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Monthly Archives: October 2012

PlaceRaider: A government smartphone spyware?

03 Wednesday Oct 2012

Posted by egarcia in Homeland Security, Human-Computer Interaction

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PlaceRaider has been called a government spyware for smartphones. Expect copycats soon. Download the PlaceRaider article.

The abstract says:

“As smartphones become more pervasive, they are increasingly targeted by malware. At the same time, each new generation of smartphone features increasingly powerful onboard sensor suites. A new strain of `sensor malware’ has been developing that leverages these sensors to steal information from the physical environment | e.g., researchers have recently demonstrated how malware can `listen’ for spoken credit card numbers through the microphone, or `feel’ keystroke vibrations using the accelerometer. Yet the possibilities of what malware can `see’ through a camera have been understudied.”

“This paper introduces a novel `visual malware’ called PlaceRaider, which allows remote attackers to engage in remote reconnaissance and what we call \virtual theft.” Through completely opportunistic use of the phone’s camera and other sensors, PlaceRaider constructs rich, three dimensional models of indoor environments. Remote burglars can thus `download’ the physical space, study the environment carefully, and steal virtual objects from the environment (such as nancial documents, information on computer monitors, and personally identi able information). Through two human subject studies we demonstrate the e ectiveness of using mobile devices as powerful surveillance and virtual theft platforms, and we suggest several possible defenses against visual malware.”

A Quantile-Quantile (Q-Q) Plot Tutorial in Excel

02 Tuesday Oct 2012

Posted by egarcia in Data Mining, Statistics and Mathematics

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Although no data set is exactly normally distributed, most statistical analyses require that the data be approximately normally distributed for their findings to be valid. One way of testing for normality is through a quantile-quantile (q-q) plot, a technique for determining if data sets originate from populations with a common distribution.

In this tutorial, you will determine if a data set is normally distributed by comparing its quantiles against those of a theoretical normal distribution. You will also learn how to make a data set nearly normally distributed.

http://www.miislita.com/statistics/quantile-quantile-plot-tutorial.pdf

Oct 3, 2012 Update: I’ve added a new figure to the article and reworked few lines.

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