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3
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[
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H
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
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8
8
-
8708
I
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C
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Vo
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7
,
No
.
5
,
Octo
b
er
201
7
:
2
8
7
3
–
2
8
8
2
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T
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s
er
v
ice
[
6
]
.
A
l
s
o
,
th
e
d
if
f
er
en
tial
m
et
h
o
d
ca
n
also
b
e
u
s
ed
f
o
r
p
r
iv
ac
y
p
r
eser
v
atio
n
in
b
ig
d
ata.
B
u
t
i
n
r
ea
l
ti
m
e
ap
p
licatio
n
,
t
h
e
p
r
iv
ac
y
is
u
n
r
eso
lv
ed
.
T
h
is
p
ap
er
g
i
v
es
th
e
s
u
r
v
e
y
f
o
r
th
e
p
r
iv
ac
y
a
n
d
s
ec
u
r
it
y
p
r
eser
v
a
tio
n
i
n
B
ig
Data
.
On
e
o
f
th
e
b
i
g
g
est
p
r
o
b
le
m
s
w
it
h
t
h
e
b
i
g
d
ata
s
ec
u
r
it
y
is
t
h
at
u
lti
m
atel
y
t
h
e
b
ig
d
ata
ar
e
s
to
r
ed
in
w
ar
e
h
o
u
s
e
w
h
ic
h
s
till
u
s
e
s
c
o
n
v
e
n
tio
n
al
au
t
h
e
n
ticatio
n
m
ec
h
an
i
s
m
.
A
s
a
n
al
y
tical
p
r
o
ce
s
s
is
an
e
x
p
en
s
iv
e
p
r
o
ce
s
s
th
at
n
o
t
o
n
l
y
r
eq
u
ir
es
s
p
ec
ialized
to
o
ls
b
u
t
also
r
eq
u
ir
es
d
if
f
er
e
n
t
f
o
r
m
s
o
f
i
n
f
r
astr
u
ctu
r
e.
Ma
j
o
r
ity
o
f
th
e
ex
i
s
ti
n
g
m
in
in
g
to
o
ls
(
e.
g
.
A
p
ac
h
e
Hiv
e)
is
b
ased
o
n
o
p
en
s
o
u
r
ce
p
r
o
g
r
am
s
w
h
ic
h
i
s
u
n
f
o
r
tu
n
atel
y
th
e
s
a
m
e
to
o
l
u
s
ed
b
y
th
e
i
n
tr
u
d
e
r
to
in
itiate
an
attac
k
.
N
o
t
o
n
l
y
h
a
s
th
is
m
aj
o
r
ity
o
f
t
h
e
s
to
r
ag
e
also
u
s
ed
t
h
e
co
n
ce
p
t
o
f
m
u
lti
-
te
n
an
c
y
i
n
o
r
d
er
t
o
m
i
n
i
m
ize
t
h
e
o
p
er
atio
n
co
s
t
o
f
th
e
u
s
er
.
Usa
g
e
o
f
m
u
lti
-
te
n
an
c
y
is
an
o
th
er
ca
u
s
e
o
f
p
r
o
b
le
m
s
to
w
ar
d
m
aj
o
r
ity
o
f
t
h
e
s
ec
u
r
it
y
th
r
ea
t
s
m
ai
n
l
y
t
h
e
p
r
i
v
ac
y
p
r
o
b
lem
s
.
A
l
t
h
o
u
g
h
,
th
er
e
ar
e
v
ar
io
u
s
s
ec
u
r
it
y
c
h
allen
g
es
in
clo
u
d
e
n
v
ir
o
n
m
e
n
t
e.
g
.
i
n
te
g
r
it
y
,
n
o
n
-
r
ep
u
d
iat
io
n
,
co
n
f
id
en
t
ialit
y
,
p
r
iv
ac
y
,
a
v
ailab
ilit
y
,
etc,
th
e
s
er
v
ice
p
r
o
v
id
er
i
s
y
et
to
e
n
s
u
r
e
r
esil
ie
n
c
y
a
g
ai
n
s
t
p
o
ten
tia
l
th
r
ea
t
s
o
v
er
clo
u
d
en
v
ir
o
n
m
e
n
t
ap
ar
t
f
r
o
m
t
h
e
tech
n
ica
l
ch
alle
n
g
es
in
p
r
o
ce
s
s
in
g
b
ig
d
ata.
T
h
is
p
ap
er
r
ev
ie
w
s
s
u
c
h
p
r
o
b
lem
s
an
d
tech
n
iq
u
es.
T
h
e
s
ec
tio
n
a
l
o
r
g
an
iza
tio
n
o
f
t
h
e
p
ap
er
i
s
d
o
n
e
a
s
f
o
llo
w
s
:
Sectio
n
2
d
is
cu
s
s
e
s
ab
o
u
t
a
co
n
ce
p
tu
al
d
escr
ip
tio
n
o
f
b
i
g
d
ata
f
o
llo
w
ed
b
y
d
is
c
u
s
s
i
o
n
o
f
p
r
iv
ac
y
is
s
u
e
s
in
b
i
g
d
ata
in
Sectio
n
3
.
Dis
cu
s
s
io
n
ab
o
u
t
ex
i
s
ti
n
g
s
ec
u
r
it
y
to
o
ls
is
elab
o
r
ated
in
S
ec
tio
n
4
.
T
h
e
ad
v
an
ta
g
e
p
o
in
ts
o
n
B
ig
Data
ar
e
d
is
cu
s
s
ed
in
Sectio
n
5
.
T
h
e
b
r
ief
i
n
g
o
f
an
elab
o
r
ated
r
esear
ch
w
o
r
k
to
w
ar
d
s
s
ec
u
r
it
y
o
f
b
i
g
d
ata
is
ca
r
r
ied
o
u
t
in
Secti
o
n
6
f
o
llo
w
ed
b
y
h
i
g
h
l
ig
h
ts
o
f
r
esear
c
h
g
ap
i
n
Sectio
n
7
.
Fi
n
all
y
,
Sectio
n
8
o
u
tl
in
e
s
t
h
e
co
n
c
lu
s
io
n
o
f
th
e
p
ap
er
.
2.
E
SS
E
NS
I
A
L
S O
F
B
I
G
DA
T
A
2
.
1
.
Arc
hite
ct
ure
o
f
B
ig
Da
t
a
T
h
e
ter
m
b
ig
d
ata
ca
n
b
e
s
aid
to
b
e
a
lar
g
e
v
o
lu
m
i
n
o
u
s
d
at
a
th
at
is
ch
ar
ac
ter
ized
b
y
m
o
r
e
co
m
p
le
x
f
o
r
m
o
f
d
ata
w
it
h
s
o
p
h
is
ticate
d
r
elatio
n
s
h
ip
ex
is
tin
g
a
m
o
n
g
s
u
c
h
d
ata
s
ets.
T
h
e
m
ai
n
ad
v
an
tag
e
o
f
b
ig
d
ata
i
s
th
at
it
p
er
f
o
r
m
s
t
h
e
b
etter
an
a
l
y
s
i
s
o
f
h
u
g
e
d
ata
th
an
co
n
v
e
n
tio
n
al
a
n
al
y
s
i
s
m
et
h
o
d
s
.
Du
e
to
th
is
r
ea
s
o
n
th
e
b
ig
d
ata
h
as
g
ai
n
ed
v
er
y
m
u
ch
i
n
ter
est
i
n
th
e
p
r
esen
t
g
en
er
atio
n
,
w
h
ic
h
h
a
s
ad
v
an
c
e
m
en
t
in
th
e
d
at
a
co
llectio
n
,
d
ata
s
to
r
ag
e
as
w
el
l
as
d
ata
in
ter
p
r
etatio
n
.
Fro
m
l
ast
f
e
w
d
ec
ad
es,
th
e
u
s
e
o
f
d
ig
ital
m
ed
ia
i
s
b
ein
g
in
cr
ea
s
ed
in
m
an
y
ar
ea
s
w
h
ic
h
g
e
n
er
ates
th
e
tr
e
m
en
d
o
u
s
a
m
o
u
n
t
o
f
d
a
ta,
e.
g
.
h
o
s
p
ital
d
ata,
b
an
k
d
ata,
s
o
cial
n
et
w
o
r
k
i
n
g
d
ata,
etc.
T
h
e
d
ata
s
to
r
ag
e
co
s
t
i
s
d
ec
r
ea
s
i
n
g
d
a
y
-
by
-
d
a
y
b
y
w
h
ic
h
w
e
ca
n
s
to
r
e
th
e
en
t
ir
e
d
ata
r
ath
er
th
an
d
is
ca
r
d
i
n
g
it.
I
n
a
d
d
itio
n
to
th
is
,
m
a
n
y
o
f
t
h
e
d
ata
an
al
y
zi
n
g
tech
n
iq
u
e
s
ar
e
d
ev
elo
p
ed
b
u
t
v
er
y
f
e
w
o
f
th
e
m
h
av
e
s
u
cc
ee
d
ed
in
ef
f
icie
n
t
d
ata
an
al
y
s
is
[
1
]
,
[
7
]
.
T
h
e
b
ig
d
ata
in
th
e
r
ea
l
w
o
r
ld
is
lik
e
th
e
co
llectio
n
o
f
h
u
g
e
r
eso
u
r
ce
s
w
h
ic
h
ca
n
b
e
u
s
ed
r
e
g
u
lar
l
y
.
T
h
e
ar
ch
itectu
r
e
(
Fig
u
r
e
1
)
o
f
th
e
b
i
g
d
ata
co
n
s
i
s
t
s
o
f
i)
d
ata
g
en
er
atio
n
p
o
in
t (
u
n
s
tr
u
c
t
u
r
ed
/s
tr
u
c
tu
r
ed
)
,
ii)
d
ata
o
w
n
er
s
,
iii)
b
u
s
i
n
es
s
an
a
l
y
s
ts
,
an
d
iv
)
d
ata
b
atch
.
U
n
s
t
r
u
c
t
u
r
e
d
a
n
d
S
t
r
u
c
t
u
r
e
d
D
a
t
a
S
t
o
r
a
g
e
I
n
f
r
a
s
t
r
u
c
t
u
r
e
R
e
a
l
T
i
m
e
D
a
t
a
B
a
t
c
h
d
a
t
a
D
a
t
a
O
w
n
e
r
s
T
e
c
h
n
i
c
a
l
A
n
a
l
y
s
t
s
B
u
s
i
n
e
s
s
A
n
a
l
y
s
t
s
Fig
u
r
e
m
1
.
