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f
wh
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et
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tin
g
o
f
n
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e
f
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with
v
ar
ied
ty
p
e
s
with
o
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t
o
v
er
wr
ite
an
d
n
eg
le
cted
th
e
o
v
er
wr
ite
d
ata.
Mo
r
eo
v
e
r
,
th
is
p
ap
er
f
o
u
n
d
a
f
ew
s
tu
d
ies
th
at
in
v
esti
g
ate
d
ata
r
ec
o
v
er
y
alg
o
r
i
th
m
s
an
d
ig
n
o
r
e
th
e
tim
e
f
ac
to
r
(
s
p
ee
d
)
i
n
r
esear
ch
av
ail
ab
le
in
th
is
f
ield
.
On
th
e
o
th
e
r
h
an
d
,
alg
o
r
ith
m
s
d
ev
el
o
p
ed
wi
th
o
th
er
alg
o
r
ith
m
s
wer
e
n
o
t
co
m
p
a
r
ed
.
I
n
th
is
p
ap
er
,
th
is
s
tu
d
y
in
tr
o
d
u
ce
d
a
p
r
ac
tical
an
d
ef
f
ec
tiv
e
c
o
m
p
a
r
is
o
n
b
etwe
en
d
ata
r
etr
iev
al
a
lg
o
r
ith
m
s
(
d
ata
r
ec
o
v
er
y
u
s
in
g
A
ho
-
C
o
r
asick
alg
o
r
ith
m
,
lo
g
ical
d
ata
r
ec
o
v
er
y
al
g
o
r
ith
m
)
an
d
th
r
ee
d
atasets
(
DF
R
-
0
9
[
2
5
]
,
T
5
co
r
p
u
s
with
o
u
t
o
v
er
wr
ite,
T
5
co
r
p
u
s
with
o
v
er
wr
ite
)
b
ased
o
n
th
e
NT
FS
f
ile
s
y
s
tem
,
to
d
eter
m
in
e
th
eir
ef
f
icien
c
y
a
n
d
th
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ab
ilit
y
to
r
ec
o
v
er
d
ele
ted
d
ata
in
th
e
s
h
o
r
test
p
o
s
s
ib
le
tim
e
an
d
with
th
e
g
r
ea
test
p
o
s
s
ib
le
ef
f
ec
tiv
en
ess
f
r
o
m
s
to
r
ag
e
d
e
v
ices
u
s
in
g
v
is
u
al
s
tu
d
io
C
p
r
o
g
r
am
m
in
g
lan
g
u
a
g
e.
T
h
is
co
m
p
ar
is
o
n
will
clea
r
ly
s
h
o
w
t
h
e
s
tr
en
g
th
s
an
d
wea
k
n
ess
es
o
f
ea
ch
o
f
th
e
alg
o
r
ith
m
s
p
r
e
s
en
ted
,
wh
ich
is
a
k
ey
p
o
i
n
t
i
n
t
h
e
d
e
v
e
l
o
p
m
e
n
t
o
f
t
h
e
s
e
a
l
g
o
r
i
t
h
m
s
b
a
s
e
d
o
n
t
h
e
ti
m
e
n
e
e
d
e
d
t
o
r
e
s
t
o
r
e
d
a
t
a
a
n
d
t
h
e
s
i
z
e
o
f
d
a
t
a
r
e
s
t
o
r
e
d
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
Fil
e
r
ec
o
v
er
y
tech
n
i
q
u
es
an
d
t
o
o
ls
ar
e
m
an
y
,
v
ar
ied
a
n
d
ar
e
co
n
s
tan
tly
ev
o
lv
i
n
g
.
E
ac
h
tech
n
iq
u
e
h
as
wea
k
n
ess
es
an
d
s
tr
en
g
th
s
th
at
d
is
tin
g
u
is
h
th
em
f
r
o
m
th
e
r
es
t
o
f
th
e
tech
n
iq
u
es.
T
h
er
e
f
o
r
e,
th
er
e
is
a
q
u
esti
o
n
th
at
alwa
y
s
ask
s
wh
ich
tech
n
iq
u
es
s
h
o
u
ld
b
e
u
s
ed
to
r
esto
r
e
d
ata
as
q
u
ick
ly
an
d
ef
f
icien
tl
y
as
p
o
s
s
ib
le.
