
unte
rp
a
rt
is
exp
e
ns
i
ve
in
t
erm
s
of
resou
rce
util
iz
at
ion
and
is
c
onsidere
d
s
wift
w
it
h
m
od
erate
secur
it
y.
Finit
e
fiel
d
arit
hm
etic
is
on
e
of
t
he
m
os
t
us
e
d
ap
proac
he
s
an
d
it
us
e
s
aff
ine
tra
ns
f
orm
at
ion
.
T
he
S
-
box
us
in
g
Fini
te
fiel
d
arit
hm
etic
has
high
desig
n
c
om
plexit
y.
It
no
t
on
ly
re
duces
com
pu
ta
ti
on
al
sp
ee
d
but
al
s
o
is
m
or
e
e
xp
e
nsi
ve,
com
par
ed
t
o
Lo
okup
ta
ble
m
e
tho
d
with
the
sam
e
secur
it
y
le
vel.
AES
im
ple
m
e
ntati
on
is
m
a
de
m
ore
vu
l
ner
a
ble
with
the
opti
m
izati
on
of
S
-
bo
x
[
6],
wh
ic
h
extend
s
the
secur
it
y
le
vel
in
m
ulti
ple
orders.
S
-
bo
x
desi
gn
optim
iz
at
ion
con
f
ronts
the
sec
ur
it
y
threats.
H
ow
e
ve
r
MAN
ET
syst
e
m
s
ca
n
be
m
ade
even
m
or
e
secur
e
with
th
e
inco
r
porati
on
of
e
nha
nced
featu
res.
Bi
om
et
ric
pr
oc
ess
ing
is
one
of
the
m
os
t
popul
ar
a
nd
extensi
v
el
y
use
d
te
ch
niques
in
the
desig
n
of
a
uth
e
ntica
ti
on
syst
em
s.
M
agn
it
ude
of
re
search
is
m
ade
in
the
resp
ect
ive
fiel
d
a
bout
the
sel
ect
ion
of
featu
res
s
uitable
f
or
processi
ng.
R
esearch
is
al
so
done
on
the
ty
pe
a
nd
m
et
ho
d
of
pro
cessi
ng,
w
hich
can
be
accom
plishe
d
in
ord
er
to
def
i
ne
au
thentic
at
ion.
I
r
is,
fin
gerpr
i
nt,
face,
DNA
an
d
palm
pr
int
recog
ni
ti
on
are
a
fe
w
of
the
feat
ur
e
s
avail
able
for
bio
m
et
ric
pr
oc
essing.
Fin
gerpr
i
nt
is
consi
der
e
d
a
s the m
os
t adora
bl
e and con
ven
i
ent appr
oac
h
t
o
the
context
of MA
NET
. V
a
r
io
us
tec
hniq
ue
s h
a
ve
been re
ported
i
n
li
te
ratu
re in p
ro
ces
sin
g
the
Bi
om
e
tric
f
eat
ur
e
ex
tract
i
on [7
-
15]
.
In
t
his
pa
per,
a
novel
m
et
ho
d
of
enc
ryption,
us
i
ng
Bi
om
et
ric
as
key
to
AE
S
is
pr
opos
e
d
a
nd
evaluate
d.
It
is
ex
pected
to
overc
om
e
the
li
m
it
a
ti
on
s
of
e
xist
ing
ci
phers
.
A
Bi
om
et
ric
base
d
a
uth
e
ntica
ti
on
te
chn
iq
ue
f
or
MANET
s
was
desc
ribe
d
i
n
l
it
eratur
e
[16].
This
pap
e
r
im
plem
ents
the
conve
ntion
al
de
sign
of
AES
,
a
nd
the
key
is
gen
e
rat
ed
us
in
g
t
he
bi
om
e
tric
featu
r
e.
Mi
nuti
ae
ex
tract
ion
is
inc
orp
or
at
ed
usi
ng
the
M
orpholo
gical
operati
onal
m
et
hod.
In
li
te
ratu
re
a
pap
e
r
im
ple
m
ents
bio
m
et
ric
processin
g
us
in
g
hyb
ri
d
encr
y
ption
te
c
hn
i
qu
e
s
[
17
]
.
The
pa
pe
r
al
so
il
lustrate
s
it
s
own
te
ch
nique
in
or
der
t
o
increa
se
the
secur
it
y
le
ve
l
in
com
m
un
i
cat
ion
netw
orks. It als
o discusse
s a
bout sym
m
et
ric
and asy
m
m
et
ri
c k
ey
gen
e
rati
on tech
niques
.
L
inear
be
hav
i
or
of
S
-
box
im
ple
m
entat
ion
,
w
hich
is
an
i
nteg
ral
f
unct
ion
al
m
od
ul
e
in
AES
enc
r
ypti
on
te
c
hniq
ue,
was
disc
usse
d
i
n
li
te
ratur
e
[
6].
This
pa
per
de
fines
great
er
secur
it
y
by
in
corp
or
at
in
g
n
on
li
nea
rity
in
the
im
ple
m
e
ntati
on
of S
-
B
ox.
In
th
e
pa
per
Mi
xed
Ra
nd
om
12
8
Bi
t
Ke
y
Usin
g
Fin
ge
r
Pr
i
nt
Feat
ure
s
and
Bi
nd
i
ng
Key
for
AES
Algorithm
[1
8]
,
Bi
om
e
tric
key
is
us
ed
in
order
to
e
ncr
y
pt
plain
te
xt
an
d
decr
y
pt
ci
ph
e
r
te
xt.
Finall
y
the
pap
e
r
exp
la
in
s
i
m
plem
entat
ion
of
AES
al
on
g
with
m
ixed
key.
The
m
inu
ti
ae
e
xtracti
on
he
re
is
accom
plished
us
i
ng
cro
ss
num
ber
a
ppr
oach.
The
a
uthor
s
of
the
pap
e
r,
Ge
ner
at
io
n
of
12
8
-
Bi
t
Bl
en
ded
Key
f
or
A
ES
Algorithm
[19
]
,
pro
posed
a
new
te
c
hn
i
qu
e
in
order
t
o
ge
ner
at
e
key
f
or
AES
e
ncr
y
ptio
n
an
d
dec
rypti
on
process
.
Th
is
pap
e
r
ta
kes
iris
as
bio
m
et
ric
featur
e
a
nd
a
rb
it
r
ary
key,
t
o
ge
ner
at
e
a
ble
nded
key.
