[{"command":"openDialog","selector":"#drupal-modal","settings":null,"data":"\u003Cdiv id=\u0022republish_modal_form\u0022\u003E\u003Cform class=\u0022modal-form-example-modal-form ecl-form\u0022 data-drupal-selector=\u0022modal-form-example-modal-form\u0022 action=\u0022\/en\/article\/modal\/6392\u0022 method=\u0022post\u0022 id=\u0022modal-form-example-modal-form\u0022 accept-charset=\u0022UTF-8\u0022\u003E\u003Cp\u003EHorizon articles can be republished for free under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence.\u003C\/p\u003E\n \u003Cp\u003EYou must give appropriate credit. We ask you to do this by:\u003Cbr \/\u003E\n 1) Using the original journalist\u0027s byline\u003Cbr \/\u003E\n 2) Linking back to our original story\u003Cbr \/\u003E\n 3) Using the following text in the footer: This article was originally published in \u003Ca href=\u0027#\u0027\u003EHorizon, the EU Research and Innovation magazine\u003C\/a\u003E\u003C\/p\u003E\n \u003Cp\u003ESee our full republication guidelines \u003Ca href=\u0027\/horizon-magazine\/republish-our-stories\u0027\u003Ehere\u003C\/a\u003E\u003C\/p\u003E\n \u003Cp\u003EHTML for this article, including the attribution and page view counter, is below:\u003C\/p\u003E\u003Cdiv class=\u0022js-form-item form-item js-form-type-textarea form-item-body-content js-form-item-body-content ecl-form-group ecl-form-group--text-area form-no-label ecl-u-mv-m\u0022\u003E\n \n\u003Cdiv\u003E\n \u003Ctextarea data-drupal-selector=\u0022edit-body-content\u0022 aria-describedby=\u0022edit-body-content--description\u0022 id=\u0022edit-body-content\u0022 name=\u0022body_content\u0022 rows=\u00225\u0022 cols=\u002260\u0022 class=\u0022form-textarea ecl-text-area\u0022\u003E\u003Ch2\u003EThe hidden pattern within your digital camera\u003C\/h2\u003E\u003Cp\u003EEven with the most advanced manufacturing methods, every camera sensor is not created equal.\u003C\/p\u003E\u003Cp\u003EFor example, a 10 megapixel camera sensor has an array of 10 million pixels \u2014 tiny cavities which trap light, turning it into a digital signal \u2014 and each of these can vary in how it measures light.\u003C\/p\u003E\u003Cp\u003EIn an ideal world, photographs of a pure blue sky taken by two identical cameras would be indistinguishable. In reality, this is not the case. The pixel imperfections of a camera\u2019s sensor leave a unique fingerprint on the images it creates, known as sensor pattern noise.\u003C\/p\u003E\u003Cp\u003EThe research enabling the extraction of these weak, but universal traces already emerged in 2006, but several problems remained to be solved. For one, the extracted fingerprints dwarf their original images, hindering large-scale \u003Cspan\u003Esensor pattern noise\u003C\/span\u003E\u0026nbsp;applications due to the brute computational force and extensive storage space required.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESearches\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EBut a team of Italian researchers working on a project named CRISP, developing technology for compressing signals and images in big data, stumbled onto a potential solution.\u003C\/p\u003E\u003Cp\u003EProfessor Enrico Magli, of Politecnico di Torino, is using the compression technology of this project, which was funded with a grant from the EU\u2019s European Research Council (ERC), to streamline the identification of the cameras behind online images.\u003C\/p\u003E\u003Cp\u003EHe launched a separate ERC-funded project, known as ToothPic, in late 2015, to look specifically at the camera identification issue.\u003C\/p\u003E\u003Cp\u003E\u2018What we have in mind with ToothPic is the ability to be able, with a suitably sized data centre, to process millions of pictures per second,\u2019 said Prof. Magli. \u2018What we do is really to make the fingerprint easily searchable and optimised to make it as fast as possible.\u2019\u003C\/p\u003E\u003Cp\u003EPrimarily, ToothPic is zooming in on the potential to verify image copyrights.\u003C\/p\u003E\u003Cp\u003EProf. Magli says copyright infringement is now something of a \u2018national sport\u2019 on photo-based social media websites like Flickr. With more than 350 million pictures also uploaded to Facebook daily, he contends that there needs to be a way to deal with illegal or unethical photo use in this sphere.