Int
ern
at
i
onal
Journ
al of Ele
ctrical
an
d
C
om
put
er
En
gin
eeri
ng
(IJ
E
C
E)
Vo
l.
8
, No
.
6
,
Decem
ber
201
8
, p
p.
5443
~
5448
IS
S
N:
20
88
-
8708
,
DOI: 10
.11
591/
ijece
.
v
8
i
6
.
pp
5443
-
54
48
5443
Journ
al h
om
e
page
:
http:
//
ia
es
core
.c
om/
journa
ls
/i
ndex.
ph
p/IJECE
Secure P
rivacy
Im
pli
ca
ti
ons for
Clients a
nd
End
-
users thr
ough
Ke
y Assortm
ent Cr
ypto
Tec
hn
iqu
es
I
mp
l
icated
Algorithm
D
.
R
amesh
,
B.
R
ama
Depa
rt
m
ent
o
f
C
om
pute
r
Scie
n
ce
,
Kak
at
i
y
a
Univ
e
rsit
y
,
Ind
ia
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
Feb
23
, 201
8
Re
vised
Ju
l
9
,
201
8
Accepte
d
J
ul
30
, 2
01
8
The
m
ai
n
role
of
ke
y
assortm
ent
cr
y
p
to
t
ec
hn
iques
will
he
lpful
to
provide
th
e
sec
urity
to the
se
nsiti
ve
d
ata
and
play
th
e
k
e
y
rol
e
for
business de
v
el
opm
ent
s.
Som
e
of
the
proble
m
s
are
rising
when
the
sche
m
e
will
sus
ta
in
the
poss
ession
cont
rol
to
pre
se
nt
the
la
t
est
set
of
te
chnica
l
and
business
conc
ern
s.
Som
e
of
the
complex
c
hal
l
enge
s
are
wait
i
ng
for
the
opti
m
isti
c
sol
uti
ons.
Th
e
cha
l
le
nges
ar
e
:
I
n
the
pla
nned
st
ora
ge
conf
id
ent
i
al
ity
impli
cate
d
outl
ine,
the
stipul
ation
of
enc
r
y
p
ti
on
fra
m
ew
ork
for
the
dat
a
whi
ch
is
conse
rve
the
self
tunni
ng
to
execu
te
m
aj
or
k
e
y
co
nstrat
int
s
b
y
con
ce
rin
ing
th
ei
r
f
iles
which
is
impos
e
d
pla
inte
xt
bel
ong
ing,
th
e
owners
of
the
privac
y
-
data
pr
ese
rve
the
sec
lusion
power
over
the
ir
ow
n
informati
on
t
o
form
ula
te
assured
wide
-
ran
ging
service
oper
ations
and
the
owners
of
dat
a
are
fa
ci
ng
th
e
complex
ity
to
orga
n
iz
e
th
eir
poss
ess
dat
a
which
is
acce
ss
ibl
e
-
m
ode
in
cloud
serve
rs,
conc
ern
ed
inn
er
servic
es:
topol
o
g
y
arc
hi
tectur
e
t
y
pe
of
implicat
e
d
dat
a
wi
th
the
ir
op
erati
ons
,
associa
t
ed
sec
recy
-
priv
acy
-
se
c
recy
d
y
n
amic
r
epl
i
ca
s
for
m
ake
use
of
t
he
data
base
d
sec
uri
t
y
withi
n
the
ir
r
ange
of
form
at
and
sec
retari
al
servi
c
es
with
the
ir
encr
y
pt
ed
da
ta
ex
ecution
cont
ro
l.
To
over
come
the
ses
in
convi
n
ce
s
thi
s
pape
r
is
proposing
the
t
ec
hni
ca
l
ide
a
l
s
t
hrough
the
al
gorit
hm
i
c
m
ethodolog
y
al
ong
the
gra
ph
ic
a
l
fl
ow
-
base
d
arc
hi
t
ec
tur
e.
T
his
pape
r is
proposing
the
k
e
y
assort
m
ent
cr
y
pto te
ch
nique
s
implicat
e
d
al
gori
thm
for
cl
ie
n
ts
and
e
nd
-
users
to
red
uce
the
above
m
ent
ion
complex
d
iffi
cu
lt
i
es;
it
desc
ribe
s
the
pr
i
m
ar
y
enc
r
y
p
ti
on
implic
ated
tech
nique
s
and
var
io
us
le
vel
s
of
cr
y
p
togra
ph
ic
algorithms
with
t
hei
r
implicati
on
s
al
ong
with
ext
ensions
of
cl
oud
impli
cate
d
data
sec
u
rity
and
digita
l
fore
nsics
implicate
d
a
pplianc
es
which
is
implica
te
d
wi
th enha
nc
e
d
var
ious h
ash
f
unc
ti
ons.
Ke
yw
or
d:
Key
-
L
ogging
Faci
li
ty
(
KLF
)
Pu
r
e
-
Ci
pherte
xt
(
PCT)
Pu
r
e
-
Plai
nte
x
t
(P
PT
)
Sing
le
M
ode E
ncr
y
ption (SM
E)
Copyright
©
201
8
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
:
D.
Ra
m
esh
,
Dep
a
rt
m
ent o
f
Com
pu
te
r
Scie
nce,
Kak
at
iy
a Univ
ersit
y,
War
a
ngal
, Tel
ang
a
na, I
ndia
.
Em
a
il
:
ra
m
eshd
52
5@gm
ai
l.c
om
1.