T
h
is
s
tu
d
y
s
h
o
wed
th
e
m
o
s
t
im
p
o
r
tan
t
m
o
d
er
n
tech
n
i
q
u
es
an
d
,
in
th
is
s
ec
tio
n
,
in
p
ar
ticu
lar
,
a
m
ec
h
an
is
m
was
d
ev
elo
p
e
d
to
co
m
p
ar
e
th
ese
tech
n
iq
u
es
b
ased
o
n
two
m
ain
v
ar
iab
les:
s
p
ee
d
an
d
ac
cu
r
a
c
y
.
Pro
p
o
s
ed
m
et
h
o
d
th
e
g
en
er
al
a
r
ch
itectu
r
e
o
f
p
r
o
p
o
s
ed
m
eth
o
d
is
illu
s
tr
ated
in
Fig
u
r
e
1
.
Fig
u
r
e
1
.
T
h
e
g
e
n
er
al
ar
ch
itec
tu
r
e
o
f
t
h
e
p
r
o
p
o
s
ed
m
eth
o
d
I
n
Fig
u
r
e
1
we
p
r
o
p
o
s
ed
o
u
r
m
eth
o
d
o
l
o
g
y
to
co
m
p
ar
e
two
alg
o
r
ith
m
s
ac
co
r
d
in
g
ac
cu
r
ac
y
an
d
s
p
ee
d
th
at
ca
n
b
e
d
escr
ib
ed
in
s
ev
e
r
a
l step
s
as f
o
llo
ws:
a.
I
n
p
u
t
s
tag
e
Du
r
in
g
t
h
is
p
h
ase,
t
h
r
ee
d
if
f
er
en
t
d
ata
s
ets
will
b
e
lo
ad
ed
,
a
n
d
th
e
co
n
ten
ts
an
d
s
ize
o
f
ea
ch
d
ata
s
et
will
b
e
r
ec
o
r
d
ed
.
T
h
is
s
tu
d
y
,
t
h
r
ee
d
ata
s
ets
wer
e
s
elec
ted
th
at
in
clu
d
ed
d
if
f
e
r
en
t
ty
p
es
o
f
d
ata
in
d
if
f
er
en
t
s
izes
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76
to
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r
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th
e
o
v
er
wr
ite
d
ata.
T
h
e
r
ef
o
r
e
,
th
e
f
o
cu
s
o
f
t
h
is
r
esear
ch
was
o
n
th
e
tim
e
n
ee
d
ed
t
o
r
ec
o
v
er
d
ata
t
h
r
o
u
g
h
th
e
s
u
g
g
ested
s
p
ee
d
cr
iter
io
n
an
d
to
ad
d
r
ess
th
e
o
v
er
wr
ite
ca
s
es
o
f
d
elete
d
d
ata.
As
ca
n
b
e
s
e
en
in
th
is
r
esear
ch
,
th
e
s
tu
d
y
o
f
th
e
ef
f
ec
tiv
en
ess
o
f
two
o
f
th
e
latest
alg
o
r
ith
m
s
d
ev
elo
p
ed
in
th
e
f
ield
o
f
r
etr
i
ev
in
g
f
iles
d
elete
d
f
r
o
m
t
h
e
NT
FS
f
ile
s
y
s
tem
,
wh
ile
th
e
p
r
e
v
io
u
s
s
tu
d
ies
w
er
e
lim
ited
to
s
tu
d
y
o
n
th
e
e
f
f
ec
tiv
en
ess
o
f
o
n
e
alg
o
r
ith
m
o
n
ly
.
On
th
e
o
t
h
er
h
an
d
,
t
h
e
alg
o
r
ith
m
s
wer
e
s
tu
d
i
ed
ac
co
r
d
in
g
to
th
e
tim
e
an
d
a
cc
u
r
ac
y
f
ac
to
r
s
.
T
h
e
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
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o
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p
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t E
l Co
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o
l
C
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mp
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o
n
o
f d
a
ta
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ec
o
ve
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y
t
ec
h
n
iq
u
es o
n
ma
s
ter file ta
b
le
b
etw
ee
n
… (
Hu
s
s
ein
I
s
ma
el
S
a
h
ib
)
77
tim
e
cr
iter
io
n
was
n
eg
lecte
d
d
u
r
in
g
th
e
p
r
ev
io
u
s
r
esear
ch
,
k
n
o
win
g
t
h
at
th
e
s
p
ee
d
o
f
p
er
f
o
r
m
an
ce
is
o
n
e
o
f
t
h
e
m
o
s
t
im
p
o
r
tan
t
f
ac
to
r
s
in
th
e
f
ield
o
f
d
ig
ital
in
v
esti
g
at
io
n
.
