Return-Path: Delivered-To: diana@transocean.com Received: from vps.transocean.com by vps.transocean.com (Dovecot) with LMTP id 8dT/DeSd0lhOeAAAInt2oQ for ; Wed, 22 Mar 2017 08:53:08 -0700 Return-path: Envelope-to: diana@transocean.com Delivery-date: Wed, 22 Mar 2017 08:53:08 -0700 Received: from ip7.ip-144-217-178.net ([144.217.178.7]:44691 helo=dcpwg.com) by vps.transocean.com with esmtp (Exim 4.88) (envelope-from ) id 1cqiZO-00089X-8L for diana@transocean.com; Wed, 22 Mar 2017 08:53:08 -0700 Date: Wed, 22 Mar 2017 11:50:37 -0400 Message-ID: <1upiM12948073TDX6dnHGcYWvjlo50f.ArR2StO97hU@smtp-bin.dcpwg.com> From: Christian Harmon Priority: Normal Mime-Version: 1 Reply-To: christian.harmon@dcpwg.com Content-transfer-encoding: 8bit Content-Type: text/html; charset=UTF-8 Organization: WD Prod INC To: diana@transocean.com X-Spam-Status: Yes, score=4.8 X-Spam-Score: 48 X-Spam-Bar: ++++ X-Spam-Report: Spam detection software, running on the system "vps.transocean.com", has identified this incoming email as possible spam. The original message has been attached to this so you can view it or label similar future email. If you have any questions, see root\@localhost for details. Content preview: Home I wanted to try and visualize some multi-dimensional data and found some interesting sets at the UCI Machine Learning Repository, from an academic study on user verification using biometric walking patterns. The x, y and z dimension accelerometer outputs can be displayed with three graphs and by using a heat-trace over time a distinct signature for each user is plotted. The smartphone in your pocket can do more than just register your position with GPS or wifi (and send it back to who knows who?), most these days have built in accelerometers that can measure change in movement in three axes. In the study visualized below mobile phones were placed in the users' breastpockets and a simple course followed while data from the phone's accelerometers was recorded. The red, green and blue dots show a heat-trace for three individuals of accelerometer output over the time-trial, clearly showing their individual 'walking signature'. One thing to note is that once the powers that be have your walking signature, short of cutting off a leg or wearing very high heels, just changing your phone will not stop them being able to track you, as long as the accelerometers are communicating with base. These biometric signatures that append to the person, not the device, are potentially far more intrusive than conventional tracking-devices and the like. Have Trouble Using Stairs? [...] Content analysis details: (4.8 points, 3.0 required) pts rule name description ---- ---------------------- -------------------------------------------------- 0.0 URIBL_BLOCKED ADMINISTRATOR NOTICE: The query to URIBL was blocked. See http://wiki.apache.org/spamassassin/DnsBlocklists#dnsbl-block for more information. [URIs: dcpwg.com] -0.0 SPF_PASS SPF: sender matches SPF record -0.0 SPF_HELO_PASS SPF: HELO matches SPF record 0.0 HTML_MESSAGE BODY: HTML included in message 0.0 HTML_FONT_LOW_CONTRAST BODY: HTML font color similar or identical to background 0.7 MIME_HTML_ONLY BODY: Message only has text/html MIME parts 0.8 BAYES_50 BODY: Bayes spam probability is 40 to 60% [score: 0.5000] 1.9 RAZOR2_CF_RANGE_E8_51_100 Razor2 gives engine 8 confidence level above 50% [cf: 100] 0.9 RAZOR2_CHECK Listed in Razor2 (http://razor.sf.net/) 0.5 RAZOR2_CF_RANGE_51_100 Razor2 gives confidence level above 50% [cf: 100] X-Spam-Flag: YES Subject: ****SPAM**** Seniors >> Do you dread climbing stairs? The joint pain, the fear of falling? Home I wanted to try and visualize some multi-dimensional data and found some interesting sets at the UCI Machine Learning Repository, from an academic study on user verification using biometric walking patterns. The x, y and z dimension accelerometer outputs can be displayed with three graphs and by using a heat-trace over time a distinct signature for each user is plotted. The smartphone in your pocket can do more than just register your position with GPS or wifi (and send it back to who knows who?), most these days have built in accelerometers that can measure change in movement in three axes. In the study visualized below mobile phones were placed in the users' breastpockets and a simple course followed while data from the phone's accelerometers was recorded. The red, green and blue dots show a heat-trace for three individuals of accelerometer output over the time-trial, clearly showing their individual 'walking signature'. One thing to note is that once the powers that be have your walking signature, short of cutting off a leg or wearing very high heels, just changing your phone will not stop them being able to track you, as long as the accelerometers are communicating with base. These biometric signatures that append to the person, not the device, are potentially far more intrusive than conventional tracking-devices and the like.
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