E-commerce, smartphones, and social networks provide numerous benefits but require users to disclose personal information and, in some cases, behavior patterns such as purchasing histories.
However, users fear things like identity theft, price discrimination, and leaving negative impressions. They solve the problem by making trade-offs. For example, they might reveal only part—not all—of the information being asked of them.
“Past research has shown that these privacy decisions are inherently difficult, and people aren’t very good at them,” writes Bart P. Knijnenburg of Clemson University.
In his article “Privacy? I Can’t Even! Making a Case for User-Tailored Privacy” published in the July/August 2017 issue of IEEE Security & Privacy, Knijnenburg proposes a user-tailored privacy approach that makes privacy decisions less burdensome by giving users the right kind of information and the right amount of control so as to be useful but not overwhelming or misleading. (Login may be required for full text.)
About Lori Cameron
Lori Cameron is a Senior Writer for the IEEE Computer Society and currently writes regular features for Computer magazine, Computing Edge, and the Computing Now and Magazine Roundup websites. Contact her at l.cameron@computer.org. Follow her on LinkedIn.
