549 research outputs found
Solutions to Detect and Analyze Online Radicalization : A Survey
Online Radicalization (also called Cyber-Terrorism or Extremism or
Cyber-Racism or Cyber- Hate) is widespread and has become a major and growing
concern to the society, governments and law enforcement agencies around the
world. Research shows that various platforms on the Internet (low barrier to
publish content, allows anonymity, provides exposure to millions of users and a
potential of a very quick and widespread diffusion of message) such as YouTube
(a popular video sharing website), Twitter (an online micro-blogging service),
Facebook (a popular social networking website), online discussion forums and
blogosphere are being misused for malicious intent. Such platforms are being
used to form hate groups, racist communities, spread extremist agenda, incite
anger or violence, promote radicalization, recruit members and create virtual
organi- zations and communities. Automatic detection of online radicalization
is a technically challenging problem because of the vast amount of the data,
unstructured and noisy user-generated content, dynamically changing content and
adversary behavior. There are several solutions proposed in the literature
aiming to combat and counter cyber-hate and cyber-extremism. In this survey, we
review solutions to detect and analyze online radicalization. We review 40
papers published at 12 venues from June 2003 to November 2011. We present a
novel classification scheme to classify these papers. We analyze these
techniques, perform trend analysis, discuss limitations of existing techniques
and find out research gaps
Characterizing Pedophile Conversations on the Internet using Online Grooming
Cyber-crime targeting children such as online pedophile activity are a major
and a growing concern to society. A deep understanding of predatory chat
conversations on the Internet has implications in designing effective solutions
to automatically identify malicious conversations from regular conversations.
We believe that a deeper understanding of the pedophile conversation can result
in more sophisticated and robust surveillance systems than majority of the
current systems relying only on shallow processing such as simple word-counting
or key-word spotting.
In this paper, we study pedophile conversations from the perspective of
online grooming theory and perform a series of linguistic-based empirical
analysis on several pedophile chat conversations to gain useful insights and
patterns. We manually annotated 75 pedophile chat conversations with six stages
of online grooming and test several hypothesis on it. The results of our
experiments reveal that relationship forming is the most dominant online
grooming stage in contrast to the sexual stage. We use a widely used
word-counting program (LIWC) to create psycho-linguistic profiles for each of
the six online grooming stages to discover interesting textual patterns useful
to improve our understanding of the online pedophile phenomenon. Furthermore,
we present empirical results that throw light on various aspects of a pedophile
conversation such as probability of state transitions from one stage to
another, distribution of a pedophile chat conversation across various online
grooming stages and correlations between pre-defined word categories and online
grooming stages
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