A
r
ch
itec
tu
r
e
o
f
b
i
g
d
ata
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o
n
ten
t A
n
I
n
s
ig
h
t to
S
ec
u
r
ity
P
a
r
a
d
ig
m
fo
r
B
ig
Da
ta
o
n
C
l
o
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d
:
C
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Du
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2
.
2
.
B
ig
Da
t
a
Cha
re
ct
er
is
t
ics
T
h
er
e
ar
e
f
iv
e
d
if
f
er
en
t
b
ig
d
a
ta
ch
ar
ac
ter
is
tics
(
Fi
g
u
r
e
2)
[
8
]
,
i.e
.
,
i)
Data
v
o
lu
m
e,
ii)
Data
v
elo
cit
y
iii)
Data
Var
iet
y
,
i
v
)
Data
Val
u
e
an
d
v
)
Data
C
o
m
p
le
x
it
y
.
Da
ta
V
o
lu
me:
-
T
h
e
tr
em
e
n
d
o
u
s
a
m
o
u
n
t
o
f
d
ata
its
el
f
f
o
r
m
h
ig
h
v
o
l
u
m
e
o
f
b
ig
d
ata.
T
h
e
ex
is
t
in
g
d
ata
v
o
lu
m
e
s
ize
is
1
0
1
5
ter
a
b
y
te
s
,
an
d
it
h
as
b
ee
n
p
r
e
d
icted
th
at
th
e
d
ata
v
o
lu
m
e
s
ize
is
p
r
ed
icted
as
1
0
2
1
ze
ttab
y
tes
i
n
f
u
t
u
r
e.
O
w
in
g
to
lar
g
e
v
o
lu
m
e
o
f
d
ata,
it
is
q
u
ite
a
ch
allen
g
i
n
g
tas
k
to
ap
p
ly
an
y
f
o
r
m
o
f
co
n
v
e
n
tio
n
al
d
ata
p
r
o
ce
s
s
i
n
g
o
r
an
al
y
s
i
s
o
n
t
h
e
to
p
o
f
b
ig
d
ata.
Da
ta
V
elo
city:
-
T
h
e
d
ata
v
o
lu
m
e
i
s
a
p
r
o
b
lem
th
at
d
ea
ls
w
it
h
t
h
e
d
ata
s
p
ee
d
f
o
r
v
ar
io
u
s
s
o
u
r
ce
s
.
O
w
i
n
g
to
h
ig
h
er
s
p
ee
d
o
f
d
ata
g
en
er
atio
n
,
it
is
q
u
ite
a
d
if
f
icu
lt
tas
k
to
ca
p
tu
r
e
th
e
liv
e
d
ata
an
d
a
p
p
ly
an
a
l
y
s
is
o
n
it.
Da
ta
V
a
r
iety:
-
T
h
e
d
ata
v
ar
iet
y
i
s
a
p
r
o
b
le
m
ar
is
i
n
g
f
r
o
m
d
if
f
er
en
t
f
o
r
m
s
o
f
t
h
e
d
ata
o
v
er
th
e
d
is
tr
ib
u
ted
an
d
lar
g
e
n
et
w
o
r
k
.
T
h
e
d
ata
is
in
th
e
f
o
r
m
o
f
v
id
eo
,
au
d
io
,
tex
t,
etc.
m
ea
s
u
r
es
th
e
d
ata
r
ep
r
esen
tatio
n
.
O
w
i
n
g
to
d
if
f
er
en
t
f
o
r
m
s
,
it
q
u
ite
a
h
ar
d
task
to
w
r
ite
a
d
y
n
a
m
ic
q
u
er
y
s
y
s
te
m
co
n
s
id
er
in
g
s
u
ch
h
eter
o
g
e
n
eit
y
.
Da
ta
V
a
lu
e
:
-
T
h
e
d
ata
v
alu
e
c
an
m
ea
s
u
r
e
th
e
d
ata
u
s
ef
u
l
n
es
s
in
d
ec
is
io
n
m
ak
in
g
.
T
h
e
u
s
e
r
ca
n
co
m
p
ile
th
e
d
ata
s
to
r
ed
an
d
w
h
ich
ca
n
o
f
f
er
th
e
f
il
ter
ed
d
ata.
Ho
w
e
v
er
,
ca
p
tu
r
i
n
g
d
ata
v
al
u
e
co
n
s
id
er
in
g
ab
o
v
e
m
en
tio
n
ed
p
r
o
b
lem
i
n
b
ig
d
ata
is
r
ea
ll
y
a
d
if
f
ic
u
lt o
n
e.
Da
ta
C
o
mp
lexity:
-
T
h
e
d
ata
co
m
p
lex
it
y
m
ea
s
u
r
es
in
ter
c
o
n
n
ec
tio
n
an
d
i
n
d
ep
en
d
en
ce
o
f
b
ig
d
ata
s
tr
u
ct
u
r
es t
h
at
n
ee
d
s
lar
g
e
d
ata
ch
an
g
ed
.
B
i
g
D
a
t
a
C
h
a
r
e
c
t
e
r
i
s
t
i
c
s
D
a
t
a
v
e
l
o
c
i
t
y
D
a
t
a
v
a
l
u
e
D
a
t
a
V
a
r
i
e
t
y
D
a
t
a
C
o
m
p
l
e
x
i
t
y
D
a
t
a
v
o
l
u
m
e
Fig
u
r
e
2
.
B
ig
d
ata
ch
ar
ac
ter
is
t
ics
2
.
3
.
I
s
s
ues
in B
ig
Da
t
a
T
h
er
e
ar
e
f
e
w
co
n
ce
p
t
u
al
p
o
i
n
ts
w
h
ic
h
d
ef
in
e
th
e
b
i
g
d
ata
is
s
u
es
t
h
at
n
ee
d
to
b
e
an
al
y
z
ed
b
y
t
h
e
o
r
g
an
izatio
n
an
d
n
ee
d
to
ad
o
p
t
th
e
tec
h
n
o
lo
g
y
e
f
f
icien
tl
y
.
T
h
e
is
s
u
es
a
n
d
p
r
o
b
lem
s
o
f
th
e
b
ig
d
ata
n
ee
d
to
b
e
h
an
d
led
s
ep
ar
atel
y
.
I
n
ter
-
R
ela
ted
I
s
s
u
es
w
ith
C
h
a
r
a
cteris
t
ics:
T
h
er
e
ar
e
s
o
m
e
i
s
s
u
es
w
h
ich
ar
e
in
ter
-
r
elate
d
w
it
h
t
h
e
b
ig
d
ata
ch
ar
ac
ter
is
tic
s
.
W
h
e
n
t
h
e
v
o
l
u
m
e
o
f
d
ata
r
is
e
s
,
t
h
e
v
alu
e
o
f
v
ar
io
u
s
k
i
n
d
s
o
f
d
ata
w
ill
f
all.
T
o
d
ay
,
t
h
e
s
o
cial
s
i
tes
ar
e
g
e
n
er
ati
n
g
ter
ab
y
te
s
o
f
d
ata,
a
n
d
i
t
h
as
b
ec
o
m
e
m
o
r
e
d
if
f
ic
u
lt
to
h
an
d
le
th
e
d
ata
u
s
i
n
g
tr
ad
itio
n
al
tech
n
iq
u
e
s
[
4
]
.
A
t
p
r
esen
t,
th
e
u
s
es
o
f
e
-
co
m
m
er
ce
-
b
ase
d
ap
p
licatio
n
s
ar
e
in
cr
ea
s
ed
as
w
el
l
as
v
ar
io
u
s
tr
an
s
ac
tio
n
al
d
ata.
T
h
e
co
n
v
e
n
tio
n
al
d
ata
h
a
n
d
li
n
g
tec
h
n
iq
u
es
ar
e
f
a
iled
to
m
ain
tai
n
t
h
e
d
ata
v
elo
cit
y
m
an
a
g
e
m
en
t
i
n
a
p
ar
ticu
lar
b
an
d
w
id
t
h
.
T
h
e
d
ata
t
y
p
e
m
a
y
b
e
in
th
e
f
o
r
m
o
f
s
tr
u
ctu
r
ed
,
s
e
m
i
-
s
tr
u
ct
u
r
ed
an
d
u
n
s
tr
u
ct
u
r
ed
d
ata
an
d
s
u
ch
f
o
r
m
ca
n
n
o
t
b
e
m
an
a
g
ed
w
it
h
t
h
e
tr
ad
itio
n
al
tech
n
iq
u
es
o
f
an
al
y
tics
.
T
h
e
d
ata
o
f
d
if
f
er
en
t
o
r
g
an
izatio
n
s
w
il
l
b
e
d
if
f
er
e
n
t
an
d
t
h
e
y
w
i
ll
ad
o
p
t
d
i
f
f
er
e
n
t
d
ata
an
al
y
tic
m
et
h
o
d
s
.
T
h
is
w
i
ll
lead
to
t
h
e
b
u
s
i
n
es
s
g
ap
b
et
w
ee
n
t
h
e
I
T
o
r
g
an
izatio
n
a
n
d
b
u
s
i
n
ess
l
ea
d
er
s
an
d
al
s
o
m
ak
e
s
s
to
r
ag
e
i
s
s
u
e.
A
ls
o
,
t
h
e
b
ig
d
ata
co
m
p
le
x
it
y
is
a
n
i
s
s
u
e
o
f
b
ig
d
ata
t
h
at
r
eq
u
ir
es
th
o
u
s
a
n
d
s
o
f
p
ar
allel
r
u
n
n
in
g
s
o
f
t
w
ar
e’
s
w
i
th
m
a
n
y
s
er
v
er
s
.
I
n
ter
-
R
ela
ted
I
s
s
u
es
w
ith
Tr
a
n
s
p
o
r
t
a
n
d
S
to
r
a
g
e:
T
o
d
ay
,
d
ata
cr
e
ated
w
it
h
m
a
n
y
s
o
cial
n
et
w
o
r
k
i
n
g
s
ite
s
ar
e
g
en
er
ati
n
g
th
e
h
u
g
e
v
o
lu
m
e
o
f
d
ata,
i.e
.