The
pa
per
,
Mi
nuti
ae
Extra
ct
io
n
from
Fing
e
r
pr
int
Im
ages
-
a
Re
view
[7
]
,
str
ongly
re
com
m
end
s
im
a
ge
qual
it
y
of
fi
ng
e
r
pr
i
nt
w
hich
w
o
uld
es
sent
ia
ll
y
require
le
ss
pr
ocessin
g.
Mi
nuti
ae
extracti
on
on
i
m
ages
su
ch
as
bi
nar
y
and
gr
ey
scal
e
i
m
ages
at
ver
y
hig
he
r
glance is
d
isc
usse
d.
The
w
ork
on,
Gen
e
rati
on
of
Bi
om
e
tric
Key
fo
r
Use
in
DE
S
[20],
ex
plain
s
dev
el
op
m
ent
of
MA
NET
syst
e
m
s
us
ing
com
bi
nation
of
Crypto
grap
hi
c
syst
e
m
s
and
bio
m
et
ric
key
gen
e
rati
on.
Sy
m
m
e
tric
encr
ypti
on
te
chn
iq
ue
is
use
d,
w
hich
e
xclusiv
el
y
w
orks
on
non
bl
ock
s
iz
e
data.
Bi
o
m
et
ric
pr
oce
ssin
g
is
incorp
or
at
ed
i
n
order
t
o
gen
e
r
at
e
the
key
use
d
f
or
data
e
nc
ryptio
n.
How
ever
t
he
da
ta
e
ncr
y
ption
st
rategy
it
sel
f
has
a
lot
of
issues
in
te
rm
s
of
key
siz
e,
w
hich
is
not
s
uff
ic
ie
nt
to
sec
ur
e
data.
The
pa
pe
r,
Mi
nuti
ae
e
xtracti
on
sc
he
m
e
fo
r
fin
gerpr
i
nt
re
cogniti
on
syst
e
m
s
[11],
di
sti
nguish
es
both
global
a
nd
local
Bi
na
rizat
ion
te
c
hniq
ues.
It
su
m
m
arizes
that
glo
bal
Bi
nar
iz
at
ion
is
best
su
it
ed
f
or
gr
ey
scal
e
im
ages
ov
e
r
c
olor
i
m
ages
ba
sed
on
intensit
y i
ll
u
m
i
nation.
The
ne
ur
al
net
work
a
ppro
ac
h
is
us
e
d
f
or
m
inu
ti
ae
e
xtracti
on
w
hich
is
e
xclusi
vely
on
the
im
age
without
pr
e
processin
g.
Thi
s
pa
per
c
on
fron
ts
t
hat
im
age
pr
e
pro
cessi
ng
w
ou
l
d
res
ult
in
false
m
inu
ti
ae
extracti
on
.
T
he
pro
posed
te
c
hniqu
e
use
s
ser
ie
s
of
co
nvol
ution
operati
on
w
hich
re
sul
ts
in
increase
d
la
te
nc
y [21].
2.
RESEA
R
CH MET
HO
D
AES
is
im
ple
m
ented
us
in
g
Bi
om
et
ric
featur
e
f
or
va
riou
s
a
pp
li
cat
io
ns
.
AE
S
a
nd
Bi
om
et
ric
processi
ng
co
m
bin
at
ion
ens
ur
es
data
secu
rity
.
No
rm
al
ly
existi
ng
arc
hitec
tures
[
2
-
4
,
8]
work
e
d
on
var
i
ou
s
AES
a
nd
Bi
om
et
ric
co
m
bina
ti
on
im
ple
m
e
ntati
on
s
,
with
resp
ect
t
o
va
ri
ou
s
ap
plica
ti
on
s
incl
ud
i
ng
MANET
s.
Conve
ntion
al
AES
a
ppr
oach
is
us
ed
al
ong
with
m
or
phol
ogic
al
m
inu
ti
ae
extracti
on
sch
e
m
e
wh
ic
h
is
ba
sed
on
fu
zzy
lo
gic.
Mor
phol
og
ic
al
te
chn
i
qu
e
is
us
e
d
to
rem
ov
e
s
purs
an
d
no
ise
on
thi
nn
e
d
im
ages
us
i
ng
HIT
an
d
Mi
ss
transform
s,
as
these
t
ran
s
f
or
m
s
req
uire
com
plex
functi
ons
to
be
i
m
ple
m
ented.
This
m
or
phol
og
ic
al
op
e
rati
on h
as t
o
be per
f
or
m
ed
befor
e
pr
e
proc
essing
a
nd post
p
re
processi
ng.
I
t i
s
require
d
to b
e
rep
eat
e
d
twic
e
in
a
row,
the
re
by
increasi
ng
t
otal
com
pu
ta
tio
nal
ti
m
e.
I
m
p
lem
entat
ion
of
AES
usi
ng
m
ultim
od
al
biom
et
ric
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
9
, N
o.
5
,
Oct
ober
20
19
:
4
2
6
6
-
4
2
7
6
4268
key
gen
e
rati
on
is
on
e
of
the
known
existi
ng
te
ch
niques
.
This
i
m
ple
m
entat
ion
f
oc
use
s
m
uch
on
m
ulti
ple
bio
m
et
ric
featur
e
ext
r
act
ion.
Alth
ough
m
ultim
od
al
bi
om
et
ric
featur
e
extracti
on
e
xt
end
s
secu
rity
le
vel,
com
plexity
of
the
de
sig
n
inc
r
eases
ra
pid
ly
a
nd
will
not
fit
into
dece
ntrali
zed
wireless
a
r
chite
ct
ur
e.
A
E
S
key
is
al
so
gen
erat
ed
us
in
g
m
ixe
d
key
input,
w
hich
fi
nd
s
it
su
it
able
and
reli
able
with
incr
eased
secu
rity
le
vel.
The
m
ixed
ke
y
is
gen
erate
d
us
in
g
f
uzzy
base
d
log
ic
w
hich
re
quires
bio
m
et
ric
inp
ut
and
ra
ndom
k
ey
.
This
agai
n
inc
reases
num
ber
of
ope
rati
on
s
wh
ic
h
co
nsum
e
processin
g
powe
r
an
d
is
no
t
su
it
able
fo
r
ba
tt
ery
dep
e
nde
nt
de
vi
ces.
MA
NET
a
pp
li
cat
io
ns
de
m
and
t
he
arc
hi
te
ct
ur
e
to
be
si
m
ple
and
sec
ured.
He
nce
a
ddit
ion
al
com
pu
ta
ti
on
s u
se
d
for
exten
ded
sec
ur
it
y
directl
y
con
trib
ut
e
to
pr
ocessi
ng
powe
r
com
plexity
.
