One topic of interest in
web privacy involves social engineering SPAM. With more users creating visible
profiles for social media, web 2.0, and other web devices, social engineering
becomes a real threat to identity theft. With thousands of web bots and web
spiders crawling social media and other sites, SPAMers can collect a plethora
of information about an individual. For instance, an unprotected Facebook
account can provide the individual's email address, birth date, hometown,
siblings, parents, relationship status, favorite music, favorite movies and
much more. An intelligent SPAMer could collect this information in a database
and sell it to telemarketers or worse yet email SPAM to collect usernames and
passwords. With the properly written program, a SPAMer could collect a lot of
valuable content that could lead to bank accounts, confidential material, and
much more.
Unfortunately, many
users are not educated enough to identify a SPAM email from a real email. Thus,
they email the SPAMer usernames and passwords. Many accounts from financial to
email have been hacked using this method. As the number of users grow on the
Internet, the number of opportunities increase to exploit the user's private
information.
To help combat SPAM,
many entities integrate a SPAM filter in their network to block SPAM from
reaching their end users. Almost all SPAM filters require an annual maintenance
agreement that supplies the entities with frequent upgrades to combat all the
new SPAM techniques that pop up every day. In order to ward off the SPAM
attacks, SPAM filter companies must create complex algorithms to determine if
emails or texts are SPAM or a legitimate message. A research question that has
both academic and practitioner merit involves discovering and creating the most
effective algorithm for capturing SPAM messages. What is the best way to
prevent SPAM from reaching the end users of a network?
Reference
Social Engineering:
Security Through Education. Retrieved on January 2, 2012 from http://www.social-engineer.org/.
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