,
th
e
d
ata
i
s
g
en
er
atin
g
w
i
th
v
ar
io
u
s
k
i
n
d
s
o
f
d
ev
ices
l
ik
e
m
o
b
ile
s
,
co
m
p
u
ter
s
,
etc.
T
h
e
d
ata
q
u
an
t
it
y
is
m
o
r
e
t
h
a
n
E
x
ab
y
te.
T
h
e
cu
r
r
e
n
t
o
r
t
r
ad
itio
n
al
d
ata
tech
n
iq
u
es
li
m
it
ter
ab
y
tes
o
f
d
ata.
W
ith
t
h
e
e
x
i
s
ti
n
g
tech
n
i
q
u
es
to
tr
an
s
f
er
t
h
e
E
x
ab
y
te
o
f
d
ata,
it
tak
e
s
n
ea
r
l
y
3
k
h
o
u
r
s
.
I
f
th
e
d
ata
tr
a
n
s
f
er
is
s
u
s
tain
ed
,
it
n
ee
d
s
s
o
m
e
m
o
r
e
ti
m
e.
I
n
ter
-
R
ela
ted
I
s
s
u
es
w
ith
Da
ta
Ma
n
a
g
eme
n
t
:
T
h
e
m
an
a
g
e
m
en
t
o
f
d
ata
is
o
n
e
o
f
t
h
e
b
ig
g
est
i
s
s
u
es
i
n
b
i
g
d
ata.
T
h
e
d
ata
w
i
th
d
if
f
er
en
t
s
ize,
f
o
r
m
at,
etc.
,
a
n
d
v
alid
at
io
n
o
f
th
e
s
e
co
m
p
le
x
d
ata
is
i
m
p
r
ac
tical
i
n
n
atu
r
e.
T
h
e
r
ep
r
esen
tatio
n
o
f
p
r
esen
t
d
ig
ita
l
d
ata
in
a
r
ic
h
m
a
n
n
er
is
ac
ce
p
tab
le
w
it
h
co
llectio
n
o
f
m
et
h
o
d
s
,
b
u
t th
er
e
is
n
o
ef
f
ici
en
t
m
ec
h
a
n
is
m
f
o
r
d
ata
m
an
a
g
e
m
en
t.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
5
,
Octo
b
er
201
7
:
2
8
7
3
–
2
8
8
2
2876
3.
P
RIVACY
I
SS
U
E
S
I
N
B
I
G
DATA
T
h
e
b
ig
d
ata
p
r
o
v
id
es
th
e
v
a
s
t
ap
p
licatio
n
ad
v
a
n
tag
e
s
b
u
t
th
e
co
n
v
en
t
io
n
al
d
ata
an
al
y
s
is
m
et
h
o
d
s
f
ail
to
p
r
o
v
id
e
th
e
p
r
o
p
er
p
r
iv
ac
y
m
ec
h
an
is
m
.
T
h
e
p
r
iv
ac
y
co
n
ce
r
n
o
f
th
e
b
ig
d
ata
in
cl
u
d
es
th
e
p
r
iv
ate
d
ata
d
is
clo
s
u
r
e
to
th
e
w
o
r
ld
.
T
h
e
o
p
en
-
e
n
d
is
s
u
e
w
i
th
t
h
e
b
ig
d
ata
is
p
r
iv
ac
y
a
n
d
s
ec
u
r
it
y
.
B
i
g
d
a
t
a
S
e
c
u
r
i
t
y
a
n
d
P
r
i
v
a
c
y
I
s
s
u
e
P
r
o
t
e
c
t
i
o
n
I
s
s
u
e
A
d
m
i
n
i
s
t
r
a
t
i
o
n
I
s
s
u
e
C
o
m
m
u
n
i
c
a
t
i
o
n
N
o
d
e
I
s
s
u
e
C
l
o
u
d
T
e
c
h
n
o
l
o
g
i
e
s
A
r
c
h
i
t
e
c
t
u
r
e
I
s
s
u
e
L
o
g
g
i
n
g
I
s
s
u
e
A
u
t
h
o
r
i
z
a
t
i
o
n
I
s
s
u
e
C
o
n
v
e
n
t
i
o
n
a
l
M
e
t
h
o
d
s
D
r
a
w
b
a
c
k
s
Fig
u
r
e
3
.
B
ig
d
ata
s
ec
u
r
it
y
&
p
r
iv
ac
y
T
h
e
b
ig
d
ata
m
a
y
also
i
n
cl
u
d
e
s
o
m
e
o
f
t
h
e
p
er
s
o
n
al
d
ata
w
h
ic
h
is
s
h
ar
ed
in
t
h
e
s
o
cial
n
et
w
o
r
k
i
n
g
s
ites
.
T
h
ese
d
ata
ca
n
b
e
co
m
b
in
ed
w
it
h
t
h
e
o
th
er
d
ata
s
ets
in
t
h
e
r
ea
l
w
o
r
ld
le
ad
in
g
t
o
th
e
ex
p
o
s
u
r
e
o
f
p
er
s
o
n
al
d
ata
to
o
th
er
s
.
T
h
e
s
h
ar
ed
p
er
s
o
n
al
d
ata
in
th
e
s
o
cial
m
ed
ia
ca
n
b
e
co
m
p
r
o
m
i
s
e
d
o
r
u
s
ed
b
y
o
th
er
s
f
o
r
th
e
p
u
r
p
o
s
e
o
f
b
u
s
i
n
es
s
in
illeg
iti
m
ate
m
a
n
n
er
w
it
h
o
u
t
an
y
k
n
o
w
led
g
e
o
f
t
h
e
u
s
er
.
S
o
m
e
o
f
th
e
p
er
s
o
n
a
l
d
ata
ca
n
m
i
s
u
s
e
f
o
r
cr
i
m
i
n
al
ac
tiv
itie
s
h
e
n
ce
it
n
ee
d
s
a
b
e
tter
f
o
cu
s
[
9
]
.
So
m
e
o
f
t
h
e
s
e
cu
r
it
y
an
d
p
r
i
v
ac
y
ch
alle
n
g
e
s
(
Fig
u
r
e
3
)
ar
e
s
tated
b
elo
w
:
P
r
o
tectio
n
I
s
s
u
e:
So
m
e
o
f
t
h
e
d
ata
w
h
ich
w
e
s
to
r
e
i
n
t
h
e
clo
u
d
w
i
ll
n
o
t
b
e
e
n
cr
y
p
ted
f
o
r
e
f
f
icie
n
c
y
p
u
r
p
o
s
e
w
h
ich
w
i
ll b
e
co
m
p
r
o
m
is
ed
o
r
en
co
u
n
ter
p
r
o
tectio
n
is
s
u
e
f
o
r
th
e
i
m
p
o
r
tan
t d
ata.
A
d
min
is
tr
a
tio
n
I
s
s
u
e:
E
v
er
y
a
d
m
in
i
s
tr
ati
v
e
n
o
d
e
h
a
s
an
ac
c
ess
ib
ilit
y
o
f
a
n
y
d
ata
w
h
ic
h
m
a
y
i
n
tr
o
d
u
ce
a
m
alicio
u
s
co
d
e
an
d
b
y
w
h
ic
h
t
h
e
d
ata
ca
n
b
e
m
a
n
ip
u
lated
o
r
co
m
p
r
o
m
is
ed
ea
s
il
y
.
A
r
ch
itectu
r
e
I
s
s
u
e:
I
n
ar
ch
ite
ctu
r
e
o
f
d
is
tr
ib
u
ted
n
o
d
e,
th
e
d
ata
ca
n
b
e
p
r
o
ce
s
s
ed
b
y
m
an
y
r
eso
u
r
ce
s
.
W
h
en
t
h
e
n
o
d
e
g
et
s
d
is
tr
ib
u
te
d
an
y
w
h
er
e
in
t
h
e
cl
u
s
ter
,
it
will
b
e
v
er
y
to
u
g
h
to
id
en
ti
f
y
t
h
e
co
m
p
u
tatio
n
an
d
b
y
w
h
ic
h
t
h
e
s
ec
u
r
it
y
a
s
s
u
r
an
ce
,
in
s
u
ch
ca
s
e,
w
ill b
e
v
er
y
d
if
f
ic
u
lt.
C
o
mmu
n
ica
tio
n
I
s
s
u
e:
Ma
n
y
o
f
th
e
Had
o
o
p
-
b
ased
d
ata
co
m
m
u
n
icatio
n
m
a
y
p
er
f
o
r
m
o
v
er
th
e
w
ir
ed
o
r
w
ir
ele
s
s
co
n
n
ec
tio
n
b
y
w
h
ich
an
y
o
n
e
ca
n
tap
o
r
h
ac
k
t
h
e
n
e
t
w
o
r
k
n
o
d
e
an
d
co
llect
th
e
i
m
p
o
r
tan
t d
ata.
C
lo
u
d
Tech
n
o
lo
g
ies:
T
h
e
ex
is
ti
n
g
tec
h
n
o
lo
g
ie
s
o
f
t
h
e
cl
o
u
d
ar
e
n
o
t
m
u
c
h
ef
f
icie
n
t
in
o
f
f
er
i
n
g
th
e
p
er
s
o
n
al
d
ata
s
ec
u
r
it
y
.
Lo
g
g
in
g
I
s
s
u
e:
A
s
w
e
all
k
n
o
w
t
h
at
t
h
e
ac
ce
s
s
o
f
th
e
c
lo
u
d
f
o
r
a
u
s
er
i
s
lo
g
g
i
n
g
i
n
d
ep
en
d
en
t
b
y
w
h
ic
h
u
s
er
w
ill
n
o
t b
e
h
av
i
n
g
an
y
k
i
n
d
o
f
d
ata
m
o
d
if
icat
io
n
.
C
o
n
ve
n
tio
n
a
l
Meth
o
d
s
Dra
w
b
a
ck
s
:
I
n
p
r
ev
io
u
s
d
ata
m
a
n
a
g
e
m
en
t,
to
o
ls
ar
e
n
o
t
m
u
ch
ef
f
ic
ien
t
i
n
h
a
n
d
in
g
th
e
h
u
g
e
v
o
l
u
m
e
o
f
d
ata,
b
y
wh
ich
d
ata
g
ets lea
k
ed
in
t
h
e
r
ea
l
w
o
r
ld
.