Secur
it
y
is
to
be
def
i
ned
at
the
cost
of
few
e
r
operati
ons.
Seve
ral
encr
y
ption
te
chn
iq
ues
are
repor
te
d
in
li
te
ratur
e
w
hich
woul
d
su
it
MAN
ET
e
nv
i
ronm
ent
in
te
rm
s
of
data
s
ecur
e
m
echan
i
sm
.
AES
is
co
ns
ide
red
as
be
s
t
appro
ac
h
in
c
on
te
xt
with
M
AN
E
T.
AE
S
is
reco
m
m
end
ed
ba
sed
on
enc
ryptio
n
tim
e,
decr
ypti
on
ti
m
e
and
th
r
oughput
of
sec
ur
it
y
syst
e
m
wh
ic
h
is
excep
ti
onal
ly
re
m
ark
able
ov
e
r
D
ES,
T
riple
DES
a
nd
Bl
ow
fis
h
[
22]
.
AES
an
d
Bi
om
et
ric
com
bin
at
ion
is
us
ed
i
n
wi
de
sp
ect
r
um
of
ne
twork
sec
ur
it
y
app
li
cat
io
ns
.
It
is
al
so
exten
de
d
to
A
TM
m
a
chine
wh
ic
h
is
desi
gn
e
d
to
be
hi
gh
s
peed
a
nd
al
so
at
ve
r
y
hig
h
sec
ur
i
ty
.
The
ap
pro
ach
us
e
s
Bi
om
et
ri
c
authe
ntica
ti
on
instea
d
of
A
T
M
card
an
d
process
t
he
in
f
orm
at
ion
us
i
ng
AES
a
nd
ste
ga
nogr
ap
hy
te
ch
nique,
in
orde
r
to
le
nd
cas
h
am
ount.
The
pro
posed
desi
gn
use
s
AES
a
nd
Bi
om
e
tric
com
bin
at
ion
and
ob
ta
in
s
su
b
sta
ntial
resu
lt
s
in
te
r
m
s
of
key
siz
e,
tim
e
and
re
sourc
e
con
s
um
ption
ov
er
DES
al
gorit
hm
and
reco
m
m
end
s
the AES a
ppr
oa
ch
to
appli
cat
ion
s
e
ns
uri
ng
hi
gh d
at
a
secu
rity
[
23]
.
The
pr
im
ary
obj
ect
ive
is,
t
o
desi
gn
a
s
ecur
it
y
te
chn
i
qu
e
w
hich
is
best
su
it
ed
f
or
M
AN
E
T
env
i
ronm
ent.
MANET
te
c
hnology
dem
ands
high
data
sec
ur
it
y
in
orde
r
to
m
i
ti
gate
m
a
l
ic
iou
s
at
ta
cks.
Henc
e
inco
rpor
at
in
g
the
sec
ur
it
y
le
ve
l
is
a
m
ajo
r
c
halle
ng
e
.
S
ecu
rity
for
MA
N
ET
is
re
quire
d
to
be
def
i
ned
at
the
cost
of
hi
gh
s
pe
ed
a
nd
le
ss
pr
ocessin
g
pow
e
r.
Alth
ough
ea
ch
of
these
pa
r
a
m
et
ers
set
a
tr
ade
off
i
n
c
on
t
ro
ll
in
g
each
oth
e
r,
optim
u
m
so
luti
on
is
to
be
desig
ne
d
with
ou
t
com
pr
om
i
sing
the
pe
rfor
m
ance
of
MAN
E
T
syst
e
m
s.
Op
ti
m
u
m
Encr
ypti
on
sta
nda
rd
is
to
be
us
ed
wh
ic
h
def
i
nes
a
su
bs
ta
ntial
secur
it
y,
retai
nin
g
a
n
op
ti
m
u
m
d
esi
gn c
om
plexity
.
The
P
rop
os
ed
syst
e
m
us
es
AES
crypt
ographic
syst
e
m
in
order
t
o
secu
re
data
com
m
un
ic
at
ion
ove
r
wireless
dyna
m
ic
network.
Sy
m
m
e
tric
ke
y
is
ge
ner
at
e
d
us
in
g
Bi
om
et
ric
featu
re
e
xtra
ct
ion
i
n
order
to
both
encr
y
pt
an
d
de
crypt
th
e
data.
128
bit
key
is
gen
e
rated
t
hroug
h
Bi
om
et
ri
c
feature
extra
ct
ion
.
Ma
in
f
oc
us
of
pro
po
se
d
desi
gn
is
in
opti
m
iz
ing
the
S
-
box
im
ple
m
entat
ion
,
i
n
ord
er
to
inc
rease
secu
rity
sta
ndar
d.
It
is
fo
ll
owed
by
bio
m
et
ric
based
key
gen
e
r
at
ion
.
T
his
co
m
bin
at
ion
is
v
ery
popula
r
a
nd
is
co
ns
ide
red
as
the
best
s
uit
f
or
MANET
e
nv
ir
on
m
ent
an
d
t
he
sam
e
is
repor
te
d
in
li
te
ratur
e
.
Fi
gure
1
sh
ows
the
pro
po
s
e
d
encr
y
ption arc
hitec
ture
Figure
1. Pro
pose
d
e
ncr
ypti
on a
rch
it
ect
ure
Key
for
S
-
box
is
gen
e
rated
ba
sed
on
bi
om
et
r
ic
featur
es.
Sim
ple
bio
m
et
ric
featur
e
a
pp
li
c
able
for
thi
s
MANET
is
fin
gerpr
i
nt.
Fin
ge
rprint
intr
oduc
es
an
ad
diti
onal
le
vel
of
data
secur
it
y
an
d
AES
key
is
ex
tract
ed
from
fing
er
pr
i
nt
in
pu
t.
He
nc
e
it
is
requir
ed
to
us
e
a
sim
ple
and
su
it
able
bi
om
et
ric
processi
n
g
w
it
ho
ut
com
pr
om
isi
ng
p
recise
ness o
f feat
ur
e
ex
t
racti
on.
The
e
nc
rypted
m
essage
is
ci
ph
e
r
te
xt
a
nd
decr
y
pted
m
essage
is
deci
pher
or
plain
te
xt
or
ori
gi
nal
m
essage.
T
his
process
is
sho
wn
in
Fig
ur
e
2.
AE
S
is
im
plem
ented
an
d
use
d
in
va
rio
us
data
com
m
un
ic
at
io
n
netw
orks.