INTROD
U
CTION
The
cl
oud
com
pu
ti
ng
is
a
centrali
zed
distrib
uted
net
work
i
m
pl
ic
at
ed
fr
am
ewo
r
k
with
the
pro
visio
n
of
a
n
ass
or
tm
e
nt
of
fe
der
al
cl
oud
reli
able
se
rv
ic
es
to
t
he
cl
ie
nts
al
ong
with
their
e
nd
use
rs
[
1]
with
c
oncern
o
f
m
utu
al
agr
eem
ents
betwee
n
t
he
cl
oud
e
nter
pr
ise
s
an
d
en
d
us
e
r
cl
ie
nts
by
i
m
plica
ti
ng
the
m
ajo
r
se
rv
i
ces
of
cl
oud
en
vir
onm
ental
flexible
data
stora
ge
,
retrieval,
se
cur
it
y,
pr
i
vacy
and
in
-
tim
e
execu
ti
on
a
nd
hig
h
secur
a
ble
data
delivery
with
help
of
pro
vi
ded
co
ns
e
nt
cl
ie
nt
env
ir
onm
ental
i
m
pl
icated
key
asso
rtm
ent
i
m
plica
te
d
crypto
te
ch
niques
to
eva
de
an
d
confine
t
he
un
const
it
ution
al
acce
ssibil
it
y
[2
]
,
[
3].
O
w
ner
s
of
data
store
their
dat
a
in
cl
ou
d
w
hi
ch
there
fore
ne
ed
to
be
secu
red.
By
storing
data
in
encry
pted
form
,
on
e
can
m
ai
ntain
the
confide
ntial
it
y
and
pri
vacy
of
data
in
cl
oud.
In
CC
th
e
var
io
us
cry
ptogra
phic
i
m
plica
te
d
appr
oach
es
are
for
m
ulate
d
to
a
ddress
the s
ub
j
ect
of sec
recy
and privacy
of
authe
ntica
te
d
-
us
er
g
e
ne
rated.
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.
8
, N
o.
6
,
Dece
m
ber
201
8
:
5443
-
5448
5444
The
a
uthors
P
r
asan
na
an
d
A
kki
di
d
detai
l
de
scriptive
i
nv
e
sti
gation
on
cl
oud
c
om
pu
ti
ng
i
m
plica
te
d
pr
i
vacy
co
ncern,
sec
uri
ty
issu
es,
ch
al
le
ng
es
and
cry
ptogra
phic
im
plica
te
d
al
gorithm
s
[4
]
.
Crypto
grap
hy
is
the
knowle
dge
of
wr
it
in
g
in
to
p
secret
co
de
an
d
is
an
an
ci
ent
art
[5
]
.
I
n
the
cl
oud
com
pu
t
ing
e
nv
ir
onm
e
nt,
the
m
ai
ntenan
ce
of
auth
or
iz
at
io
n
and
pro
visio
n
of
co
ntr
ol
over
the
data
is
a
disti
nct
pr
ere
qu
i
sit
e
ov
er
an
d
abov
e
assess
an
d
t
o
authe
ntica
te
the
pr
im
ary
sec
ur
it
y
of
the
cl
oud
ser
vice
pr
ov
i
der
s
im
plicated
en
vironme
nt
[6
]
.
The
unf
or
tu
nat
e
inf
or
m
at
ion
r
evelat
ion
will
cause
a
ff
ect
s
t
he
data
posses
so
r
sta
tus,
ec
onom
ic
rep
utati
on,
a
nd
i
m
pact
their
reg
ulato
ry
an
d
le
gal
com
pli
ance
nee
ds
[7]
.
The
enc
ryp
ti
on
te
ch
nique
s
are
the
bes
t
an
d
so
phist
ic
at
ed
da
ta
protect
ion
m
echan
ism
to
der
i
ve
the
m
eth
ods
to
protec
t
the
treas
ur
e
d
data,
t
he
prot
ect
ion
la
ye
rs
f
or
m
ed
in the
for
m
s o
f
secret keys
to r
epr
ese
nt the
pr
ivacy
i
m
plica
ted
data [
8].
The
E
ncr
y
p
ti
on
im
plica
te
d
In
te
gri
ty
(EbI)
is
i
m
plica
te
d
on
t
he
te
ch
nolog
ie
s
a
nd
pro
gr
essi
on
of
le
ading
t
he
cr
yptogra
ph
ic
se
cur
it
y
dep
e
nde
d
ser
vices
[
9]
,
[10].
Enc
ryption
is
a
cr
ucial
and
im
po
rtant
data
al
ong
with
t
he
ir
ap
pliance
im
pl
ic
at
ed
protect
ion
te
ch
nique
an
d
t
he
e
nc
ryptio
n
keys
sh
oul
d
be
acc
ur
at
el
y
su
pe
r
vised
a
nd
protect
ed
.
T
he
ap
pear
a
nce
of
cl
oud
im
pli
cat
ed
ser
vices
will
li
ber
at
ion
of
e
ff
ect
i
ve
se
cur
it
y
i
m
plica
te
d
serv
ic
es,
an
d
al
so
it
i
m
plicated
t
he
enc
ryptio
n
im
pl
ic
at
ed
capab
il
it
ie
s
wh
ic
h
are
util
iz
ed
to
sec
ure
the
pr
i
vacy
data
especial
ly
in
the
cl
oud
i
m
pli
cat
ed
env
i
ron
m
ent,
and
al
so
it
pr
ov
i
de
the
c
han
ce
s
an
d
to
enab
le
the
al
l
kin
ds
of
orga
nizat
ions
to
easi
ly
pr
ot
ect
their
sensiti
ve
data
thr
ou
gh
t
he
inter
nal
key
-
lo
gg
i
ng
ba
sed
facil
it
y
(K
LbF)
[11]
,
[
12]
.