A
u
th
o
r
iz
a
tio
n
I
s
s
u
e:
T
h
e
jo
in
in
g
o
f
th
e
t
h
ir
d
p
ar
t
y
s
er
v
ice
p
r
o
v
id
es
m
ak
e
s
ec
u
r
it
y
an
d
p
r
iv
ac
y
i
s
s
u
e
f
o
r
u
s
er
s
i
n
an
y
n
et
w
o
r
k
ac
ti
v
it
y
.
4.
E
XI
ST
I
N
G
SE
CURI
T
Y
T
O
O
L
S
T
h
e
em
er
g
i
n
g
an
d
g
r
o
w
in
g
B
ig
Data
n
ee
d
an
ex
tr
ao
r
d
in
ar
y
tec
h
n
o
lo
g
y
t
h
at
ca
n
p
r
o
ce
s
s
th
e
d
ata
w
it
h
g
r
ea
ter
v
o
l
u
m
e
w
it
h
i
n
a
s
h
o
r
test
ti
m
e.
T
h
e
m
ec
h
an
i
s
m
ad
o
p
ted
f
o
r
b
ig
d
ata
s
u
c
h
as
m
as
s
i
v
el
y
p
ar
allel
p
r
o
ce
s
s
in
g
d
atab
ase,
d
is
tr
ib
u
t
ed
d
atab
ase,
clo
u
d
co
m
p
u
ti
n
g
,
s
ca
lab
le
d
ata
s
to
r
ag
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u
n
its
,
etc.
I
n
r
ea
l
ti
m
e
ap
p
licatio
n
s
,
b
ig
d
ata
an
al
y
tic
s
p
la
y
s
a
m
aj
o
r
r
o
le.
I
n
r
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en
t
p
ast,
th
er
e
ar
e
v
ar
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u
s
to
o
ls
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r
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iq
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e
s
ar
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elo
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ip
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u
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n
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a
n
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ze
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h
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d
ata.
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ese
all
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e
ab
o
v
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m
et
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s
h
a
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co
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s
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p
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o
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m
ath
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m
at
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a
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d
also
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T
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[
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Fro
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f
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ig
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o
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ata
ca
n
b
e
an
al
y
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d
.
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h
e
b
ig
d
ata
tech
n
iq
u
e
is
g
iv
in
g
an
id
ea
h
o
w
t
h
i
s
d
ata
ca
n
r
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lize.
A
b
ig
d
ata
tech
n
iq
u
e
s
h
o
u
ld
m
ee
t
th
e
f
o
llo
w
i
n
g
p
er
f
o
r
m
a
n
ce
f
ac
to
r
s
:
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h
e
tech
n
iq
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e
s
h
o
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ld
b
e
ab
le
to
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ef
in
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th
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es li
k
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m
e,
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tech
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iq
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e
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ld
h
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v
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ata
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o
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a
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atab
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tech
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g
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ld
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e
n
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n
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to
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av
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f
u
n
ctio
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alit
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in
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atio
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.
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h
e
tech
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lo
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m
u
s
t h
a
v
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y
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s
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e
f
a
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lt to
ler
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t a
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.
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h
e
tech
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lo
g
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m
u
s
t h
a
v
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th
e
s
ca
lab
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a
n
d
ex
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n
s
ib
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it
y
.
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tech
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lo
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y
m
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s
t a
llo
w
th
e
ad
-
h
o
c
q
u
er
ies alo
n
g
w
it
h
m
in
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m
al
m
ain
ten
a
n
ce
.
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u
r
r
en
tl
y
,
t
h
e
A
p
ac
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Fo
u
n
d
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ased
Had
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o
p
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o
p
en
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r
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p
o
s
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m
er
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al
l
s
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s
y
s
te
m
s
o
f
in
f
r
astr
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ctu
r
es
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ac
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itati
n
g
d
is
tr
ib
u
ted
clo
u
d
co
m
p
u
tin
g
.
T
h
e
s
u
b
s
y
s
t
e
m
s
in
Had
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o
p
ca
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b
e
g
iv
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n
a
s
i)
Had
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o
p
Dis
tr
i
b
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ted
Fil
e
(
HD
F)
s
y
s
te
m
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s
a
ls
o
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s
id
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as
f
ile
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y
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te
m
an
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ii)
Ma
p
R
ed
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ce
m
a
y
al
s
o
n
o
ted
as
p
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g
r
a
m
m
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n
g
p
ar
ad
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m
.
T
h
e
o
th
er
s
u
b
s
y
s
te
m
s
f
ac
e
is
s
u
es
w
h
ile
w
o
r
k
in
g
w
it
h
t
h
e
h
u
g
e
v
o
lu
m
e
o
f
d
ata.
I
n
r
ec
e
n
t
p
as
t,
th
e
w
o
r
k
s
h
av
e
g
i
v
e
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s
ig
n
i
f
ica
n
t
r
es
u
lt
s
to
s
to
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e
t
h
e
tr
e
m
en
d
o
u
s
a
m
o
u
n
t
o
f
d
ata
b
u
t
f
ailed
to
g
i
v
e
t
h
e
ac
c
u
r
ac
y
i
n
r
ea
d
in
g
b
ac
k
t
h
ese
d
ata.
I
n
th
ese
m
et
h
o
d
s
,
r
ea
d
in
g
o
f
d
ata
tak
es
m
o
r
e
ti
m
e
t
h
an
t
h
e
ti
m
e
ta
k
en
to
r
e
ad
th
e
s
m
a
ll
v
o
l
u
m
in
o
u
s
d
ata.
T
h
is
is
s
u
e
ca
n
b
e
atta
in
ed
b
y
r
ea
d
in
g
t
h
e
n
u
m
b
er
o
f
d
ata
d
is
k
s
at
a
ti
m
e,
b
u
t
it
d
o
es
n
o
t
m
a
k
e
an
y
s
en
s
e
a
s
it
l
ea
d
s
to
th
e
u
s
e
o
f
a
n
u
m
b
er
o
f
d
is
k
s
.
T
h
e
p
r
o
ce
s
s
m
a
y
lead
to
h
ar
d
w
ar
e
f
ai
lu
r
es,
an
d
it c
an
b
e
o
v
er
co
m
e
b
y
r
ep
licatio
n
.
T
h
e
ab
o
v
e
-
m
en
tio
n
ed
is
s
u
es
ca
n
b
e
r
eso
lv
ed
w
it
h
th
e
h
e
lp
o
f
HDF
s
y
s
te
m
a
n
d
th
e
d
ata
co
m
b
i
n
i
n
g
is
s
u
es
b
y
Ma
p
R
ed
u
ce
.
T
h
e
ad
v
an
ta
g
e
o
f
Ma
p
R
ed
u
ce
is
t
h
at
it
w
ill
m
i
n
i
m
ize
th
e
co
m
p
u
tatio
n
r
is
k
s
d
ea
li
n
g
w
it
h
r
ea
d
i
n
g
an
d
w
r
it
in
g
.
T
h
u
s
w
e
ca
n
s
a
y
th
at
th
e
Had
o
o
p
-
b
ased
s
y
s
te
m
ca
n
o
f
f
er
a
r
elia
b
le
s
o
lu
tio
n
f
o
r
d
ata
s
to
r
ag
e
an
d
p
r
esen
t a
n
ef
f
icie
n
t a
n
al
y
s
is
m
ec
h
an
is
m
.
T
h
e
HDF
s
y
s
te
m
an
d
Ma
p
R
ed
u
ce
c
an
o
f
f
er
s
to
r
ag
e.
4
.
1
.
H
DF
Sy
s
t
em
T
h
e
HDF
[
1
1
]
s
y
s
te
m
is
a
f
i
le
s
y
s
te
m
a
n
d
is
d
esig
n
ed
to
s
to
r
e
a
lar
g
e
v
o
lu
m
e
o
f
d
ata
an
d
s
tr
ea
m
i
n
g
lar
g
e
v
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l
u
m
e
o
f
d
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
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C
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I
SS
N:
2088
-
8708
C
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2879
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RE
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1
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2
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9
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1
Fro
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tab
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t
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m
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n
s
tr
ated
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l.
[
1
4
]
g
iv
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p
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d
s
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r
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y
b
ased
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ata
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th
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h
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it.
T
h
e
w
o
r
k
d
escr
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ed
in
H
u
et
al.
[
1
5
]
g
iv
es
th
e
p
r
o
m
i
n
en
t
en
er
g
y
e
f
f
icie
n
t
m
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n
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n
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h
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cu
r
r
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e
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w
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tech
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o
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ical
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s
u
es
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ess
ed
.
I
n
th
e
w
o
r
k
a
u
th
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s
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id
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o
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r
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.
ar
ch
itectu
r
al
is
s
u
e
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ess
ed
.
Yan
et
al.
[
1
6
]
in
tr
o
d
u
ce
d
a
u
n
iq
u
e
co
n
c
ep
t o
f
E
n
cr
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ted
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p
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clo
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.
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to
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clo
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p
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in
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clo
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.
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m
w
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cr
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.
T
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p
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f
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an
ce
an
a
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s
is
o
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m
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lts
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.
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s
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t
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m
i
n
B
D
m
in
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n
g
s
tated
i
n
Xu
et
al.
[
1
7
]
.
T
h
e
s
i
m
u
latio
n
r
es
u
lts
o
f
th
i
s
p
r
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p
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v
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f
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atc
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w
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co
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p
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.
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h
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f
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e
n
tl
y
u
s
ed
f
r
a
m
e
w
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k
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ce
n
ar
io
[
1
8
]
is
p
r
esen
ted
in
Fi
g
u
r
e
6
.
I
n
w
h
ich
t
h
e
d
ata
p
u
b
lis
h
in
g
,
d
ata
m
i
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,
an
d
d
ata
co
llectio
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p
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s
s
ar
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in
v
o
lv
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d
.
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n
th
is
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th
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d
ata
co
llecto
r
w
il
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co
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d
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p
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d
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it
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T
h
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d
s
in
th
is
co
n
s
is
t
o
f
v
ar
io
u
s
attr
ib
u
tes.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
J
E
C
E
Vo
l.
7
,
No
.
5
,
Octo
b
er
201
7
:
2
8
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–
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2880
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[
1
7
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w
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L
ia
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al.