It
works
with
blo
ck
siz
e
data
wh
ic
h
is
of
te
n
cal
le
d
as
ci
ph
er
te
xt
a
nd
i
s
i
m
ple
m
ented
us
i
ng
m
od
ifie
d
S
-
bo
x wh
ic
h
is a
n
i
nteg
ral p
a
rt
of
the en
c
ryptio
n sy
stem
s an
d bi
om
et
ric b
ased
key.
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
Impleme
nta
ti
on
of AE
S usin
g bio
metri
c
(
Sr
i
vi
dya
R
)
4269
Figure
2. Pro
pose
d decrypti
on a
rch
it
ect
ure
2.1
.
D
ynamic
S
-
b
ox
S
-
bo
x
is
us
uall
y
i
m
ple
m
ented
us
in
g
a
ff
ine
tr
ansfo
rm
ation
a
nd
i
nverse
fun
ct
ion
s
in
t
he
G
al
io’s
Fiel
d
GF
(
2
n
)
,
w
her
e
n=3
.
T
his
m
et
hod
is
op
ti
m
al
l
y
us
ed
in
var
io
us
ap
plica
ti
on
s.
Si
nce
S
-
box
a
rch
it
e
ct
ur
e
is
sta
nd
a
rd
a
nd
would
be
pre
dicta
ble
by
m
a
l
i
ci
ou
s
at
ta
cks
.
I
n
orde
r
to
a
dd
qu
al
it
y
secur
it
y
to
existi
ng
de
sign
s
,
S
-
bo
x
is
m
od
i
fied
by
inc
orp
or
at
in
g
nonlin
ear
be
ha
vior.
And
it
would
be
highly
dif
ficult
to
pr
e
di
ct
the
encr
y
ption.
S
-
box
ge
ne
rates
a
m
a
trix
of
hex
a
decim
al
n
um
ber
and
is
XO
Re
d
by
1’
s
com
p
lem
ent
of
th
e
or
i
gin
al
m
at
rix
wh
ic
h
is
the
base
f
or
e
nc
ryption.
T
his
pro
cess
is
as
sho
wn
i
n
F
ig
ur
e
3.
The
sam
e
m
a
trix
is
inv
e
rsed at
d
e
c
ryptio
n
e
nd in or
der to
retrie
ve
the
or
i
gin
al
m
essage.
In
the
presente
d
te
ch
nique,
in
pu
t
is
m
app
ed
to
def
a
ult
S
-
box
i
nh
e
re
ntly
gen
e
rated
.
Lat
er,
S
-
bo
x
is
XO
Re
d
by
1’
s
com
ple
m
ent
of
the
sam
e.
It
gen
erates
a
n
int
erm
ediat
e
S
-
box
w
hich
is
e
xtensiv
el
y
nonli
ne
ar
in
beh
a
vior.
This
is
res
pons
ible
for
generati
ng
ci
ph
e
r
te
xt.
T
he
inte
r
m
ediate
S
-
box
is
i
nversed
an
d
is
gi
ven
to
decr
y
pto
r
whic
h gen
e
rates
de
ci
ph
e
red te
xt.
Figure
4
s
hows
Dynam
ic
S
-
bo
x use
d
f
or
gen
e
rati
ng cip
her te
xt
.
Figure
3
.
Dy
na
m
ic
S
-
box crea
ti
on
us
in
g defa
ult
S
-
Box
Figure
4. Dy
na
m
ic
S
-
box use
d for
gen
e
rati
ng
ci
ph
e
r
te
xt
In
the
proce
sse
s
of
enc
ryptio
n,
input
value
at
the
po
int
(
X,
Y)
is
m
app
ed
t
o
def
a
ult
S
-
bo
x
an
d
again
m
app
ed
to
inte
rm
ediat
e
S
-
box
w
hich
is
respon
si
ble
for
ge
ne
rati
ng
the
ci
pher
te
xt.
As
s
how
n
in
F
ig
ur
e
.
4,
f
irst
uppe
r
blo
c
k
is
the
de
fau
lt
S
-
Box,
f
r
om
wh
ic
h
values
are
m
app
ed
on
t
o
l
ow
e
r
i
nterm
ediat
e
S
-
bo
x
fina
ll
y
to
ob
ta
in
the
ci
pher
te
xt
at
som
e
po
int
(X,
Y)
in
interm
ediat
e
S
-
Bo
x.D
ur
i
ng
de
crypti
on,
the
ci
ph
e
r
te
xt
i
s
m
app
ed
to
in
ver
se
of
i
nter
m
ediat
e
S
-
bo
x
an
d
a
gain
m
app
e
d
to
de
fa
ult
S
-
box
w
h
i
ch
is
res
pons
i
ble
f
or
gen
e
rati
ng the
decip
her te
xt.
2.2
.
Bi
ome
tric ba
s
ed k
ey
g
e
nera
tion
Fing
e
r
pr
int
is
a
physi
cal
trai
t
of
hum
an
be
ing
s
.
It
is
us
e
d
as
a
bi
om
et
r
ic
featur
e
an
d
is
extracte
d
thr
ough
bio
m
et
ric
pr
oce
ssin
g.
Bi
om
e
tric
is
us
ed
he
re
to
gen
e
rate
the
ke
y,
us
ed
f
or
da
ta
encr
ypti
on
and
decr
y
ption.
Bi
om
et
ric
pr
oces
sing
inclu
des
var
i
ou
s
ope
rati
on
s
s
uch
as
ca
pturin
g
a
nalo
g
data,
prep
r
oce
ssing,
m
inu
ti
ae extra
ct
ion
a
nd k
ey
generati
on.
Inp
ut f
in
gerp
rint im
age is init
ia
ll
y seg
m
ented
wit
h
an
inten
ti
on
of
no
ise
r
e
m
ov
al
. Th
e e
ntire i
m
age is
div
ide
d
int
o
m
at
rix
of
siz
e
16x16.
Var
ia
nce
is
then
cal
culat
ed
an
d
is
com
par
ed
with
de
fin
ed
global
th
res
ho
l
d
value
(0.10).
T
his
is
accom
plishe
d
f
or
t
he
en
ti
re
i
m
age.
If
t
he
val
ue
of
vari
ance
is
le
ss
th
an
th
reshold
va
lue,
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
9
, N
o.
5
,
Oct
ober
20
19
:
4
2
6
6
-
4
2
7
6
4270
th
e
val
ue
is
de
le
te
d.
The
im
a
ge
is
la
te
r
no
r
m
al
iz
ed
to
incr
ease
i
m
age
qu
al
it
y,
by
ob
ta
inin
g
de
sire
d
va
riance.