Wh
en
c
rypto
grap
hy
is
us
ed
to
protect
treasu
re
d
data,
the
risk
is
transf
er
re
d
from
the
co
ntent
to
the
keys
an
d
the
protect
io
n
of
c
rypto
gr
a
ph
ic
keyi
ng
m
ater
ia
l
beco
m
es
par
am
ount
onc
e
the
encr
y
ption has
been de
sig
ned
in a syste
m
at
ic
way.
The
cr
ucial
co
ncern
posi
ti
on
ed
in
the
way
of
cl
ou
d
de
pe
nded
a
doptio
n
i
m
pl
ic
at
ed
bounda
ry
is
the
requisi
te
f
or
tr
adin
g
t
o
retai
n
the
possessi
on
a
nd
al
so
to
c
on
t
ro
l
of
their
own
data
w
hile
it
is
in
pro
gressi
on
and
acc
um
ulate
at
cl
oud
im
p
li
cat
ed
ser
vice
pro
vid
e
rs
(CbSP)
[
6].
I
n
pre
s
ent
days,
m
any
or
gan
iz
at
io
ns
a
re
will
ing
to
m
ove
towa
rd
s
to
t
he
cl
ou
d
im
pli
cat
ed
en
vir
onm
ent
it
m
a
y
capit
ulate
the
inf
or
m
at
ion
im
plica
te
d
secur
it
y
(IbS
)
enh
a
ncem
ent
wh
e
re
the
CbSP
sti
ck
on
to
the
thir
d
-
par
ty
de
pe
ndent
f
ram
ework
s
.
I
n
crypto
gr
a
phy
m
echan
ism
,
the
un
-
en
crypte
d
data
(UED
),
r
efer
red
t
o
as
pure
-
plainte
xt
(
PPT).
The
PP
T
can
be
transm
itted
an
d
enc
rypte
d
in
to
pure
-
ci
phert
ext
(P
CT
),
whic
h
will
in
tur
n
(
usual
ly
)
be
decr
y
pted
int
o
us
a
ble
plainte
xt e
nvir
on
m
ent [13
]
.
2.
DETE
R
MINE
D
E
X
E
RTI
ONS A
N
D
SE
CURE
CONC
ERNS
The
m
ai
n
ro
le
of
key
ass
ort
m
ent
crypto
t
echn
i
qu
e
s
will
help
fu
l
t
o
prov
i
de
the
sec
ur
it
y
to
the
sensiti
ve
data
and
play
the
key
ro
le
for
bus
iness
de
velo
pm
ents
[1
4].
S
om
e
of
the
probl
e
m
s
are
rising
wh
e
n
the
schem
e
will
su
sta
in
the
po
s
sessio
n
c
ontrol
to
p
rese
nt
the
la
te
st
set
of
te
ch
nical
an
d
busine
ss
co
nc
ern
s
.
So
m
e o
f
t
he
c
om
plex
chall
enges are
wait
ing f
or the
optim
ist
i
c so
l
ution
s
. T
he
ch
al
le
nges a
r
e:
a.
The
cl
oud
im
plica
te
d
serv
ic
e
pr
ovi
der
wil
l
no
t
isolat
e
t
he
pr
im
ary
functi
on
al
it
y
of
data
-
owners
sel
f
con
t
ro
l m
echan
ism
f
ro
m
their
own pr
i
vacy
data.
b.
In
the
plan
ne
d
stora
ge
co
nf
i
de
ntial
it
y
i
m
plicated
ou
tl
ine
, th
e
sti
pu
la
ti
on
of
encr
y
ption
fr
a
m
ewo
r
k
f
or
th
e
data
w
hic
h
is
conser
ve
th
e
s
el
f
tu
nn
i
ng
to
exec
ute
m
ajor
key
co
ns
trat
i
nts
by
co
nce
rining
thei
r
file
s
w
hic
h
is i
m
po
s
ed plai
ntext
be
longin
g
c.
The
owne
rs
of
the
pr
ivacy
-
da
ta
pr
ese
r
ve
th
e
secl
us
io
n
po
wer
over
their
own
i
nfor
m
at
i
on
to
form
ulate
assured
wide
-
r
ang
i
ng
ser
vice
operati
ons
a
nd
the
own
ers
of
data
a
re
facing
the
c
om
plexity
to
orga
niz
e
their
possess
data
wh
ic
h
is
acce
ssible
-
m
od
e
in
cl
ou
d
serv
e
rs,
c
on
ce
rn
e
d
inne
r
ser
vices:
topolo
gy
arch
it
ect
ure
ty
pe
of
im
plica
t
ed
data
with
t
heir
op
e
rati
ons
,
associat
e
d
se
crecy
-
pri
vacy
-
secrecy
dy
nam
ic
rep
li
cas
f
or
m
a
ke
use
of
the
da
ta
based
secu
rity
within
their
range
of
form
a
t
and
sec
retaria
l
serv
ic
es
wit
h
their e
ncr
ypte
d data e
xec
ution co
ntr
ol.
To
overc
om
e
t
heses
in
co
nvinces
this
pa
pe
r
is
pr
op
os
in
g
the
al
go
rithm
ic
m
e
tho
dolo
gy
al
on
g
the
gr
a
phic
al
flo
w
base
d
f
ram
e
work
an
d
it
r
ecom
m
end
in
g
the
key
ass
ort
m
ent
crypto
t
echn
i
qu
e
s
im
plica
te
d
al
gorithm
fo
r
c
li
ents
and
e
nd
-
us
ers
to
r
ed
uce
the
ab
ove
m
ention
c
om
plex
di
ff
ic
ulti
es;
it
descr
ibes
t
he
pri
m
ary
encr
y
ption i
m
p
li
cat
ed
te
chn
i
ques a
nd v
a
rio
us l
evels
of
c
ryp
tograp
hic alg
ori
th
m
s w
it
h
thei
r
im
plica
t
ion
s
al
ong
with
exte
ns
io
ns
of
cl
oud
i
m
plica
te
d
data
secur
it
y
an
d
di
gital
fo
re
ns
ic
s
i
m
plica
te
d
Applia
nces
w
hich
is
i
m
plica
te
d
with e
nh
a
nce
d var
iou
s
h
as
h f
un
ct
ion
s
.