[
1
9
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d
is
cu
s
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ed
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h
t
h
e
p
r
o
x
y
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-
en
cr
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p
t
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m
eth
o
d
,
b
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w
h
i
ch
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cip
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tex
t c
a
n
b
e
co
n
d
iti
o
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all
y
s
h
ar
ed
m
u
lt
ip
le
ti
m
e
s
w
it
h
o
u
t d
is
clo
s
u
r
e
o
f
d
ata.
P
er
e
r
a
et
al.
[
2
0
]
a
d
d
r
e
s
s
ed
th
e
n
ec
es
s
it
y
o
f
B
D
p
r
iv
ac
y
i
n
t
h
e
I
n
ter
n
et
-
of
-
T
h
in
g
s
(
I
o
T
)
w
o
r
ld
.
I
t
is
ad
m
itted
th
at
t
h
e
I
o
T
ca
n
h
elp
to
co
llect
th
e
lar
g
e
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et
o
f
d
ata
o
n
a
s
in
g
le
p
latf
o
r
m
,
b
u
t
w
i
ll
f
ac
e
p
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ac
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i
s
s
u
es
f
o
r
th
e
u
s
er
’
s
d
ata.
Ned
elc
u
et
al.
[
2
0
]
h
av
e
ad
d
r
ess
ed
th
e
B
D
ch
allen
g
e
s
an
d
t
h
e
ad
v
an
ta
g
e
s
o
f
B
D
i
n
m
an
u
f
ac
t
u
r
in
g
f
ield
.
T
h
is
s
tu
d
y
a
n
al
y
s
is
i
n
cl
u
d
es
s
o
m
e
o
f
th
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s
i
g
n
if
ica
n
t
cr
iter
ia
’
s
li
k
e
th
e
s
co
p
e
o
f
B
D
an
d
ad
v
an
ta
g
es
o
f
B
D
i
n
co
m
p
a
n
i
es
p
r
o
s
p
ec
tiv
e.
T
h
e
p
r
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ac
y
a
n
d
B
D
co
n
ce
p
t
w
a
s
also
e
m
p
h
asized
b
y
B
r
ian
et
al.
[
2
1
]
w
h
er
e
it
h
a
s
m
e
n
tio
n
e
d
th
at
o
n
l
y
p
r
o
v
i
d
in
g
th
e
s
ec
u
r
it
y
w
it
h
en
cr
y
p
tio
n
m
ec
h
an
is
m
is
n
o
t
e
n
o
u
g
h
b
u
t
it
is
a
p
r
iv
ac
y
s
o
lu
tio
n
f
o
r
t
h
e
d
ata.
So
m
e
f
u
tu
r
e
r
ec
o
m
m
e
n
d
atio
n
s
ar
e
also
ad
d
r
ess
ed
w
h
ic
h
m
a
y
g
iv
e
t
h
e
b
etter
id
ea
f
o
r
a
s
ec
u
r
it
y
s
o
l
u
tio
n
.
T
h
e
s
t
u
d
y
o
f
C
ar
d
en
a
s
et
al.
[
2
2
]
g
av
e
th
e
co
n
s
eq
u
en
ce
s
o
f
b
ig
d
ata
an
al
y
tics
f
o
r
s
ec
u
r
it
y
p
u
r
p
o
s
e.
I
n
th
is
,
it
i
s
ad
d
r
ess
ed
th
a
t
th
er
e
is
n
ee
d
o
f
ce
r
tai
n
r
es
ea
r
ch
es
to
b
e
k
ep
t
ex
p
lo
r
in
g
t
h
e
v
ar
io
u
s
in
tr
u
s
i
o
n
m
ec
h
a
n
is
m
s
e
v
o
lv
i
n
g
w
it
h
tec
h
n
o
lo
g
y
ad
v
a
n
ce
m
e
n
t.
Yu
et
al.
[
2
3
]
h
a
s
ex
p
r
ess
ed
th
e
n
et
w
o
r
k
i
n
g
co
n
ce
p
t
in
b
i
g
d
ata.
I
n
th
i
s
wo
r
k
s
ev
er
al
r
esear
ch
ar
ticle
s
p
r
esen
ted
f
o
r
th
e
n
et
w
o
r
k
i
n
g
i
s
s
u
es
in
B
D,
s
u
r
v
e
y
o
v
er
v
ie
w
i
s
d
escr
ib
ed
.
T
h
e
w
o
r
k
ca
r
r
ied
o
u
t
b
y
B
ae
k
et
al.
[
2
4
]
h
a
s
d
is
cu
s
s
ed
ab
o
u
t
a
s
ec
u
r
it
y
tec
h
n
iq
u
e
to
w
ar
d
s
s
af
e
g
u
ar
d
in
g
th
e
en
ter
p
r
is
e
ap
p
licatio
n
s
to
war
d
s
s
m
ar
t
g
r
id
s
.
A
h
ier
ar
ch
ical
s
tr
u
ct
u
r
e
w
a
s
d
ev
elo
p
ed
th
at
o
f
f
er
s
ex
te
n
s
i
v
e
an
al
y
tical
s
er
v
ice
in
m
o
s
t
s
ec
u
r
ed
m
an
n
er
u
s
in
g
d
ig
ital
s
i
g
n
atu
r
e,
id
en
ti
t
y
-
b
as
ed
en
cr
y
p
tio
n
m
ec
h
a
n
is
m
,
an
d
p
r
o
x
y
r
e
-
e
n
cr
y
p
tio
n
p
o
licie
s
.
P
r
o
b
lem
o
f
d
ata
s
h
ar
i
n
g
in
m
o
s
t
s
e
c
u
r
ed
m
a
n
n
er
w
a
s
d
is
c
u
s
s
ed
i
n
t
h
e
w
o
r
k
ca
r
r
ied
o
u
t
b
y
Do
n
g
et
al.
[
2
5
]
.
T
h
e
au
th
o
r
s
h
av
e
u
s
ed
th
e
tech
n
iq
u
e
o
f
r
e
-
en
cr
y
p
t
io
n
th
at
e
x
p
licitl
y
u
s
e
s
tr
an
s
f
o
r
m
atio
n
o
p
er
atio
n
o
v
er
th
e
cip
h
er
tex
t
o
v
er
th
e
v
ir
tu
a
l
m
ac
h
in
e
i
n
o
r
d
er
to
s
ec
u
r
e
t
h
e
s
en
s
iti
v
e
d
ata.
T
h
e
s
ec
u
r
it
y
is
ac
h
ie
v
ed
u
s
in
g
id
en
tit
y
-
b
ase
d
cr
y
p
to
g
r
ap
h
y
m
a
in
l
y
.
T
h
er
e
a
r
e
also
v
ar
io
u
s
s
tu
d
ie
s
to
w
ar
d
s
d
ata
p
r
iv
ac
y
.
O
n
e
o
f
s
u
ch
s
t
u
d
y
w
a
s
d
is
c
u
s
s
ed
b
y
F
u
et
al.
[
2
6
]
w
h
o
ad
d
r
ess
ed
th
e
p
r
o
b
lem
o
f
s
en
s
iti
v
e
d
ata
p
r
iv
ac
y
.
A
n
e
n
cr
y
p
tio
n
s
ch
e
m
e
f
o
r
ex
is
ti
n
g
clo
u
d
s
ea
r
ch
s
er
v
ices
i
s
f
o
r
m
u
lated
in
t
h
is
w
o
r
k
in
o
r
d
er
to
f
u
r
th
er
s
tr
e
n
g
th
e
n
t
h
e
cl
o
u
d
-
b
ased
s
e
m
an
t
ic
s
y
s
te
m
.
A
t
y
p
ical
ad
v
er
s
ar
ial
m
o
d
el
w
a
s
b
u
ild
u
s
in
g
s
e
m
a
n
t
ic
-
b
ased
ap
p
r
o
ac
h
o
n
tex
t
m
i
n
in
g
w
a
s
in
tr
o
d
u
ce
d
b
y
th
e
au
t
h
o
r
.
T
h
e
s
tu
d
y
o
u
tco
m
e
w
as
f
o
u
n
d
to
p
o
s
s
e
s
s
b
ett
er
s
ea
r
ch
ti
m
e
w
i
th
r
ed
u
ce
d
c
o
m
p
le
x
it
y
.
Ha
m
ee
d
an
d
A
li
[
2
7
]
h
av
e
p
r
esen
ted
a
tech
n
iq
u
e
f
o
r
th
w
ar
tin
g
t
h
e
s
ec
u
r
it
y
t
h
r
ea
ts
o
f
d
is
tr
ib
u
te
d
d
en
ial
-
of
-
s
er
v
ice
u
s
i
n
g
Had
o
o
p
.
A
m
i
tig
at
io
n
tech
n
iq
u
e
w
as
in
tr
o
d
u
ce
d
f
o
r
id
en
tif
ica
tio
n
o
f
p
o
s
s
ib
le
f
lo
o
d
in
g
t
h
r
ea
t
i
n
Ma
p
R
ed
u
ce
f
r
a
m
e
w
o
r
k
.
S
i
m
il
ar
ca
teg
o
r
y
o
f
th
e
w
o
r
k
w
as
al
s
o
ca
r
r
ied
o
u
t
b
y
J
o
s
e
a
n
d
B
in
u
[
2
8
]
co
n
s
id
er
i
n
g
th
e
ca
s
e
s
t
u
d
y
o
f
i
n
tr
u
s
io
n
o
v
er
DNS
s
er
v
er
s
.
A
co
u
n
te
r
m
ea
s
u
r
e
w
as
co
n
s
tr
u
cted
u
s
i
n
g
Had
o
o
p
an
d
Ma
p
R
ed
u
ce
.
Ho
n
g
b
in
g
et
al.
[
2
9
]
h
av
e
in
t
r
o
d
u
ce
d
th
e
m
ec
h
an
i
s
m
to
s
ec
u
r
e
th
e
s
to
r
ag
e
s
y
s
te
m
o
f
b
ig
d
ata
u
s
i
n
g
clo
u
d
in
d
ex
i
n
g
s
er
v
ice
s
its
el
f
as
w
ell
as
it
also
u
s
e
s
tr
ap
d
o
o
r
f
u
n
ctio
n
to
f
u
r
t
h
er
s
tr
en
g
th
t
h
e
en
cr
y
p
t
io
n
s
tan
d
ar
d
.