The n
or
m
al
iz
e
d
e
qu
at
io
ns are
shown
bel
ow
us
in
g (1)
-
(
4)
.
(
,
)
=
{
0
+
√
0
(
(
,
)
−
)
2
(
,
)
>
0
−
√
0
(
(
,
)
−
)
2
ℎ
(1)
wh
e
re
I(
i,
j
)
de
no
te
s t
he gray
-
le
vel v
al
ue
at p
ixel (i,
j
)
. M a
nd
VA
R
de
no
te
the esti
m
a
te
d
m
ean and varia
nce
of
J
resp
ect
ively
.
G(
i,
j)
de
no
te
s
the
norm
aliz
ed
gr
ay
-
le
vel
value
at
pix
el
(i,
j
)
.
M
0
and
VA
R
0
are
the
desir
e
d
m
ean
an
d
var
i
ance
values
re
sp
ect
ively
.
Im
age
is
div
i
ded
into
16x16
bl
oc
k
siz
e.
Bl
ock
est
i
m
ation
or
ie
ntati
on
is d
on
e
on t
he norm
al
iz
ed
i
m
age a
nd is c
ompu
te
d usin
g bel
ow equat
io
ns
:
(
,
)
=
∑
∑
2
(
,
)
+
2
=
−
2
+
2
=
−
2
(
,
)
,
(2)
V
y
(
i
,
j
)
=
∑
∑
(
∂
x
2
(
u
,
v
)
∂
y
2
j
+
ω
2
v
=
j
−
ω
2
i
+
ω
2
u
=
i
−
ω
2
(
u
,
v
)
,
(3)
θ
(
i
,
j
)
=
1
2
tan
−
1
(
v
y
(
i
,
j
)
v
x
(
i
,
j
)
)
,
(4)
Wh
e
re
θ
(i,
j
)
is
the lea
st sq
ua
r
e estim
at
e o
f
lo
cal
r
id
ge orie
ntati
on
at, t
he bl
ock cente
red at
p
ixel
(i,
j
)
.
The
im
age
is
bin
a
rized
us
in
g
Fixe
d
T
hres
ho
l
ding
Bi
na
rizat
ion
m
et
ho
d
wh
ic
h
ta
kes
a
n
im
age
and
returns
a
bi
na
ry
value.
I
n
t
his
m
e
tho
d
fixed
th
res
ho
l
d
value
is
us
e
d
to
assign
0’
s
and
1’
s
for
al
l
pix
el
po
sit
io
ns
.
It
does
so
by
us
in
g
two
th
res
ho
l
ds
,
on
e
f
or
ba
ckgr
ound
an
d
on
e
for
fin
ge
r
pr
i
nt.
The
im
a
ge
will
unde
rgo
paddi
ng
with
pa
dd
i
ng
num
be
r
of
pix
el
s
from
ever
y
si
de.
Ea
ch
of
the
se
pa
dd
e
d
pix
el
s
will
be
"painted"
in bl
ack. The
b
asi
c
idea f
or f
i
xed
Bi
nar
iz
at
ion m
et
hod
is
desc
ribed in
(
5)
.
(
,
)
=
{
1
(
,
)
≥
0
ℎ
(5
)
T sho
ws glo
bal
thr
es
hold
valu
e.
Cros
si
ng
N
umber
(C
N)
co
nc
ept
is use
d
f
or m
inu
ti
ae
extra
ct
ion
.
By
exam
ining
ne
ig
hborhoo
d
of
eac
h
rid
ge
pix
el
us
i
ng
a
3x3
wi
ndow.
T
his
m
eth
od
e
xtracts
ri
dg
e
en
di
ng
s
a
nd
bi
furcati
on
s
f
ro
m
the
s
ke
le
ton
i
m
age.
Crossi
ng
nu
m
ber
for
a
p
ixel
‘P’ ca
n b
e re
pr
ese
nted
a
s in
F
i
gure
5.
Figure
5
.
Cr
os
s
ing
num
ber
Ri
dg
e
en
ding
pix
el
corres
po
nd
s
to
a
Crossi
ng
Nu
m
ber
of
on
e
a
nd
bi
furc
at
ion
pix
el
co
r
respo
nd
s
to
a
Cros
si
ng
N
umber
of
t
hr
ee
.
Neig
hborh
ood
of
P
,
of
pix
e
l
p,
as
s
how
n
in
Fig
ur
e
5
Each
m
inu
ti
ae
po
i
nts
extracte
d
from
a
fing
e
rprint
im
age
is
denoted
as
(
x,
y)
co
ordi
nates.
I
n
thi
s,
we
sto
re
th
ose
extracte
d
m
i
nu
ti
ae
po
i
nts
in
two
diff
e
re
nt
vecto
rs,
Vect
or
M1
com
pr
ise
s
every
x
co
-
or
din
at
e
values
an
d
ve
ct
or
M2
com
pr
ise
s
ever
y
y
co
-
ord
inate
values
.
By
us
ing
M1
and
M
2
12
8
-
bi
t
bio
m
e
tric
key
is
gen
erated
.
The
Al
gorith
m
fo
r
gen
e
rati
ng
biom
et
ric k
ey
for
BAES is
stat
e
d Alg
ori
thm
1
:
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
Impleme
nta
ti
on
of AE
S usin
g bio
metri
c
(
Sr
i
vi
dya
R
)
4271
Algorithm
1
:
Gen
e
rati
ng
Bi
om
et
ric Key
Inp
ut: Fin
gerpri
nt b
iom
et
ric
im
age,
Ou
t
pu
t:
Bi
om
et
ric Key (Bi
oKey
)
in
He
xad
ec
i
m
al
f
or
m
at
Start
1.
Id
e
ntify
Mi
nuti
ae p
oin
ts i
n
Ro
I
-
NP
2.
Com
pu
te
m
od
ulu
s
of the
nu
m
ber
o
f
Mi
nu
ti
ae p
oin
ts
by
128,
Rem
-
NP m
od 12
8
3.
Ca
lc
ulate
total
m
inu
ti
ae p
oin
t
s av
ai
la
ble
f
or
stora
ge,
NP
=
NP
-
Re
m
4.
Nu
m
ber
of inte
racti
on
s
’
J
r
e
quire
d
to
p
e
rform
co
m
pr
ession o
f
the
k
ey
size
to 128
-
bit, J
=
NP
/1
28
5.
Fo
r
1
J,
Dr
op Le
ft 64
bit a
nd Ri
ght 6
4 bit
. D
i
vid
e t
he re
m
ai
nin
g key se
t i
nto
M
L
a
nd
M
R
.