On
th
e
o
th
er
h
an
d
,
b
o
th
o
f
th
e
two
alg
o
r
ith
m
s
ar
e
u
n
ab
le
to
d
eter
m
in
e
th
e
u
n
d
a
m
ag
ed
f
ile
an
d
r
esto
r
ed
o
n
l
y
,
wh
er
e
b
o
th
o
f
th
em
r
ec
o
v
er
ed
f
iles
d
estru
ctiv
e
an
d
non
-
r
e
ad
ab
le.
I
n
ad
d
itio
n
to
t
h
at
b
o
th
alg
o
r
ith
m
s
ca
n
n
o
t
d
e
ter
m
in
e
if
th
e
f
ile
is
co
m
p
lete
ly
d
estro
y
ed
o
r
ca
n
r
etr
iev
e
in
f
o
r
m
atio
n
s
u
c
h
as im
ag
es o
r
s
h
o
r
t a
u
d
io
clip
s
o
r
e
v
en
tex
t c
lip
s
.
4.
CO
NCLU
SI
O
N
I
n
th
is
p
ap
er
,
th
r
ee
d
if
f
er
en
t d
ata
s
ets
wer
e
u
s
ed
.
As
a
r
esu
lt
o
f
th
e
ap
p
licatio
n
o
f
th
r
ee
d
if
f
er
en
t d
ata
s
ets,
th
is
wo
r
k
is
lo
o
k
in
g
in
to
d
esig
n
in
g
a
h
ig
h
ly
ef
f
icien
t
d
ata
r
ec
o
v
er
y
alg
o
r
ith
m
an
d
h
ig
h
er
s
p
ee
d
th
an
th
e
alg
o
r
ith
m
s
b
ein
g
s
tu
d
ied
.
T
h
e
tar
g
et
alg
o
r
ith
m
b
eg
in
s
b
y
r
ea
d
in
g
th
e
MFT
an
d
s
p
ec
if
ies
all
m
etad
ata
f
o
r
ea
ch
f
ile
h
as
an
in
d
ex
in
th
e
m
aster
f
ile
tab
le.
T
h
en
is
th
e
s
elec
tio
n
o
f
th
e
d
am
ag
ed
f
iles
p
ar
tially
o
r
co
m
p
letely
.
I
f
r
esto
r
e
all
f
iles
was
p
r
o
m
p
ted
,
th
e
lo
g
ical
alg
o
r
ith
m
will
b
e
f
o
llo
wed
.
I
f
we
wan
t
to
r
esto
r
e
a
s
p
ec
if
ic
ty
p
e
o
f
d
ata
o
r
a
s
p
ec
if
ic
f
ile,
th
e
Ah
o
-
C
o
r
asick
alg
o
r
ith
m
will
b
e
u
s
ed
to
s
ea
r
ch
f
o
r
an
d
r
ec
o
v
er
y
th
e
r
eq
u
ir
ed
f
iles
.
On
th
e
o
th
er
h
an
d
,
th
e
Ah
o
-
C
o
r
asick
alg
o
r
ith
m
p
r
o
v
ed
f
aster
in
s
ea
r
ch
in
g
an
d
d
eter
m
in
in
g
a
s
p
ec
if
ic
ty
p
e
o
f
f
ile
to
r
etr
iev
e.
T
h
er
ef
o
r
e,
th
e
Ah
o
-
C
o
r
asick
alg
o
r
ith
m
will
b
e
u
s
ed
to
r
etr
iev
e
a
s
p
ec
if
ic
ty
p
e
o
f
d
ata.
I
n
all
ca
s
es,
d
am
ag
ed
f
iles
s
h
o
u
ld
n
o
t
b
e
r
esto
r
ed
wh
ich
lead
s
to
waste
in
tim
e.