Usa
g
e
o
f
Ma
p
R
ed
u
ce
w
as
also
s
ee
n
f
o
r
e
v
alu
atin
g
t
h
e
s
tr
en
g
th
an
d
e
f
f
e
ct
iv
en
e
s
s
o
f
e
x
is
tin
g
v
alid
atio
n
tech
n
iq
u
es
o
v
er
cl
o
u
d
en
v
ir
o
n
m
en
t.
T
h
e
s
t
u
d
y
p
r
o
d
u
ce
s
a
g
o
o
d
liter
at
u
r
e
s
u
p
p
o
r
t
o
f
e
x
is
t
in
g
au
th
e
n
tica
tio
n
tec
h
n
iq
u
e
s
o
n
clo
u
d
u
s
in
g
Ma
p
R
ed
u
ce
.
J
u
s
t
lik
e
Ma
p
R
ed
u
ce
,
t
h
er
e
ar
e
s
tu
d
ies
w
h
er
e
o
n
l
y
Had
o
o
p
p
latf
o
r
m
w
a
s
e
m
p
h
a
s
ize
d
f
o
r
s
ec
u
r
it
y
.
T
h
e
w
o
r
k
ca
r
r
ied
o
u
t
b
y
L
i
et
al.
[
3
0
]
h
as
u
s
ed
A
d
v
an
ce
d
E
n
cr
y
p
tio
n
Sta
n
d
ar
d
(
A
E
S)
f
o
r
Had
o
o
p
clu
s
ter
s
in
o
r
d
er
to
s
ec
u
r
e
m
u
lti
m
ed
ia
f
iles
.
T
h
e
s
tu
d
y
o
u
tco
m
e
w
a
s
f
i
n
all
y
w
it
n
e
s
s
ed
w
i
th
lo
w
er
ed
en
cr
y
p
tio
n
ti
m
e.
U
s
ag
e
o
f
A
E
S
w
as
also
s
ee
n
i
n
t
h
e
wo
r
k
ca
r
r
ied
o
u
t
b
y
W
an
g
et
al.
[
3
1
]
ad
o
p
tin
g
n
an
o
w
ir
es.
Di
f
f
er
en
t
f
o
r
m
s
o
f
m
e
m
o
r
y
-
b
a
s
ed
ar
r
ay
w
er
e
d
ep
lo
y
ed
f
o
r
th
is
p
u
r
p
o
s
e
u
s
i
n
g
e
x
ter
n
al
i
n
ter
f
ac
e
o
f
i
n
p
u
t
-
o
u
tp
u
t.
Sc
h
u
s
ter
e
t
al.
[
3
2
]
h
av
e
p
r
esen
ted
a
tec
h
n
iq
u
e
t
h
at
s
ec
u
r
e
d
an
al
y
tical
f
r
a
m
e
w
o
r
k
t
h
at
u
s
e
s
Ma
p
R
ed
u
ce
f
r
a
m
e
w
o
r
k
.
Ya
n
g
et
al.
[
3
3
]
h
av
e
i
n
tr
o
d
u
ce
d
th
e
m
ec
h
a
n
is
m
o
f
attr
ib
u
te
-
b
a
s
ed
en
cr
y
p
tio
n
f
o
r
ad
d
r
ess
in
g
th
e
p
r
o
b
le
m
o
f
s
ec
u
r
ed
ac
ce
s
s
co
n
tr
o
l.
A
u
n
iq
u
e
tech
n
iq
u
e
o
f
p
o
lic
y
u
p
d
atin
g
s
ch
e
m
e
w
as
i
n
tr
o
d
u
ce
d
b
y
th
e
au
th
o
r
th
at
al
s
o
b
alan
ce
s
t
h
e
co
m
p
u
tat
io
n
b
u
r
d
en
.
Z
h
an
g
et
al.
[
3
4
]
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
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C
E
I
SS
N:
2088
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8708
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ac
k
p
r
o
p
ag
atio
n
tech
n
iq
u
e
o
f
h
ig
h
er
o
r
d
er
in
o
r
d
er
to
p
er
f
o
r
m
ef
f
icien
t
en
cr
y
p
tio
n
m
ec
h
a
n
i
s
m
o
v
er
clo
u
d
en
v
ir
o
n
m
e
n
t.
7.
RE
S
E
ARCH
G
AP
T
h
is
s
ec
tio
n
d
is
cu
s
s
e
s
ab
o
u
t
t
h
e
p
r
o
b
le
m
o
f
e
x
i
s
ti
n
g
r
e
s
ea
r
ch
w
o
r
k
t
h
at
is
s
till
lef
t
u
n
s
o
lv
ed
.
T
h
e
s
u
r
v
e
y
a
n
al
y
s
i
s
o
f
r
ec
en
t
w
o
r
k
s
a
n
d
s
o
m
e
g
o
o
d
s
tu
d
y
f
o
r
B
D
p
r
iv
ac
y
an
d
s
ec
u
r
it
y
s
u
g
g
es
ts
t
h
an
th
e
is
s
u
e
is
v
er
y
cr
it
ical
a
n
d
it
n
ee
d
s
a
p
r
o
p
er
s
o
lu
tio
n
in
r
ea
l
ti
m
e
ap
p
li
ca
tio
n
s
s
ce
n
ar
io
.
An
e
x
h
a
u
s
ti
v
e
s
tu
d
y
to
w
ar
d
s
all
th
e
r
ec
en
tl
y
e
x
p
lo
r
ed
r
esear
ch
co
n
tr
ib
u
tio
n
s
h
o
w
s
t
h
at
t
h
e
y
p
r
o
v
id
e
an
e
f
f
icie
n
t
tec
h
n
iq
u
e
to
s
o
l
v
e
ce
r
tai
n
s
ec
u
r
it
y
p
r
o
b
lem
s
o
v
er
b
ig
d
ata
ap
p
r
o
ac
h
in
clo
u
d
.
Ho
w
e
v
er
,
th
e
ar
ea
o
f
b
ig
d
ata
is
s
u
c
h
a
v
ast
t
h
at
it
w
ill
b
e
q
u
ite
ea
r
l
y
to
co
n
cl
u
d
e
ef
f
ec
ti
v
en
e
s
s
o
f
a
n
y
ex
i
s
ti
n
g
s
t
u
d
y
as
r
o
b
u
s
t
a
n
d
r
esil
ie
n
t
to
w
ar
d
s
p
o
ten
tial
s
ec
u
r
it
y
th
r
ea
ts
.
T
h
e
p
r
o
b
lem
s
t
h
at
ar
e
lef
t
u
n
s
o
lv
ed
ar
e
as b
r
ief
ed
b
elo
w
:
1.
Les
s
emp
h
a
s
is
o
n
a
u
th
en
tica
ti
o
n
mec
h
a
n
is
m
:
T
h
er
e
is
a
les
s
n
u
m
b
er
o
f
i
m
p
r
o
v
e
m
e
n
t
b
ein
g
ca
r
r
ied
o
u
t
to
w
ar
d
s
e
n
s
u
r
e
a
r
o
b
u
s
t
a
n
d
f
a
u
lt
-
f
r
ee
au
t
h
e
n
ticatio
n
p
o
lic
y
f
o
r
b
ig
d
ata
u
s
er
s
.
A
lt
h
o
u
g
h
,
t
h
er
e
ar
e
v
ar
io
u
s
n
o
v
el
id
ea
s
to
w
ar
d
s
au
t
h
en
ticatio
n
s
y
s
te
m
i
n
c
l
o
u
d
b
u
t
t
h
e
y
w
er
e
n
ev
er
te
s
tif
ied
f
o
r
th
e
ir
ap
p
licab
ilit
y
o
v
er
b
ig
d
ata
an
a
l
y
tic
-
b
ased
ap
p
licatio
n
.
2.
F
ew
s
tu
d
ies
fo
cu
s
in
g
o
n
p
r
iva
cy
:
A
t
p
r
esen
t
m
aj
o
r
it
y
o
f
th
e
s
t
u
d
ies
to
w
ar
d
s
b
i
g
d
at
a
s
ec
u
r
it
y
h
a
v
e
ad
d
r
ess
ed
th
e
p
r
o
b
lem
o
f
d
ata
s
ec
u
r
it
y
a
n
d
ac
ce
s
s
co
n
tr
o
l
m
ai
n
l
y
.
T
h
er
e
is
a
v
er
y
le
s
s
e
m
p
h
a
s
is
o
n
t
h
e
d
esig
n
s
ec
u
r
it
y
t
h
at
is
m
ai
n
l
y
d
u
e
to
m
as
s
iv
e
d
ata
s
ize.
3.
Les
s
fo
cu
s
to
w
a
r
d
s
d
a
ta
b
r
o
ke
r
s
:
A
t
p
r
ese
n
t,
m
an
y
o
f
th
e
clo
u
d
s
er
v
ice
p
r
o
v
id
er
s
ar
e
u
s
i
n
g
m
u
lt
i
-
ten
an
c
y
.
T
h
e
y
also
h
a
v
e
a
p
r
ac
tice
o
f
s
h
ar
in
g
ce
r
tai
n
s
eg
m
e
n
t
o
f
t
h
e
d
ata
to
th
e
t
h
ir
d
p
ar
t
y
t
h
at
tr
e
m
en
d
o
u
s
l
y
i
n
cr
ea
s
es p
o
ten
t
ial
r
is
k
.
P
r
iv
ac
y
is
th
e
f
ir
s
t t
h
i
n
g
to
g
et
co
m
p
r
o
m
is
ed
.
T
h
e
ex
is
t
in
g
s
o
l
u
tio
n
d
o
esn
’
t a
d
d
r
ess
s
u
c
h
p
r
o
b
lem
s
.
4.
S
to
r
a
g
e
in
s
ec
u
r
ity
in
b
ig
d
a
ta
:
I
t
is
w
e
ll
k
n
o
w
n
f
ac
t
th
at
No
SQL
d
atab
ase
is
s
ti
ll
e
v
o
l
v
in
g
a
n
d
q
u
ite
p
r
o
b
lem
atic
to
r
etain
o
p
ti
m
al
s
ec
u
r
it
y
a
s
p
er
th
e
d
e
m
an
d
s
.