6.
Sw
a
p
M
L
a
nd
M
R
7.
Convert t
hese
128 bit
s to
h
e
xa
decim
al
n
um
b
ers.
Stop
The Alg
or
it
hm
for
Bi
om
et
ric
Adva
nced E
nc
ryptio
n
Sta
nd
a
rd is sta
te
d Alg
or
it
hm
2
:
Algorithm
2
:
Bi
om
e
tric
Adva
nced E
ncr
ypti
on Sta
nd
a
r
d
Inp
ut: Pla
in te
xt of
128 bit
or 16
byte
b
loc
k, 16
byte
Bi
oK
e
y
Ou
t
pu
t:
Ci
pher
-
te
xt
of
128 o
r 16 byt
e
bit bl
oc
k
Start
1.
Stat
e
m
at
rix=
I
niti
al
stat
e 1
6 b
yt
e 4
x4 m
at
rix
2.
ADDBi
oKey
(
Stat
e
m
at
rix,
B
ioKey
0
)
3.
for ro
u
nd
s=
1 to
n
r
-
1
a.
SM
s
= Substi
tut
eB
yt
e (S
ta
te
m
at
rix)
b.
SM
r
= RowShi
ft (
SM
s
)
c.
SM
c
= Colum
nMix (
SM
r
)
d.
ADDBi
oKey
(
SM
c,
Bi
oK
ey
i
)
4.
SMs= S
ub
sti
tu
te
By
te
(
Stat
e m
at
rix)
5.
SMr= Ro
wShi
ft (
SMs
)
6.
ADDBi
oKey
(
SM
r,
Bi
oK
ey
nr
-
1
)
Stop
In
t
he
a
bove
BAES
al
gorith
m
SM
ind
ic
at
es
Stat
e
Ma
trix
an
d
SMs
in
dicat
es
sta
te
m
a
t
rix
obta
ined
after
byte
subs
ti
tuti
on
,
SMr
i
nd
ic
at
es
the
st
at
e
m
at
rix
ob
ta
ined
afte
r
sh
i
fting
r
ows,
SMc
ind
ic
at
es
sta
te
m
at
rix
ob
ta
ine
d
a
fter
m
ixing
c
olu
m
ns
.
3.
RESU
LT
S
A
ND
DI
SCUS
S
ION
S
AES
im
ple
m
e
ntati
on
al
ong
with
Bi
om
et
ric
key
ge
ner
at
io
n
is
do
ne
on
MATLAB
platfo
rm
.
AES
S
-
box
c
reati
on
log
ic
is
m
od
ifi
ed
by
us
i
ng
1’s
c
om
ple
m
ent
m
e
tho
d,
wh
ic
h
re
su
lt
s
in
nonlinea
r
ge
nerat
io
n
of
S
-
box
a
nd
i
nv
e
rse
S
-
box
m
at
rix.
He
nce
it
is
hig
hly
di
ffi
cult
t
o
predict
the
in
pu
t
data.
This
m
od
ifie
d
S
-
box
def
i
nes
a
n
a
ddit
ion
al
secu
rity
threa
d
in
ord
e
r
to
s
afe
guar
d
the
data.
T
he
input
gi
ven
is
a
plain
te
xt
w
hi
ch
in
hex
a
decim
al
f
or
m
at
is con
ve
rted
to
d
eci
m
al
d
at
a.
The
decim
al
d
at
a,
the
key,
m
od
i
fied
S
-
box
and
re
c
onfi
gur
at
ion
m
a
trix
al
tog
et
he
r
ge
nerat
es
a
ci
ph
er
te
xt.
128
bit
ke
y
is
us
ed
to
ge
ner
at
e
ci
pher
t
ext,
us
i
ng
key
exp
a
ns
i
on
func
ti
on
.
T
he
ne
w
key
m
a
trix
ge
ne
rated
works
in
co
nju
nctio
n
with
S
-
bo
x
an
d
reconfi
gurati
on
m
at
rix
to
ge
ner
at
e
the
ci
ph
er
te
xt.
The
key
use
d
to
gen
e
rate
ci
phe
r
te
xt
is
m
od
el
ed
by
us
i
ng
fi
ng
e
r
pr
i
nt
i
m
age.
A
Fi
ng
e
r
pri
nt
im
age
of
s
iz
e
256x50
0
is
ta
ken
and
is
c
onve
rted
to
gr
ey
scal
e
as
show
n
in
F
igure
6.
Fig
ure
7
s
hows
a
n
i
m
age
wh
ic
h
i
s
conve
rted
to
bin
a
ry
form
at
us
ing
thres
hold
com
par
iso
n
m
et
ho
d.
It
s
hows
a
n
i
m
age
bei
ng
pr
ocesse
d
us
in
g
Mi
nu
ti
ae
ext
ra
ct
ion
wh
ic
h
us
es
C
r
os
s
num
ber
m
et
hod.
Extract
ed
m
inu
ti
ae
ar
e
co
nv
e
rted
to
vecto
rs
a
nd
t
he
vecto
rs
a
re
again
conve
rted
t
o 1
28 b
it
key.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
9
, N
o.
5
,
Oct
ober
20
19
:
4
2
6
6
-
4
2
7
6
4272
Figure
6
.
I
nput
fin
ger p
rint im
age
Figure
7
.
Bi
nary
i
m
age
The
i
nput text
and Bi
om
et
ric p
r
ocessi
ng h
e
xa
deci
m
al
k
ey
are give
n
as
sho
wn in i
nput tex
t
.
Inp
ut text:
0
17
34
51
68
85
102
119
136
153
170
187
204
221
238
255
The he
xad
eci
m
al
f
or
m
at
o
f
in
pu
t t
e
xt is s
hown in pla
inte
xt_
he
x
.
Plai
ntext_he
x
= {'
00
'
'
11
'
'
22
'
'
33
'
'
44
'
'
55
'
'
66
'
'
77
'
'
88
'
'
99
'
‘
aa'
’
‘bb’
''
cc
'
'
dd
'
'
ee
'
'
ff
'
}
Figure
8
s
how
s
Mi
nu
ti
ae
extracti
on
po
i
nt
im
age.
CN
m
eth
od
is
us
e
d
in
order
to
e
xtra
ct
m
inu
ti
ae
po
i
nts.
