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This book begins with a broader discussion of cybercrime and
attacks targeting ATMs and then focuses on a specific type of
cybercrime named "ATM Hacking." It discusses ATM Hacking from a
more full scope of aspects, including technology, modus operandi,
law enforcement, socio-economic and geopolitical context, and
theory development. After unpacking a classic case of ATM Hacking
and its modus operandi, implications for cybersecurity and
prevention, intra- and inter-agency collaboration, and theory
development are presented. This book also demonstrates the analysis
of extensive qualitative data collected from a high-profile case in
which European criminal group hacked into a London voice mail
server belonging to a Taiwanese financial institution - First
Commercial Bank,. Then it programmed dozens of ATMs to "spit out"
millions of dollars of cash. The successful crackdown on this type
of crime is rare, if not unique, while the number of similar crimes
has increased enormously in recent years and the trend seem to
continue unabatingly. Further, the implications go beyond a country
or a continent. Intra- and inter-agency collaboration among players
of law enforcement is essential to the case especially in the
police context of "turf jealousies." The authors seek to document
the ways in which agencies collaborate, as well as the perceived
benefits and challenges of cooperation. Whether the broader
political and contextual climates in which these agencies operate,
limit the extent to which they can cooperate. This book is useful
as a reference for researchers and professionals working in the
area of cybercrime and cybersecurity. University professors can
also use this book as a case study for senior seminars or graduate
courses.
Leveraging Biomedical and Healthcare Data: Semantics, Analytics and
Knowledge provides an overview of the approaches used in semantic
systems biology, introduces novel areas of its application, and
describes step-wise protocols for transforming heterogeneous data
into useful knowledge that can influence healthcare and biomedical
research. Given the astronomical increase in the number of
published reports, papers, and datasets over the last few decades,
the ability to curate this data has become a new field of
biomedical and healthcare research. This book discusses big data
text-based mining to better understand the molecular architecture
of diseases and to guide health care decision. It will be a
valuable resource for bioinformaticians and members of several
areas of the biomedical field who are interested in understanding
more about how to process and apply great amounts of data to
improve their research.
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