No
r
m
a
ll
y
,
t
h
e
b
ig
d
ata
ar
e
s
to
r
ed
in
m
u
lt
ip
le
tier
s
w
h
er
e
e
x
i
s
ti
n
g
s
y
s
te
m
d
o
esn
’
t
r
ea
ll
y
f
o
cu
s
o
n
h
o
w
s
u
ch
ex
is
tin
g
e
n
cr
y
p
tio
n
s
tr
ate
g
y
i
s
co
m
p
lia
n
t
o
f
tier
-
b
ased
s
to
r
ag
e
s
tr
ate
g
y
.
8.
CO
NCLU
SI
O
N
E
n
s
u
r
in
g
s
ec
u
r
it
y
to
w
ar
d
s
cl
o
u
d
is
n
e
v
er
a
n
ea
s
y
tas
k
f
o
r
an
y
s
er
v
ice
p
r
o
v
id
er
esp
ec
i
all
y
i
n
t
h
e
p
r
esen
ce
o
f
s
u
c
h
m
alic
io
u
s
ac
tiv
itie
s
o
v
er
i
n
ter
n
et.
W
it
h
t
h
e
tech
n
o
lo
g
y
o
f
clo
u
d
m
o
d
er
n
izin
g
,
th
e
attac
k
er
s
ar
e
also
b
ec
o
m
i
n
g
s
m
ar
t.
Fr
o
m
s
to
r
ag
e
v
ie
w
p
o
i
n
t,
s
to
r
in
g
t
h
e
o
p
er
atio
n
al
d
ata
tak
e
s
t
h
e
s
to
r
ag
e
co
s
t
b
u
t
s
to
r
in
g
t
h
e
an
a
l
y
ze
d
d
ata
ta
k
e
s
th
e
co
s
t
o
f
b
o
th
s
to
r
ag
e
a
n
d
p
r
o
ce
s
s
in
g
ca
r
r
ied
o
u
t
to
tr
an
s
f
o
r
m
i
t.
Hen
ce
,
b
i
g
d
ata
is
b
asical
l
y
an
ex
p
e
n
s
i
v
e
af
f
a
ir
to
w
ar
d
clo
u
d
s
to
r
ag
e
s
y
s
te
m
i
n
o
r
d
er
to
s
to
r
e
it.
T
h
e
p
r
o
b
lem
m
i
g
h
t
t
u
r
n
w
o
r
s
t,
i
f
s
u
c
h
ex
p
en
s
i
v
e
d
ata
is
s
u
b
j
ec
ted
to
c
o
m
m
o
n
o
r
p
o
ten
tial
th
r
ea
t
s
.
Hen
ce
,
t
h
is
p
ap
er
s
ig
n
i
f
ica
n
tl
y
d
is
cu
s
s
es
t
h
e
m
aj
o
r
to
p
ics
r
elate
d
to
b
ig
d
ata
s
ec
u
r
it
y
a
n
d
p
r
iv
ac
y
.
W
ith
t
h
is
p
ap
er
,
w
e
p
r
o
v
id
ed
th
e
r
ec
en
t
w
o
r
k
s
t
h
at
ar
e
g
iv
e
n
I
E
E
E
X
p
lo
r
e.
Fro
m
t
h
e
a
n
al
y
s
is
o
f
r
esear
ch
g
ap
an
al
y
s
i
s
,
it
i
s
p
o
in
ted
th
a
n
n
o
m
u
c
h
s
tu
d
ie
s
o
f
f
er
ed
ef
f
icie
n
t
s
ec
u
r
it
y
.
T
h
er
e
ar
e
s
o
m
e
r
ec
en
t
m
eth
o
d
s
ca
n
b
e
ex
ec
u
ted
p
r
o
p
e
r
l
y
to
m
ak
e
b
etter
s
ec
u
r
it
y
s
y
s
te
m
f
o
r
m
B
D.
Sti
l
l,
th
ese
r
ec
e
n
t
m
eth
o
d
s
n
ee
d
co
n
ti
n
u
o
u
s
r
esear
ch
to
m
a
k
e
t
h
e
m
m
o
r
e
ef
f
icie
n
t
w
it
h
in
cr
ea
s
in
g
r
ea
l
-
ti
m
e
d
a
ta.
Ou
r
f
u
tu
r
e
w
o
r
k
w
ill
b
e
f
o
cu
s
ed
to
w
ar
d
s
en
s
u
r
i
n
g
m
o
d
elin
g
to
w
ar
d
s
s
tr
en
g
th
e
n
i
n
g
th
e
p
r
iv
ac
y
p
r
o
b
le
m
s
in
b
i
g
d
ata
s
ec
u
r
it
y
.
P
o
s
s
ib
ilit
ie
s
o
f
u
s
i
n
g
o
p
ti
m
izat
io
n
th
eo
r
y
w
ill
b
e
q
u
ite
h
i
g
h
er
as
w
e
d
o
n
’
t
w
a
n
t
to
in
cr
ea
s
e
th
e
r
eso
u
r
ce
co
s
t
o
v
er
b
ig
d
ata
in
f
r
astru
ct
u
r
e
w
h
i
le
at
th
e
s
a
m
e
ti
m
e
w
e
w
a
n
t to
ac
h
ie
v
e
o
p
ti
m
al
p
r
iv
ac
y
p
r
o
tectio
n
a
n
d
r
esil
ien
c
y
f
r
o
m
m
aj
o
r
p
o
ten
tial th
r
ea
ts
.
RE
F
E
R
E
NC
E
S
[
1
]
S
.
L
o
h
r,
“
T
h
e
A
g
e
o
f
Big
D
a
ta
,”
Ne
w
Yo
rk
T
i
m
e
s
,
V
o
l.
1
1
,
2
0
1
2
[
2
]
M
.
S
w
a
n
,
“
T
h
e
Qu
a
n
ti
f
ied
S
e
lf
:
F
u
n
d
a
m
e
n
tal
Disru
p
ti
o
n
i
n
Big
D
a
ta
S
c
ien
c
e
a
n
d
Bi
o
lo
g
ica
l
Disc
o
v
e
r
y
,”
Big
Da
t
a
,
V
o
l
.
1
.
2
,
p
p
.
8
5
-
9
9
,
2
0
1
3
[
3
]
F
.
P
ro
v
o
st,
a
n
d
T
.
F
a
wc
e
tt
,
"
Da
ta
S
c
ien
c
e
a
n
d
it
s
Re
latio
n
sh
ip
t
o
Big
Da
ta
a
n
d
Da
ta
-
d
riv
e
n
De
c
isi
o
n
M
a
k
in
g
,"
Big
Da
ta,
V
o
l
.
1
.
1
,
p
p
.
5
1
-
5
9
,
2
0
1
3
[
4
]
T
S
u
ti
k
n
o
,
D
S
ti
a
w
a
n
,
IM
I
S
u
b
ro
t
o
,
"
F
o
rt
ify
in
g
b
ig
d
a
ta
in
f
ra
stru
c
tu
re
s
to
f
a
c
e
s
e
c
u
rit
y
a
n
d
p
riv
a
c
y
issu
e
s
,
”
T
EL
KOM
NIKA
T
e
lec
o
mm
u
n
ic
a
ti
o
n
C
o
mp
u
ti
n
g
El
e
c
tro
n
ics
a
n
d
Co
n
tro
l
.,
v
o
l.
1
2
,
n
o
.
4
,
p
p
.
7
5
1
-
7
5
2
,
2
0
1
4
.
[
5
]
C.
W
a
n
g
,
Co
n
g
,
"
P
riv
a
c
y
-
p
re
se
r
v
in
g
P
u
b
li
c
A
u
d
it
in
g
f
o
r
Da
ta
S
to
ra
g
e
S
e
c
u
rit
y
in
Clo
u
d
Co
m
p
u
ti
n
g
,"
In
f
o
c
o
m
,
2
0
1
0
P
ro
c
e
e
d
in
g
s IE
EE
,
2
0
1
0
[
6
]
O.
T
e
n
e
a
n
d
J.
P
o
l
o
n
e
tsk
y
,
"
Big
d
a
ta
f
o
r
a
ll
:
P
riv
a
c
y
a
n
d
Us
e
r
C
o
n
tr
o
l
in
t
h
e
A
g
e
o
f
A
n
a
l
y
ti
c
s
,"
Nw
.
J.
T
e
c
h
.
&
In
tell.
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,
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201
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2882
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8
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I.
Ru
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ste
in
,
“
Big
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ta
:
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d
o
f
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Ne
w
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e
g
in
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?
,
”
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tern
a
ti
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n
a
l
Da
ta
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riv
a
c
y
L
a
w
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rt
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c
o
m
in
g
),
12
-
5
6
,
2
0
1
3
[
9
]
B.
D.
JA
M
ES
,
“
S
e
c
u
rit
y
a
n
d
P
riv
a
c
y
Ch
a
ll
e
n
g
e
s
in
Clo
u
d
C
o
m
p
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ti
n
g
En
v
iro
n
m
e
n
ts
,”
2
0
1
0
[
1
0
]
A
.
Ka
tal,
M
.
W
a
z
id
,
a
n
d
R.
H.
G
o
u
d
a
r,
"
Big
Da
ta
:
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u
e
s,
Ch
a
ll
e
n
g
e
s,
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d
G
o
o
d
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ra
c
ti
c
e
s,
"
Co
n
tem
p
o
ra
r
y
Co
m
p
u
ti
n
g
(IC3
),
S
ix
th
In
tern
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
.
IEE
E,
2
0
1
3
.
[
1
1
]
L
.
S
w
e
e
n
e
y
,
"
K
-
A
n
o
n
y
m
it
y
:
A
M
o
d
e
l
f
o
r
P
ro
tec
ti
n
g
P
riv
a
c
y
,”
I
n
tern
a
ti
o
n
a
l
Jo
u
r
n
a
l
o
f
Un
c
e
rtain
ty
,
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u
z
z
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a
n
d
Kn
o
w
led
g
e
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d
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1
0
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0
5
,
p
p
.
5
5
7
-
5
7
0
,
2
0
0
2
[
1
2
]
I.
Ha
sh
e
m
,
A
.
T
a
r
g
io
,
"
T
h
e
Ri
se
o
f
“
Big
Da
ta
”
o
n
Clo
u
d
Co
m
p
u
ti
n
g
:
Re
v
ie
w
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n
d
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e
n
Re
se
a
rc
h
Iss
u
e
s
,"
In
f
o
rm
a
ti
o
n
S
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ste
m
s,
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o
l.