3.
CRYPTO
GRAPHI
C A
ND
HASH
I
MPLI
CA
TE
D
ALG
ORI
TH
MI
C
I
MPLI
CA
TI
O
NS
The
e
ncr
y
ptio
n
te
ch
niques
a
re
the
best
a
nd
s
ophisti
cat
ed
data
pr
otect
ion
m
echan
ism
t
o
der
ive
the
m
et
ho
ds
t
o
pro
te
ct
the
treasure
d
data,
t
he
pr
otect
ion
la
ye
rs
form
ed
in
the
f
or
m
s
of
secret keys
to
re
prese
nt
the
pr
i
vacy
im
plicated
data.
T
he
crypto
gr
a
phic
im
pl
ic
at
ed
al
gorithm
s
are
cl
assifi
ed
int
o
var
i
ou
s
ways
an
d
i
t
will
be
c
h
aracte
rized
by
the
nu
m
ber
of
key
-
points
a
re
de
plo
ye
d
f
or
ge
ne
rati
ng
the
enc
r
ypti
on
an
d
de
crypti
on
m
echan
ism
s
and
by
t
heir
i
m
pl
ic
at
ed
A
ppli
ance
se
que
nces.
The
has
hing
im
plica
ted
al
go
rithm
ic
(
HbA)
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
Secure Pri
v
acy
I
m
plicati
ons f
or
Cl
ie
nts
and
En
d
-
us
ers t
hro
ugh
Ke
y
Ass
or
t
men
t C
ry
pto
…
(
D.
R
ames
h
)
5445
pr
i
nciples
will
act
li
ke
as
si
gn
ific
ant
res
pons
ibil
it
y
in
te
r
m
s
of
sec
ur
i
ng
th
e
syst
em
s
by
certi
fy
the
reli
abili
ty
of
the
t
ru
ste
d
i
m
plica
te
d
data
com
m
un
ic
at
i
on.
The
H
bA
translat
es
the
var
ia
ble
-
de
pe
nded
-
le
ngth
te
xt
fiel
d
into
a
fi
xed
-
si
ze
-
strin
g
a
nd
i
t
pr
im
arily
us
ed
in
a
sec
ur
it
y
i
m
plica
te
d
sy
stem
s
with
the
two
c
on
c
e
r
ns
[15]
wh
ic
h
a
re
a.
Sing
le
m
od
e
has
hing
m
e
thod:
the
de
rive
d
the
has
h
im
p
li
cat
ed
ou
tp
ut;
it
is
co
m
plex
to
rev
e
rse
th
e
has
hing im
plicated
f
unct
ions
to g
e
ne
rate t
he ori
gin
al
m
essage.
b.
Non
-
colli
sion
i
m
plica
te
d
ou
t
pu
t
m
et
ho
d:
f
or
a
hash
i
ng
i
m
plica
te
d
al
go
rithm
,
it
is
com
pu
ta
ti
on
al
ly
infeasible
t
o
fi
nd
an
y
tw
o
m
essages which
a
re
the
sam
e
ha
sh
o
ut
pu
t.
He
r
e
the
ha
sh
is
t
r
eat
ed
as
m
essage
dig
est
or d
i
gital
f
in
gerpr
i
nt b
y
conside
rin
g
th
ese tw
o prop
e
r
ti
es.
The
in
div
i
du
al
s
are
pr
oduci
ng
a
sm
al
l
-
hash
-
outp
ut
fro
m
a
bu
l
ky
-
do
cum
ent
and
use
the
di
gital
fin
gerpr
i
nt
of
the
do
c
um
ent
as
the
hash
im
plica
te
d
ou
t
pu
t
.
This
ty
pe
of
dig
it
al
fing
e
rprint
will
be
us
ed
t
o
m
ake
sure
t
hat
the
data
has
not
bee
n
inter
fe
rin
g
wh
il
e
it
is
transm
issi
on
m
od
e
wh
e
n
is
passing
t
hro
ugh
the
low
-
secu
r
e
c
om
m
un
ic
at
ion
m
edia.
In
a
ddi
ti
on
,
from
the
dig
it
al
fin
gerpri
nt,
it
is
no
t
possible
t
o
discl
os
e
the
con
te
nt
of
the
or
i
gin
al
m
ess
age.
T
he
m
es
sage
-
dig
e
st
-
al
gorithm
5
(MD
5)
a
nd
Sec
ur
e
Hash
-
Algorit
hm
-
1
(S
H
A
-
1)
are
th
e
widely
us
ed
and
im
ple
m
ent
ed
crypt
ograph
ic
hash
im
plicated
al
gorithm
s.
These
two
ty
pe
s
of
has
hing
al
go
rithm
s
hav
e
bee
n
m
easur
e
d
as
the
one
-
way
and
powerf
ully
colli
sion
-
f
re
e
has
hing
al
go
rithm
s.
128
-
bit
ou
t
pu
t
has
bee
n
f
orm
ed
by
MD
5
a
nd
160
-
bit
ou
t
put
ha
s
been
f
orm
ed
by
S
H
A
-
1.
N
or
m
al
ly
,
the
SHA
-
1
is
m
easur
e
d
as
hi
gh
-
sec
ur
a
ble
im
plica
te
d
on
it
s
la
r
ger
siz
e,
but
c
om
pu
ta
ti
on
al
ly
it
’s
m
or
e
exp
e
ns
i
ve
tha
n
MD5.