T
he
12
8
bit
key
is
ge
ner
at
e
d
us
in
g
bio
m
et
ric
key
extracti
on
al
go
rithm
and
the
n
it
is
c
onver
t
ed
to
h
exa
decim
al
f
or
m
at
as sh
own
in k
ey
_h
e
x
.
key_
hex =
{'
1f
'
'
3c'
'
2d
'
'
01
'
'
0
3'
'
2e'
'
1b
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'
2d
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'
c2''
ff
'
'
9a'
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Figure
8
.
Mi
nuti
ae
extracti
on
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
Impleme
nta
ti
on
of AE
S usin
g bio
metri
c
(
Sr
i
vi
dya
R
)
4273
Figure
9
a
nd
F
igure
10
de
pict
S
-
bo
x
a
nd
in
ver
se
S
-
B
ox,
wh
ic
h
are
m
od
ifie
d
a
nd
us
e
d,
in
or
der
t
o
inco
rpor
at
e
no
n
-
li
nea
r funct
ion
al
it
y.
Figure
9
.
I
nter
m
idiat
e S
-
Box
Figure
10
.
Inve
rse of
interm
ediat
e S
-
Box
The ge
ner
at
e
d ci
ph
e
r
te
xt is
s
how
n:
105
196
224
216
106
123
4
48
216
205
183
128
112
180
197
90.
The In
ve
rse
ci
ph
e
r
te
xt is gen
erated
fo
ll
ow
e
d by dec
ryptio
n
op
e
rati
on a
nd is as
sho
wn
:
0 17
34
51
68
85
102
119
136
153
170
187
204
221
238
255.
Total
tim
e
tak
en
to
e
xec
ute
the
progra
m
on
MATL
AB
s
of
twa
re
is
show
n
us
in
g
F
i
gure
1
1
.
Total
tim
e
ta
ken
is
giv
e
n
by
1.270
97
sec
on
ds
,
in
orde
r
to
encr
y
pt
128
bit
inp
ut
da
ta
with
128
bit
Bi
ome
tric
base
d key an
d decry
pt the s
a
m
e.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8708
In
t J
Elec
&
C
om
p
En
g,
V
ol.
9
, N
o.
5
,
Oct
ober
20
19
:
4
2
6
6
-
4
2
7
6
4274
Figure
11
.
T
ot
al
tim
e taken
to
reg
e
ner
at
e
th
e d
eci
phe
r
te
xt
3.1.
C
ompar
ati
ve
s
tu
d
y
of
AES
an
d
BAE
S
This
sect
io
n
giv
es
an
anal
ysi
s
of
the
pro
po
se
d
B
A
ES
ci
pher
with
existi
ng
A
ES
ci
phe
r
.
The
perf
or
m
ance
m
e
tric
con
s
idere
d
f
or
c
omparis
on
are
pro
cessi
ng
t
i
m
e
and
m
e
m
or
y
util
iz
ed.
Ta
ble
1
giv
es
com
par
ison
of
execu
ti
on
ti
m
e
for
AES
an
d
BAES
ci
ph
e
rs
us
in
g
te
xt
d
at
a
input.
From
t
he
ta
ble
it
is
e
vid
e
nt
that
m
e
m
or
y
u
ti
li
zation
of
B
AES
an
d
AE
S
do
not
var
y.
And
BAE
S
is
equ
i
valentl
y
eff
ic
ie
nt
at
the
c
os
t
of
m
ini
m
al
p
ro
ce
ssing o
ve
rh
ea
d.
The
re
su
lt
s
are
gen
e
rated
us
i
ng
M
ATL
AB
too
l.
Tim
e
ta
ken
co
uld
be
e
ve
n
le
sser
if
it
i
s
execu
te
d
in
fast proces
sin
g sy
stem
s an
d
a
dv
a
nce
d
com
pilers. A
possibl
e issue wo
uld
be
only
w
it
h re
sp
ect
to
ac
qu
i
ring
t
he
bio
m
et
ric
i
m
a
ge
with
high
r
esolutio
n
a
nd
qu
al
it
y,
an
d
t
hi
s
cou
l
d
be
a
ddress
ed
by
us
i
ng
la
te
st
sens
ors
with
qu
al
it
y
i
m
age
pr
e
processi
n
g
capa
bili
ty
.
This
is
a
m
i
nor
iss
ue
an
d
do
e
s
not
m
ajorly
aff
ect
t
he
key
gen
e
rati
on
or
usa
ge.
Table
1.
T
he
c
om
par
ison
of
AES
an
d
B
AE
S
Para
m
eters
AES
BAES
Me
m
o
r
y
Utilized
1
6
k
b
(1
2
8
b
it
d
ata)
1
6
k
b
(1
2
8
b
it
d
ata)
Ti
m
e
in sec
0
.90
1
1
.27
4.
CONCL
US
I
O
N
In
this
pa
per,
data
secur
it
y
te
chn
i
qu
e
is
i
m
plem
ented
fo
r
MANET
a
pp
li
cat
ion
.
T
he
da
ta
secur
it
y
syst
e
m
is
desi
gn
e
d
us
in
g
a
m
al
ga
m
at
ion
of
AES
a
nd
Bi
om
e
tric
.
AE
S
is
desig
ne
d
us
in
g
un
i
qu
e
S
-
box
gen
e
rati
on
te
chn
i
qu
e
wh
ic
h
def
i
nes
m
ult
iple
secur
it
y
le
vels.
Key
gen
e
rati
o
n
f
or
encr
y
ption
a
nd
dec
rypt
ion
is
inco
rpor
at
e
d
usi
ng
b
iom
et
ric
input.
Bi
om
et
ri
c
input
is
a
fin
ger
p
ri
nt
i
m
age,
w
hich
is
easy
and
f
easi
ble
f
or
th
i
s
con
te
xt,
com
par
ed
t
o
rest
of
the
bio
m
et
ric
prof
il
es.
Sim
pl
e
bio
m
et
ric
pr
ocessin
g
te
ch
ni
qu
e
is
inc
orp
orat
ed
a
t
the cost
of
op
ti
m
u
m
p
ro
cessi
ng c
om
plexity
.
Bi
om
e
tric
key
is
pr
efe
rred
he
re
since
in
sy
m
m
e
tric
ci
ph
er
s
li
ke
AES
ke
y
play
s
a
vital
ro
le
an
d
it
is
easy
to
rep
la
c
e
the
bio
m
et
ric
key,
in
wors
t
po
ssi
ble
case
if
any
crypta
na
ly
st
analy
ses
the
cu
rr
e
nt
ke
y.
The
co
m
pu
ta
ti
on
al
tim
e
is
1.
2709
71
sec
onds
for
processin
g
on
In
te
l
Xeon
P
r
ocess
or
with
16
GB
RAM.