4
7
,
p
p
.
9
8
-
1
1
5
,
2
0
1
5
[
1
3
]
“
5
Ha
d
o
o
p
S
e
c
u
rit
y
P
ro
jec
ts”
,
h
tt
p
s://
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w
.
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p
len
ty
.
c
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m
/b
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/2
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4
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h
a
d
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o
p
-
se
c
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y
-
p
ro
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ts/
[
1
4
]
L
.
X
u
,
C.
Jia
n
g
,
J.
W
a
n
g
,
J.
Y
u
a
n
a
n
d
Y.
Re
n
,
"
In
f
o
r
m
a
ti
o
n
S
e
c
u
rit
y
in
Big
D
a
ta:
P
riv
a
c
y
a
n
d
Da
ta
M
in
in
g
,
"
in
IEE
E
Acc
e
ss
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l.
2
,
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o
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,
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p
.
1
1
4
9
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1
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6
,
2
0
1
4
.
[
1
5
]
J.
Hu
a
n
d
A
.
V
.
V
a
silak
o
s,
"
En
e
rg
y
Bi
g
Da
ta
A
n
a
l
y
ti
c
s
a
n
d
S
e
c
u
rit
y
:
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a
ll
e
n
g
e
s
a
n
d
Op
p
o
rtu
n
it
ies
,
"
in
IEE
E
T
ra
n
sa
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ti
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s
o
n
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m
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rt Grid
,
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l.
7
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p
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2
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2
3
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4
3
6
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2
0
1
6
.
[
1
6
]
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Ya
n
,
W
.
Din
g
,
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.
Yu
,
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Z
h
u
a
n
d
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De
n
g
,
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d
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p
li
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ti
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o
n
E
n
c
ry
p
ted
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Da
ta
in
Clo
u
d
,
"
in
IEE
E
T
ra
n
sa
c
ti
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n
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g
Da
t
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1
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6
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[
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7
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L
.
X
u
,
C.
Jia
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g
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C
h
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n
,
J.
W
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n
g
a
n
d
Y.
Re
n
,
"
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F
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w
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r
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n
d
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ly
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rv
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ti
o
n
T
e
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n
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s in
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ig
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ta M
in
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g
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ter
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2
,
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p
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5
4
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2
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b
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2
0
1
6
.
[
1
8
]
K.
L
ian
g
,
W
.
S
u
silo
a
n
d
J.
K.
Li
u
,
"
P
riv
a
c
y
-
P
re
se
rv
in
g
Cip
h
e
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t
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g
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n
tr
o
l
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r
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ta
S
to
ra
g
e
,
"
in
IEE
E
T
ra
n
sa
c
ti
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n
s I
n
fo
rm
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ti
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re
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sic
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rity
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l.
1
0
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n
o
.
8
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p
p
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1
5
7
8
-
1
5
8
9
,
A
u
g
.
2
0
1
5
.
[
1
9
]
C.
P
e
re
ra
,
R.
Ra
n
jan
,
L
.
W
a
n
g
,
S
.
U.
K
h
a
n
a
n
d
A
.
Y.
Z
o
m
a
y
a
,
"
Big
Da
ta
P
riv
a
c
y
in
th
e
I
n
tern
e
t
o
f
T
h
in
g
s
Era,"
in
IT
Pro
fes
sio
n
a
l
,
v
o
l.
1
7
,
n
o
.
3
,
p
p
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3
2
-
3
9
,
M
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y
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Ju
n
e
2
0
1
5
.
[
2
0
]
B.
Ne
d
e
lcu
,
"
A
b
o
u
t
Big
Da
ta
a
n
d
it
s
C
h
a
ll
e
n
g
e
s
a
n
d
Be
n
e
f
it
s
in
M
a
n
u
f
a
c
tu
rin
g
."
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tab
a
se
S
y
ste
m
s
Jo
u
rn
a
l
4
,
n
o
.
3
,
p
p
.
10
-
1
9
,
2
0
1
3
[
2
1
]
B.
M
.
G
a
ff
,
H.
E.
S
u
ss
m
a
n
,
a
n
d
J.
G
e
e
tt
e
r,
"
P
riv
a
c
y
a
n
d
Big
Da
ta
."
Co
m
p
u
ter
4
7
,
n
o
.
6
,
p
p
.
7
-
9
,
2
0
1
4
[
2
2
]
A
.
A
.
Cá
rd
e
n
a
s,
P
.
K.
M
a
n
a
d
h
a
t
a
a
n
d
S
.
P
.
Ra
jan
,
"
Big
Da
ta
A
n
a
l
y
ti
c
s
f
o
r
S
e
c
u
rit
y
,
"
in
IEE
E
S
e
c
u
rity
&
Priva
c
y
,
v
o
l.
1
1
,
n
o
.
6
,
p
p
.
7
4
-
7
6
,
No
v
.
-
De
c
.
2
0
1
3
.
[
2
3
]
S
.
Yu
;
M
.
L
iu
;
W
.
Do
u
;
X
.
L
iu
;
S
.
Zh
o
u
,
"
Ne
tw
o
rk
in
g
f
o
r
Big
Da
ta:
A
S
u
rv
e
y
,
"
in
IEE
E
Co
m
m
u
n
ica
ti
o
n
s
S
u
rv
e
y
s
&
T
u
to
rials
,
v
o
l.
P
P
,
n
o
.
9
9
,
p
p
.
1
-
1
,
2
0
1
6
[
2
4
]
J.
Ba
e
k
,
Q.
H.
V
u
,
J.
K.
L
iu
,
X.
Hu
a
n
g
a
n
d
Y.
X
ian
g
,
"
A
S
e
c
u
re
Clo
u
d
Co
m
p
u
ti
n
g
Ba
se
d
F
ra
m
e
w
o
rk
f
o
r
Big
Da
ta
In
f
o
rm
a
ti
o
n
M
a
n
a
g
e
m
e
n
t
o
f
S
m
a
rt
G
rid
,
"
in
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Cl
o
u
d
C
o
mp
u
ti
n
g
,
v
o
l.
3
,
n
o
.
2
,
p
p
.
2
3
3
-
2
4
4
,
A
p
ril
-
Ju
n
e
1
2
0
1
5
.
[
2
5
]
X
in
h
u
a
Do
n
g
,
R
u
ix
u
a
n
L
i,
He
n
g
He
,
W
a
n
w
a
n
Zh
o
u
,
Z
h
e
n
g
y
u
a
n
X
u
e
a
n
d
Ha
o
W
u
,
"
S
e
c
u
re
S
e
n
sit
iv
e
Da
ta
S
h
a
rin
g
o
n
a
Big
Da
ta
P
latf
o
rm
,
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in
T
sin
g
h
u
a
S
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c
e
a
n
d
T
e
c
h
n
o
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y
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l
.
2
0
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n
o
.
1
,
p
p
.
7
2
-
8
0
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F
e
b
.
2
0
1
5
.
[
2
6
]
Z.
F
u
,
J.
S
h
u
,
X
.
S
u
n
a
n
d
N.
L
in
g
e
,
"
S
m
a
rt
Clo
u
d
S
e
a
rc
h
S
e
rv
ice
s
:
V
e
rif
iab
le
Ke
y
wo
rd
-
b
a
se
d
S
e
m
a
n
ti
c
S
e
a
rc
h
Ov
e
r
En
c
r
y
p
ted
Clo
u
d
Da
ta
,
"
in
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Co
n
su
me
r
El
e
c
tro
n
ics
,
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l.
6
0
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o
.
4
,
p
p
.
7
6
2
-
7
7
0
,
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v
.
2
0
1
4
[
2
7
]
S
.
Ha
m
e
e
d
a
n
d
U.
A
li
,
"
E
ff
ic
a
c
y
o
f
L
iv
e
DD
o
S
De
te
c
ti
o
n
w
it
h
H
a
d
o
o
p
,
"
NOM
S
2
0
1
6
-
2
0
1
6
IEE
E/
IFI
P
Ne
two
rk
Op
e
ra
ti
o
n
s a
n
d
M
a
n
a
g
e
me
n
t
S
y
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siu
m
,
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n
b
u
l,
2
0
1
6
,
p
p
.
4
8
8
-
4
9
4
.
[
2
8
]
A
.
S
.
Jo
se
a
n
d
B.
A
.
,
"
A
u
to
m
a
ti
c
De
tec
ti
o
n
a
n
d
Re
c
ti
f
ica
ti
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o
f
DN
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f
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ti
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n
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p
li
f
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o
n
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tt
a
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k
s
w
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h
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d
o
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M
a
p
Re
d
u
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e
a
n
d
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u
k
w
a
,
"
2
0
1
4
Fo
u
rt
h
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
A
d
v
a
n
c
e
s
in
C
o
mp
u
ti
n
g
a
n
d
C
o
mm
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n
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a
ti
o
n
s
,
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c
h
in
,
2
0
1
4
,
p
p
.
1
9
5
-
1
9
8
.
[
2
9
]
H.
Ch
e
n
g
,
C.
R
o
n
g
,
K.
Hw
a
n
g
,
W
.
W
a
n
g
a
n
d
Y.
L
i,
"
S
e
c
u
re
Big
Da
ta
S
to
ra
g
e
a
n
d
S
h
a
rin
g
S
c
h
e
m
e
f
o
r
Clo
u
d
T
e
n
a
n
ts
,
"
in
Ch
in
a
C
o
mm
u
n
ica
ti
o
n
s
,
v
o
l
.
1
2
,
n
o
.
6
,
p
p
.
1
0
6
-
1
1
5
,
J
u
n
e
2
0
1
5
.
[
3
0
]
M
.
L
i,
C.
Ya
n
g
a
n
d
J.
T
ian
,
"
V
i
d
e
o
S
e
lec
ti
v
e
En
c
ry
p
ti
o
n
Ba
se
d
o
n
Ha
d
o
o
p
P
latf
o
rm
,
"
2
0
1
5
IEE
E
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Co
m
p
u
t
a
ti
o
n
a
l
In
t
e
ll
ig
e
n
c
e
&
Co
mm
u
n
ica
ti
o
n
T
e
c
h
n
o
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