The
S
HA
-
1
is
t
he
f
avou
red
has
hin
g
im
plica
te
d
al
gorithm
fo
r
i
m
plica
ti
ng
the
V
PN
de
plo
ym
ent
m
echan
ism
.
With
the
hard
ware
an
d
s
of
t
war
e
i
m
ple
m
entat
io
n
in
to
day'
s
networks,
t
he
perf
or
m
ance
dif
fere
nc
e
is us
ually
n
ot a
concer
n [16].
4.
KEY
AS
S
ORT
MENT
CRY
PTO
TE
CHN
IQU
ESI
MPLI
CA
TE
D ALG
ORI
TH
MI
C SE
QUE
NC
ES
As
pe
r
sho
wn
in
the
flo
w
cha
rt
F
igure.
1
an
d
the
al
gorithm
,
the
m
et
ho
dolo
gy
has
be
en
i
m
pl
ic
at
ed
in
two
le
vels
of
execu
ti
on
s
uc
h
as
en
d
-
us
e
r
i
m
plica
te
d
sign
at
ures
an
d
A
pp
li
ance
im
plica
te
d
segm
ents.
The
Applia
nce im
plica
te
d
segm
ents can be
proce
ssed
a
nd im
pli
cat
ed
f
ro
m
the
cl
ie
nts o
r
end
-
us
ers
sig
natu
re
s.
Figure
1. Exec
ution fl
ow ch
a
r
t of cl
ie
nt and
end
-
us
er
en
vir
on
m
ental
sign
a
tures
a
nd a
pp
li
ance e
nv
i
ronm
ental
div
isi
on
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.
8
, N
o.
6
,
Dece
m
ber
201
8
:
5443
-
5448
5446
4.1.
Clie
nt
and En
d
-
U
ser En
viro
nment
al Si
gna
tu
res
The
first
le
ve
l
of
exec
utio
n
com
po
ses
t
he
init
ia
l
authe
ntica
te
d
se
qu
e
nces
a
bout
t
he
en
d
-
us
e
r
i
m
plica
te
d
sign
at
ures
thr
ough
plain
te
xt
(PPT)
of
sig
natu
re
m
od
e1,
pr
i
vate
key
(PK)
of
sig
natu
re
m
od
e2
al
ong
with
the
der
i
ved
base
cl
ass
en
viron
m
ent
as
show
n
in
t
h
e
F
ig
ure
1.
T
he
der
i
ve
d
ba
se
cl
ass
c
an
be
com
po
sin
g
the
ci
per
text (P
C
T)
by m
aking
the single
set w
it
h
two
va
rio
us el
e
m
ents o
f
sign
at
ur
es s
uc
h as PPT
a
nd P
K.
F(
S
(P
PT
,P
K))
Der
i
ved Ba
se (
PCT
)
The
fi
nal
sta
ge
can
be
prep
ared
from
the
sen
der’s
side
env
i
ronm
ent
with
hel
p
of
t
he
f
unct
ion
gen
e
rati
on
with the
elem
ents o
f
PP
T
, P
CT
, E
U
-
A
uth
Ce
rtif
ic
at
e v
al
ues.
ʃ
(s
e(P
PT, PC
T
, E
U
-
Au
t
h
-
Ce
r
ti
ficat
e)
Finall
y,
t
he
ge
ner
at
e
d
final
st
age
of
operati
ons
will
be
pus
he
d
into
the
sec
ond
le
vel
exec
ution
m
od
e
of
Applia
nce
i
m
pl
ic
at
ed
seg
m
ents
fo
r
furt
her
up
gr
a
dati
on
s
s
uc
h
as
update
or
m
od
ify
the
existi
ng
data
or
enh
a
ncem
ent of
new d
at
a al
ong wit
h
the
ex
ist
ing
data.
4.2.
Ap
pli
ance
En
vironm
ent
al
Divisio
n
The
seco
nd
le
vel
of
e
xecu
ti
on
com
po
ses
A
pp
li
ance
im
pli
cat
ed
segm
ents
by
der
ivi
ng
th
e
two
sta
ge
s
of
A
ppli
ances m
od
es
su
ch
a
s A
ppli
ance
m
od
e1
a
nd
A
ppli
ance
m
od
e2
as
s
how
n
in
the F
ig
ure
1.
H
ere
th
e
firs
t
le
vel
of
A
pp
li
a
nce
m
od
e
c
an
ho
l
ds
t
he
A
pp
l
ia
nce
im
plica
ted
desire
d
plain
te
xt
(Ab
DP
T
)
and
the
sec
ond
le
vel
of
Applia
nce
m
od
e
can
hold
s
Applia
nce
i
m
pl
ic
at
ed
plain
te
xt
(
AbOPT
)
w
hich
is
bel
ongs
t
o
ot
her
plain
te
xt.
This
sec
ond
le
vel
of
Appl
ia
nc
e
m
od
e
is
the
enh
a
nce
d
ver
si
on
of
Applia
nc
e
m
od
e1;
it
co
ntains
t
he
ne
w
adde
d
or
update
d
data
of
t
he
par
ti
cu
la
r
sp
eci
fie
d
A
pp
li
ance
of
the
par
ti
cula
r
ente
rprise.
T
hese
t
wo
va
rio
us
le
ve
ls
of
Applia
nce m
odes can
b
e
co
m
bin
ed
t
og
et
her to
update the
f
i
nal v
e
rsion
of t
he gen
uin
e
d
at
a in clo
ud.
