Detecting malicious profiles in Twitter
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Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2099.1/16512
Tipus de documentProjecte Final de Màster Oficial
Data2012-09-13
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
:
Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
The
popularity
of
Social
Networks
during
the
last
years
has
caught
the
attention
of
cybercriminals
for
the
distribution
of
Spam
and
malicious
contents.
In
order
to
do
that,
they
create
fake
profiles
to
send
spam
messages
to
legitimate
users,
leading
to
fraud
or
malware
campaigns.
Sometimes
cybercriminals
use
stolen
accounts
of
legitimate
users
to
send
these
malicious
messages.
The
goal
of
this
work
is
to
use
information
available
for
any
user
to
detect
malicious
profiles
in
Twitter,
the
second
most
popular
Social
Network
in
the
world.
Also
we
explore
the
possibility
of
distinguishing
into
different
kind
of
malicious
profiles:
spammers
and
hacked
accounts.
We
show
how
it
is
possible
to
obtain
a
set
of
features
derived
from
the
public
information
available
in
order
to
correctly
classify
malicious
and
clean
profiles
with
a
success
rate
over
90%.
We
show,
also,
how
the
same
method
could
be
used
to
detect
hacked
profiles
with
similar
results.
Based
on
these
results,
we
propose
a
global
system
that
could
use
both
local
and
global
information
for
improved
results
in
the
detection
of
malicious
profiles.
MatèriesComputer crimes, Online social networks, Computer security, Delictes informàtics, Xarxes socials en línia, Seguretat informàtica
TitulacióMÀSTER UNIVERSITARI EN INTEL·LIGÈNCIA ARTIFICIAL (Pla 2009)
Col·leccions
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
VDIAZ.MT_DetectingMaliciousProfilesTwitter.pdf | 3,241Mb | Visualitza/Obre |