I
f
th
e
m
em
o
r
y
is
f
o
r
m
atted
,
th
e
MFT
will
b
e
em
p
ty
an
d
co
n
tain
n
o
in
f
o
r
m
atio
n
.
T
h
e
alg
o
r
ith
m
s
will
f
ail
to
r
ec
o
v
er
an
y
f
ile
s
o
th
at
th
e
alg
o
r
ith
m
s
h
o
u
ld
b
e
ab
le
to
r
etr
iev
e
d
ata
b
ased
o
n
f
ile
s
tr
u
ctu
r
e
s
u
ch
as f
ile
-
ca
r
v
in
g
tech
n
iq
u
es.
ACK
NO
WL
E
DG
E
M
E
NT
S
T
h
e
au
th
o
r
s
g
r
atef
u
lly
ac
k
n
o
wled
g
e
UT
HM
Sch
em
e,
Un
i
v
er
s
iti
Un
iv
er
s
iti
T
u
n
Hu
s
s
ei
n
Ma
lay
s
ia
(
UT
HM
)
,
Dep
ar
tm
en
t
o
f
in
f
o
r
m
atio
n
Secu
r
ity
.
RE
F
E
R
E
NC
E
S
[1
]
M
.
P
a
tan
k
a
r
a
n
d
D.
Bh
a
n
d
a
ri,
“
F
o
re
n
sic
T
o
o
ls
u
se
d
i
n
Dig
i
tal
C
rime
In
v
e
stig
a
ti
o
n
,
”
I
n
d
i
a
n
J
.
Ap
p
l.
Res
.
,
v
o
l.
4
,
n
o
.
5
,
p
p
.
2
7
8
-
2
8
3
,
2
0
1
4
.
[
2
]
S
.
To
m
e
r,
A.
Ap
u
rv
a
,
P
.
Ra
n
a
k
o
ti
,
S
.
Ya
d
a
v
,
a
n
d
N.
R.
Ro
y
,
“
Da
ta rec
o
v
e
ry
in
F
o
re
n
sic
s,”
2
0
1
7
In
t
.
Co
n
f.
C
o
mp
u
t
.
Co
mm
u
n
.
T
e
c
h
n
o
l.
S
ma
rt
Na
ti
o
n
,
IC3
T
S
N
2
0
1
7
,
v
o
l
.
2
0
1
7
,
p
p
.
1
8
8
-
1
9
2
,
2
0
1
8
.
[
3
]
M
.
Al
h
u
ss
e
in
a
n
d
D.
W
ij
e
se
k
e
ra
,
“
A
h
ig
h
ly
re
c
o
v
e
ra
b
le
a
n
d
e
f
ficie
n
t
fil
e
s
y
ste
m
,
”
Pro
c
e
d
i
a
T
e
c
h
n
o
l
.
,
v
o
l.
1
6
,
p
p
.
4
9
1
-
4
9
8
,
2
0
1
4
.
[
4
]
Y.
Yu
so
ff,
R.
Ism
a
il
,
a
n
d
Z.
Ha
ss
a
n
,
“
Co
m
m
o
n
P
h
a
se
s
o
f
Co
m
p
u
ter
F
o
re
n
sic
s
In
v
e
stig
a
ti
o
n
M
o
d
e
ls,”
In
t.
J
.
Co
m
p
u
t
.
S
c
i.
In
f.
T
e
c
h
n
o
l
.
,
v
o
l
.
3
,
n
o
.
3
,
p
p
.
1
7
-
3
1
,
2
0
1
1
.
[
5
]
P
.
A.
S
.
Ka
p
se
,
P
ri
y
a
S
.
P
a
t
il
,
“
S
u
rv
e
y
o
n
Diffe
re
n
t
P
h
a
se
s o
f
Di
g
it
a
l
F
o
re
n
sic
s In
v
e
st
ig
a
ti
o
n
M
o
d
e
ls,”
In
t.
J
.
I
n
n
o
v
.
Res
.
Co
mp
u
t.
C
o
mm
u
n
.
En
g
.
,
v
o
l.
0
3
,
n
o
.
0
3
,
p
p
.
1
5
2
9
-
1
5
3
4
,
2
0
1
5
.
[6
]
F
.
Ha
fe
e
z
,
“
Ro
le
o
f
F
il
e
S
y
ste
m
i
n
Op
e
ra
ti
n
g
S
y
ste
m
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
C
o
mp
u
ter
S
c
ien
c
e
a
n
d
I
n
n
o
v
a
ti
o
n
,
v
o
l.