The
use
r
need
to
add
it
s
fi
na
l
ver
sio
n
of
t
he
data
int
o
the
cl
oud
se
rv
e
r
in
his
s
pecif
ie
d
stora
ge
locat
ion
with
out
giv
in
g
or
adv
e
rtisi
ng
by
it
s
ow
n
e
xisti
ng
or
m
od
ifie
d
netw
ork
arc
hitec
ture
al
ong
w
it
h
it
s
own
res
ources
li
ke
as
cur
re
nt
act
ive
us
er
s,
internal
pri
vate
acce
ssibil
it
y
keys
and
VPN
en
viron
m
ents.
Gen
e
rall
y,
the
cl
oud
e
nv
i
ron
m
ent
can
restr
ic
t
the
en
d
us
e
rs
to
sto
re
thei
r
e
nh
a
nce
d
versi
on
of
data
to
thei
r
existi
ng
data
wh
e
n
they
c
ha
ng
e
d
or
m
od
ifi
ed
their
i
nterna
l
recours
es
w
hich
a
re
not
in
cl
ud
e
d
w
he
n
they
get
the
res
ources
s
erv
ic
es
from
clo
ud
init
ia
ll
y.
This
al
gorithm
ic
te
chn
iq
ues
ca
n
tra
ns
m
i
ts
enh
ance
d
data
to
cl
oud
stora
ges
t
o
patch
it
wit
h
it
s
own
existi
ng
da
ta
with
se
ndin
g
a
ny
pri
vate
i
nfor
m
at
ion
a
bout
t
he
cl
ie
nt
or
e
nd
us
ers
.
T
his
f
il
te
ring
m
echan
ism
can
be
process
t
hrough
t
he
com
puti
ng
the
e
nd
-
us
ers
ci
per
te
xt
(CT
)
i
m
plica
te
d
on
their
co
nv
e
rsions.
T
he
CT
i
m
plies
the
PT
for
der
i
ving
the
AbDPT
a
nd
A
bOPT.
Finall
y,
the
der
i
ved
en
ha
nc
ed
Applia
nce
im
pl
ic
at
ed
co
nt
ents
will
be
for
warde
d
to
exte
rn
al
se
r
vice
a
nd
a
dd
e
d
to
t
he
cl
oud
i
m
plica
te
d
server
by FS
i
m
plica
te
d
se
qu
e
nce
as s
how
n
in
F
ig
ure
1.
FS
=
ʃ (A
bDP
T,
AbDCT,
E
U
-
Au
t
hCertifi
c
at
e)
4.3.
Algori
th
m
Stat
e
m
ent
0: E
nd
-
U
ser
im
plica
te
d
sig
natu
res
Gathe
rin
g
the
s
ign
at
ures
from
the end
-
us
e
rs
/
data ow
ner
s
Stat
e
m
ent
1: Gat
her
in
g
t
he
m
od
e
1
im
plica
ted
si
gn
at
ur
e
Plai
n
Te
xt (
P
P
T)
Si
gnat
ure m
od
e1
Stat
e
m
ent
2: Gat
her
in
g
t
he
m
od
e
2
im
plica
ted
si
gn
at
ur
e
Pr
ivate
Key (
P
K)
Sig
natu
r
e m
od
e2
Stat
e
m
ent
3: Com
po
se the
d
e
r
ived base
class
F(
S
(
PPT
, PK
))
PCT
Stat
e
m
ent
4: S
end
e
rs si
de pre
par
at
io
n
t
o pu
s
h
the
d
at
a
f
or
up
-
gr
a
datio
n
ʃ
(s
e (
PPT, PC
T, E
U
-
A
uth
Ce
rtific
at
e)
Stat
e
m
ent
5: App
li
ance
E
nv
i
r
on
m
ental
D
ivis
ion
:
Applia
nce
appr
oac
h1
Applia
nce a
ppr
oach
1
Appli
ance
im
plica
ted
Desire
d
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xt (A
bDP
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m
ent
6: App
li
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E
nv
i
r
on
m
ental
D
ivis
ion
:
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appr
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h2
Applia
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ppr
oach2
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im
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ted
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r
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Text (A
bOPT)
Stat
e
m
ent
7: App
li
ance
E
nv
i
r
on
m
ental
Plai
n Text
(AEPT
) wil
l be
gen
e
rat
e
d by com
bin
i
ng the
Applia
nce
En
vi
ronm
ental
D
esi
red
Plai
n
Te
xt
and
Applia
nce
i
m
plica
te
d
Ot
her Plai
n
Te
xt
Applia
nce
En
vi
ronm
ental
Plain
Te
xt (AE
PT) =A
bDPT +
A
bOPT
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
Secure Pri
v
acy
I
m
plicati
ons f
or
Cl
ie
nts
and
En
d
-
us
ers t
hro
ugh
Ke
y
Ass
or
t
men
t C
ry
pto
…
(
D.
R
ames
h
)
5447
Stat
e
m
ent
8: Com
par
ison wil
l be
nee
ded w
it
hout a
dv
e
rtisi
ng the
end
-
us
e
rs
upd
at
e
d pr
i
vate
env
i
ronm
ent f
or
der
ivi
ng the
Applia
nce
im
plica
te
d
Desire
d Pl
ai
n
Te
xt a
nd App
li
ance
E
nvir
on
m
ental
Desire
d
Ci
pe
r
Text
IF
CT
im
plies
PT
THE
N Appli
an
ce En
vir
on
m
en
ta
l Desired
Pla
i
n
Te
xt (AbDP
T)
THE
N Appli
an
ce En
vir
on
m
en
ta
l Desired
Ci
pe
rTex
t
(
AbDC
T)
Stat
e
m
ent
9: Desi
red
c
onte
nt
i
m
pl
ic
at
ed
A
ppli
ance w
il
l f
orwards t
o
e
xter
nalser
vice
Stat
e
m
ent
10
:
Finall
y st
age
of sto
ra
ge
the
enhance
d data
Final Se
nd
FS
FS
=
ʃ (A
bDP
T,
AbDCT,
E
U
-
Au
t
hC
erti
fic
at
e)
And
the
ser
vic
es
will
ver
ify
this
m
essage
as
wh
il
e
the
use
r
had
gen
e
rat
ed
or
se
nt
it
directl
y.