This
te
chn
iq
ue
can
be
en
han
ce
d
by
pr
operly
rout
ing
the
sym
m
e
tric
key
fr
om
s
ource
node
to
destinat
io
n
no
de,
so
that
add
it
io
na
l
secur
it
y
is
accom
plished
.
The
ta
r
get
a
pp
li
cat
io
n
of
BAES
c
ou
l
d
be
m
-
governan
ce
,
e
-
com
m
erce, bank
i
ng syst
em
s
, m
i
li
ta
ry syst
e
m
s an
d
in a
ny
genre
of MA
N
ETs fo
r
sec
ur
e
data exc
ha
nge.
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
Elec
&
C
om
p
En
g
IS
S
N: 20
88
-
8708
Impleme
nta
ti
on
of AE
S usin
g bio
metri
c
(
Sr
i
vi
dya
R
)
4275
REFERE
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ol
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r
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y
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Appl
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Secur
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a
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Sy
m
m
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r
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NET
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Multi
m
odal
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ptogr
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Le
ve
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int
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et
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Bio
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Cr
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pto
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Us
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Use
r
Pass
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”
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“
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Secur
e
S
oftwa
re
Im
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m
ent
a
ti
on
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ine
ar
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-
box
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th
e
Enh
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ent
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Biom
e
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cs
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”
2012
Inter
nati
onal
Conf
e
renc
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uti
ng,
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troni
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lectric
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l
Technol
ogi
es
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m
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Im
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,
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SI
Inte
rnational
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urnal
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i
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,
“
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Morphologi
c
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Ex
tra
c
ti
on
of
True
Fingerpr
int
Minuti
a
e
base
d
on
the Hit
or
Mi
ss
Tra
nsform
,
”
I
nte
rnational
Jou
rnal
of Bi
ometri
cs
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B
ioi
nfor
matic
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IJB
B)
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sh
Ku
m
ar
Garg,
“
Bina
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ec
hniqu
es
used
for
Gre
y
Scale
I
m
age
s
,
”
Inte
rnational
Journal
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f
Computer
Appli
cat
ions
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0975
–
8887)
,
vol.
71
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o.
1
,
Jun 2013
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[10]
G
Vinit
ha
Sanc
hez
,
T
S
Vishnu
Pri
y
a
,
“
Secur
e
and
Eff
ic
i
ent
Co
m
m
unic
at
ion
i
n
MA
NETS
using
AES
enc
r
y
p
ti
o
n
and
Fis
he
y
e
St
a
te
rout
ing
proto
col
,
”
Int
ernati
o
nal
Journal
of
I
nnovat
i
ve
Re
sea
rch
in
Sc
ie
nc
e,
Engi
ne
ering
an
d
Technol
ogy
,
ISS
N(O
nli
ne)
:
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,
v
ol
.
6
,
no
.
8
,
Aug 2017
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Zori
t
a,
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,
“
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a
e
ex
tra
c
ti
on
s
che
m
e
for
f
ingerprint
re
cognitio
n
s
y
stems
,
”
200
1
Inte
rnationa
l
Confe
renc
e
on
I
mage
Proce
ss
in
g
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Cat.
No.
01C
H37205)
IEE
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,
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a
e
E
xtr
ac
t
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v
el
1
Fe
at
ure
s
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Fingerpri
nt
,
”
I
E
EE
Tr
ansacti
ons
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urit
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2016.
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wig
Fronthal
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Kollreider
,
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ef
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al
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ur
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Enha
nce
m
ent
and
Minuti
a
e
Ext
ra
ct
i
o
n
in
Fingerpr
int
s
,
”
IEEE
Tr
ansactions
On Image
P
roce
ss
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17
,
no
.
3
,
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[14]
Xin
Gao,
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uang
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rui
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n
Li
u
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J
ufu
Feng
,
“
A no
vel
m
et
hod
of
fi
nger
print
m
inut
i
a
e
ext
ra
ct
ion
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d
on
gabor
phase
,
”
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IEEE
In
te
r
nati
onal
Con
fe
re
nce
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Image
Pr
oce
ss
ing
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EEE,
2010
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[15]
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O.
Alij
l
a
Motaz
Saad
Sally
F.
Iss
awi
,
“
Neura
l
Ne
twork
-
base
d
Minu
ti
a
e
Extrac
ti
on
for
Fingerprin
t
Veri
ficati
on
S
y
st
em
,
”
2017
8th
In
te
rnational
Conf
ere
nce on
In
formation
Techno
lo
gy
(
ICIT)
,
IEE
E
,
2017
.
[16]
T.
Pri
y
ank
a,
E.Ram
ara
,
“
Biom
e
tri
c
B
ase
d
Auth
ent
i
ca
t
ion
for
MA
NET
Us
ing
Eff
ic
i
ent
Fingerpr
i
nt
,
”
In
te
rnationa
l
Journal
of
Ad
va
nc
ed Re
search
Tr
ends
in
Eng
inee
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no.
20,
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pr
2016.
[17]
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m
ad
Sh
ahna
waz
Nasir
,
Praka
sh
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y
,
“
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ple
m
ent
ation
of
Biom
et
ric
Secu
rity
using
H
y
br
id
Com
bina
ti
on
of
RS
A
and
Sim
p
le
S
y
m
m
et
ric
K
e
y
Algor
it
hm
,
”
Inte
rnational
Jo
urnal
of
Innov
a
ti
v
e
Re
search
in
Computer
and
C
omm
unic
ati
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E
ngine
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ol
.
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no
.
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Oct
201
3.
[18]
S.
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Sa
th
ya
Pri
y
a
,
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Kart
h
iga
ikumar,
“
Mixed
Random
128
Bit
Ke
y
Us
ing
F
inge
r
Print
Fe
at
u
res
and
Bind
ing
Ke
y
for
AES
A
lgori
thm
,
”
2014
Inte
rnationa
l
C
on
fe
renc
e
on
C
onte
mpor
ary
Computing
and
Inf
orm
ati
cs
(
IC3I)
,
IEE
E
,
2014
.
[19]
S.
Sridevi
Sa
th
ya
Pri
y
a
,
P.
Kar
t
higa
ikumar
and
N.M.
SivaMang
ai
,
“
Gene
ration
of
128
-
Bit
B
le
n
ded
Ke
y
for
AE
S
Algorit
hm
,
”
Em
erging
ICT
for
Bridgi
ng
the
Fu
t
ure
-
Proce
edi
n
gs
of
the
49th
A
nnual
Conve
nt
io
n
of
the
Computer
Soci
e
ty
o
f
Ind
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