2
0
1
6
,
p
p
.
1
1
7
-
1
2
7
,
2
0
1
6
.
[7
]
M
.
Ala
z
a
b
,
S
.
Ve
n
k
a
tram
a
n
,
a
n
d
P
.
Watters
,
“
Eff
e
c
ti
v
e
Dig
it
a
l
F
o
re
n
sic
An
a
l
y
sis
o
f
t
h
e
N
TF
S
Disk
Im
a
g
e
,
”
Ub
iq
u
it
o
u
s Co
m
p
u
t
.
Co
mm
u
n
.
J
.
,
v
o
l
.
4
,
n
o
.
3
,
p
p
.
5
5
1
-
5
5
8
,
2
0
0
9
.
[8
]
S
.
Al
-
fe
d
a
g
h
i
a
n
d
B.
Al
-
b
a
b
tain
,
“
M
o
d
e
li
n
g
t
h
e
F
o
re
n
sic
s
P
r
o
c
e
ss
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
S
e
c
u
rity
a
n
d
it
s
Ap
p
li
c
a
ti
o
n
s
,
v
o
l
.
6
,
n
o
.
4
,
p
p
.
9
7
-
1
0
8
,
2
0
1
2
.
[9
]
M
.
Ala
z
a
b
a
n
d
P
.
Watters
,
“
Dig
it
a
l
fo
re
n
sic
tec
h
n
iq
u
e
s
fo
r
sta
ti
c
a
n
a
ly
sis
o
f
NTF
S
ima
g
e
s,”
4
th
In
t
.
C
o
n
f
.
I
n
f.
T
e
c
h
n
o
l
.
ICIT
,
2
0
09
.
[1
0
]
K
.
L
.
R
u
s
b
a
r
s
k
y
a
n
d
K
.
C
i
t
y
,
“
A
F
o
r
e
n
s
i
c
C
o
m
p
a
r
i
s
o
n
o
f
N
T
F
S
a
n
d
F
A
T
3
2
F
i
l
e
S
y
s
t
e
m
s
,
”
M
a
r
s
h
a
l
l
U
n
i
v
.
,
p
.
2
9
,
2
0
1
2
.
[1
1
]
G
.
H.
F
e
ll
o
ws
,
“
Th
e
j
o
y
s
o
f
c
o
m
p
lex
it
y
a
n
d
th
e
d
e
lete
d
fil
e
,
”
Dig
it
.
In
v
e
stig
.
,
v
o
l.
2
,
n
o
.
2
,
p
p
.
8
9
-
9
3
,
2
0
0
5
.
[1
2
]
J.
Da
v
is,
J.
M
a
c
Lea
n
,
a
n
d
D.
Da
m
p
ier,
“
M
e
th
o
d
s o
f
I
n
fo
rm
a
ti
o
n
Hid
in
g
a
n
d
De
tec
ti
o
n
i
n
F
il
e
S
y
st
e
m
s,”
2
0
1
0
Fi
f
t
h
IEE
E
In
t.
W
o
rk
.
S
y
st.
Ap
p
ro
a
c
h
e
s to
Di
g
it
.
Fo
re
n
sic
E
n
g
.
,
v
o
l.
5
,
n
o
.
Ju
n
e
,
p
p
.
6
6
-
6
9
,
2
0
1
0
.
[1
3
]
C.
Zo
u
b
e
k
a
n
d
K.
S
a
c
k
,
“
S
e
lec
ti
v
e
d
e
letio
n
o
f
n
o
n
-
re
lev
a
n
t
d
a
ta,”
Dig
it
.
I
n
v
e
stig
.
,
v
o
l.
2
0
,
p
p
.
S
9
2
–
S
9
8
,
2
0
1
7
.
[1
4
]
S
.
Dill
o
n
,
“
Hid
e
a
n
d
S
e
e
k
:
Co
n
c
e
a
li
n
g
a
n
d
Re
c
o
v
e
rin
g
Ha
rd
Disk
Da
ta,”
J
a
me
s
M
a
d
iso
n
U
n
ive
rs
it
y
In
fo
se
c
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Evaluation Warning : The document was created with Spire.PDF for Python.