Th
e
above
im
plicational
se
qu
e
nc
es
will
well
work
im
plica
t
ed
on
the
ty
pe
of
ha
sh
a
lgorit
hm
has
been
i
m
ple
m
ented
to
squeeze
t
he
P
PT
al
so
orga
nism
of
h
om
o
m
or
ph
i
c
ge
ner
at
io
n.
Am
on
gs
t
t
hem
the
ho
m
om
or
ph
ic
i
m
plica
te
d
and
searcha
ble
en
crypti
on
m
et
ho
ds
are
la
r
gely
f
ashio
na
ble
w
he
re
one
can
pe
rfor
m
com
pu
ta
ti
on
a
nd searc
h o
n
P
CT e
xclu
sive
of r
e
veali
ng t
he PPT
[3
].
5.
CONCL
US
I
O
N
The
m
ai
n
ro
le
of
key
ass
ort
m
ent
crypto
t
echn
i
qu
e
s
will
help
fu
l
t
o
prov
i
de
the
sec
ur
it
y
to
the
sensiti
ve
data
and
play
the
ke
y
ro
le
f
or
bus
iness
de
velo
pm
ents.
T
he
m
a
in
prob
le
m
will
be
raised
when
t
he
syst
e
m
will
m
ai
ntain
the
ow
ner
s
hip
co
ntr
ol
an
d
to
prese
nt
the
la
te
st
set
of
te
c
hnic
al
an
d
bu
si
ness
c
on
cern
s
.
This
pa
pe
r
is
pro
posin
g
the
ke
y
assor
tm
ent
crypto
te
c
hn
i
ques
im
plica
te
d
al
gorithm
fo
r
cl
ie
nts
and
e
nd
-
us
e
rs
to
re
du
ce
the
a
bove
m
ention
com
plex
dif
ficult
ie
s;
it
descr
ibes
the
pri
m
ar
y
encr
ypti
on
i
m
pl
ic
at
ed
te
chn
iq
ue
s
and
var
i
ous
le
vels
o
f
crypt
ogra
ph
ic
al
gor
it
h
m
s
with
their
i
m
plica
ti
on
s
al
ong
with
extensi
on
s
of
cl
oud
i
m
plica
te
d
data
secu
rity
and
dig
it
al
f
or
e
nsi
cs
i
m
plica
te
d
Applia
nces
wh
ic
h
is
im
pl
ic
at
ed
with
e
nhance
d
var
i
ou
s
h
a
sh f
unct
ions.
ACKN
OWLE
DGE
MENTS
I
w
ould
li
ke
to
than
kful to
m
y
su
pe
r
visor, c
ol
le
agu
es
and
fr
i
ends.
REFERE
NCE
S
[1]
Eri
csson,
2015
,
“
Enc
r
y
pti
on
Perform
anc
e
Im
prove
m
ent
s
of
the
Paill
ie
r
Cr
y
ptos
y
s
tem
”
,
ava
i
la
bl
e
at
:
htt
ps://
epr
int.i
acr.org/
2015/864
.
p
df
[2]
Mell
,
Pe
te
r
and
T
im
Grac
e
,
“
Draft
NIS
T
W
orking
Defi
nit
ion
of
C
loud
Co
m
puting
”
,
htt
p://csrc
.
nist.
g
ov/groups/SNS
/c
louddc
om
puti
n
g/c
loud
-
def
-
v15
.
doc, on
Augus
t
2009.
[3]
Prasanna
B
T,
C
B
Akki,
“
A
Com
par
at
ive
Stud
y
of
Hom
om
orph
ic
and
Se
arc
hab
l
e
En
cr
y
pti
on
Sc
hemes
for
Cloud
Com
puti
ng”.
[4]
Prasanna
B.
T
,
C
.
B.
Akki
,
“
A
Su
rve
y
on
Hom
omorphi
c
and
Se
ar
cha
bl
e
Encr
y
ption
Secur
ity
Alg
orit
hm
s
for
Cloud
Com
puti
ng
”
.
Co
mm
unic
ate
d
to J
ournal
of
In
te
rc
onnec
t
ion
Ne
two
rks
,
April
2014.
[5]
Gar
y
C.
Kess
le
r ,
“
An Overview
of
Cr
y
ptogra
ph
y,
Handbook
on
L
oca
l
Area
Netwo
rks
”,
Au
erbac
h
,
Sept.
1998
.
[6]
Vault
iv
e
Enc
r
y
p
ti
on
in
Us
e
Plat
f
orm
,
Ta
king
Co
ntrol
of
Cloud
Data:
A
Rea
li
st
ic
Approac
h
to
En
cr
y
p
ti
on
of
Clou
d
Data
in
Us
e
”
,
Va
ult
ive
In
c. 489
5
t
h
Ave, 31st Fl.
N
ew Y
or
k, N
Y
100
17.
ww
w.va
ul
ti
v
e.
com
[7]
Gigaom Re
sea
r
c
h,
2014
,
“
Data
Pr
iva
c
y
and
Secur
ity
in
t
h
e
Pos
t
-
Snow
den
Era
”
,
av
ai
l
abl
e
a
t:
htt
p://ww
w.ve
rn
egl
oba
l.
com/sit
e
s/defa
ul
t/
fi
le
s/gi
gaom_resea
rch
-
dat
a_pr
iva
c
y
_
an
d_sec
urity
.
pdf
[8]
Cloud
Secur
i
t
y
Alli
an
ce,
“
Seca
aS
Im
ple
m
en
ta
ti
on
Guidance,
Ca
te
gor
y
8
:
Enc
r
y
pt
ion
”
,
Septe
m
ber
201
2,
htt
p://ww
w.c
lou
dsec
urity
a
lliance
.
org,
[9]
G
utman,
P.,
Nac
ca
ch
e,
D.
,
&
Pal
m
er,
C.
C.
(2005
,
Ma
y
/June).
“
W
hen
Hashes
C
oll
ide
”
.
IEEE
Sec
u
rity
&
P
rivac
y
,
3(3),
68
-
71
.
[10]
PERC,
2015,
“
Secur
e
Re
al
-
ti
m
e
Tra
nsp
ort
Protocol
(SRTP
)
for
Cloud
Service
s
”
,
av
ai
l
able
at
:
htt
ps://
tool
s.i
et
f
.
org/ht
m
l/
dra
f
t
-
m
at
tsson
-
per
c
-
srtp
-
cl
oud
[11]
Cr
y
ptogr
aph
y
in
an
al
l
En
cr
y
pt
e
d
world
ch
arting
the
futur
e
of
in
novat
ion
,
volum
e
92
|
#10
De
cem
ber
22,
2015,
Eri
csson T
ec
hno
log
y
Rev
ie
w Cr
y
ptogr
aph
y
in an
all
En
cr
y
pt
ed
w
orld
Secur
ity
in t
he
post
-
snow
d.
[12]
Fraunhofe
r
Insti
t
ute
for
Se
cur
e
In
form
at
ion
T
ec
hn
olog
y
.
(2012
,
M
arc
h). On t
he
Se
cur
ity
of
Cloud S
tora
ge
Servi
ce
s
.
Ret
ri
eve
d
f
rom
htt
p://ww
w.sit.
fr
aunhof
er.
d
e/
d
e/
c
loudstud
y
.
html
[13]
Ace
W
G,
2015,
Objec
t
Secur
ity
of
CoA
P
(O
S
COA
P),
ava
il
ab
le
at
:
ht
tps:/
/
too
ls.i
e
tf.
org/h
tml/d
raf
t
-
sel
ande
r
-
ace
-
obje
c
t
-
sec
uri
t
y
[14]
Europe
an
Netw
ork
and
Inform
at
ion
Se
cur
ity
Agenc
y
(ENIS
A).
(2009).
C
lo
ud
Com
puti
ng
bene
fi
ts,
risks,
and
rec
om
m
enda
ti
on
s for
informat
ion
sec
uri
t
y
.
R
et
ri
e
ved
from
htt
p://ww
w.e
nis
a.
eur
op
a.eu/act/r
m
/fi
le
s/del
ive
r
ab
le
s/cl
oud
-
computing
-
risk
-
assess
m
ent
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.
8
, N
o.
6
,
Dece
m
ber
201
8
:
5443
-
5448
5448
[15]
Acc
essD
at
a
.
(20
06,
April)
.
MD
5
Coll
isions: The
Eff
ect
on
Com
pute
r
Forensi
cs.
Acc
essD
at
a
W
hit
e
Pap
er.
[16]
Qiang
Huang
and
Jaz
ib
Frahim,
SSL
VP
N
Te
chnol
og
y
,
Net
work
W
orld
|
Oct
22,
2008
htt
p://ww
w.ne
tw
orkworld.
com/ar
ti
cle/2268575
/l
a
n
-
wan/c
hap
te
r
-
2
--
ssl
-
vpn
-
te
chno
log
y
.
html
BIOGR
AP
H
I
ES
OF
A
UTH
ORS
D
Ramesh
completed
M.T
ec
h
(
Com
pute
r
Scie
n
ce
)
From
School
of
IT
,
JN
TU
Hy
der
aba
d
and
pursuing
PhD
in
the
dep
art
m
ent
of
Com
pute
r
Scie
nce,
Kaka
tiy
a
Univer
sit
y
,
W
ar
anga
l
.
Present
working
as
Assista
nt
Profess
or
in
Com
pute
r
Scie
nce,
Depa
rtment
of
Comput
er
Scie
n
ce,
Univer
sit
y
C
ampus
Coll
ege
,
Kaka
t
i
y
aUnive
rsi
t
y
sinc
e
ei
ght
y
e
a
rs.
Area
of
int
ere
st
is
Cloud
Com
puti
ng,
cr
y
p
togra
ph
y
Netwo
rk
Secur
ity
.
Publ
ished
pape
rs
in
I
EE
E
In
te
rn
at
ion
al
Confer
ences
and
Int
ern
a
ti
ona
l
Journals.
Dr
B.
RAM
A
r
ec
e
ive
d
he
r
Ph.D.
Degre
e
in
Com
pute
r
Scie
nce
from
Pad
m
ava
ti
Mahi
la
Visvavid
y
ala
y
a
m
,
Thi
rupa
thi
,
I
ndia
in
the
y
e
ar
of
2009.
She
is
working
as
As
sistant
Profess
or
i
n
Com
pute
r
Scie
n
ce
at
Dep
art
m
en
t
of
Com
pute
r
S
ci
en
ce,
Kaka
tiy
a
Univer
sit
y
.
Her
are
a
of
in
te
r
est
is
Artifi
cial
Intelli
gen
ce
and
Da
t
a
Mining.
She
i
s
the
aut
hor
or
co
-
aut
hor
of
var
ious
scie
nti
f
ic
,
te
chn
ic
a
l
p
ape
rs
in
Scopus,
IEEE
,
Springer
I
nt
ern
at
ion
al
,
Nat
iona
l
Journals
an
d
Co
nfe
ren
c
es
.
Evaluation Warning : The document was created with Spire.PDF for Python.