\u003Cblockquote class=\u0022tw-text-center tw-text-blue tw-font-bold tw-text-2xl lg:tw-w-1\/2 tw-border-2 tw-border-blue tw-p-12 tw-my-8 lg:tw-m-12 lg:tw--ml-16 tw-float-left\u0022\u003E\n \u003Cspan class=\u0022tw-text-5xl tw-rotate-180\u0022\u003E\u201c\u003C\/span\u003E\n \u003Cp class=\u0022tw-font-serif tw-italic\u0022\u003E\u2018What we do is really to make the fingerprint easily searchable and optimised to make it as fast as possible.\u2019\u003C\/p\u003E\n \u003Cfooter\u003E\n \u003Ccite class=\u0022tw-not-italic tw-font-normal tw-text-sm tw-text-black\u0022\u003EProfessor Enrico Magli, Politecnico di Torino, Italy\u003C\/cite\u003E\n \u003C\/footer\u003E\n\u003C\/blockquote\u003E\n\u003C\/p\u003E\u003Cp\u003ETo this end, his team will launch a demonstration search engine this summer, and has a network of about 100 university computers hard at work, downloading 50 million pictures from Flickr.\u003C\/p\u003E\u003Cp\u003EThe demo \u2014 a simple internet app, where people can upload a picture or fingerprint and check if it matches photos in ToothPic\u2019s database \u2014 is hoped to attract the attention of social media heavyweights like Google or Facebook, which could theoretically offer an internet-wide fingerprint search service thanks to their extensive image databases.\u003C\/p\u003E\u003Cp\u003EWhile Prof. Magli notes there are privacy concerns around using this kind of information, he believes such photo fingerprint applications are nothing to be concerned about.\u003C\/p\u003E\u003Cp\u003EToothPic\u2019s technology has already sparked a media forensics collaboration with the Turin Police, while photo marketplaces and photographers seeking their stolen cameras are also interested, he said.\u003C\/p\u003E\u003Cp\u003EThe team will simultaneously launch the software through a startup company, and hopes to add a parallel product by autumn, which uses the \u003Cspan\u003Esensor pattern noise\u003C\/span\u003E\u0026nbsp;from smartphone cameras to offer a simpler alternative to two-step authentication processes like Wi-Fi logins.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EForensics\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EIn the UK, a research and industry consortium named DIVeFor has already proved the worth of \u003Cspan\u003Esensor pattern noise\u003C\/span\u003E\u0026nbsp;technology in criminal forensics, in 2014 helping Sussex Police to secure the first ever conviction using image fingerprints.\u003C\/p\u003E\u003Cp\u003EProfessor Chang-Tsun Li, of the University of Warwick, led the EU-funded project, a major focus of which was developing multimedia \u003Cspan\u003Esensor pattern noise\u003C\/span\u003E\u0026nbsp;extraction technologies. When police arrested a man on suspicion of possessing child pornography and discovered the suspect\u2019s mobile phone held two videos involving children, they turned to Prof. Li\u2019s technology.\u003C\/p\u003E\u003Cp\u003E\u2018Initially, the suspect denied his responsibility, and claimed that the two videos were sent to him by someone else,\u2019 he explained.\u003C\/p\u003E\u003Cp\u003EPolice identified the fingerprint of the smartphone camera, and by comparing this to the fingerprints of the pornographic video stills, found a match strong enough that the man pleaded guilty and was sentenced to nine years in jail.\u003C\/p\u003E\u003Cp\u003EThe professor is now using \u003Cspan\u003Esensor pattern noise\u003C\/span\u003E\u0026nbsp;technology to help Interpol group the 5 million images in its international child exploitation database by source camera. He says this is a much more challenging prospect, because without possessing the original cameras, these images can only be grouped by the similarities between their very weak fingerprints.\u003C\/p\u003E\u003Cp\u003ETo perform the complex task of tying these similarities together, he has had to develop machine learning software \u2014 an artificial intelligence that can recognise patterns and use this information in a way normal modelling cannot.\u003C\/p\u003E\u003Cp\u003EWith the potential of this technology in mind, Prof. Li this year founded the IDENTITY research consortium, with EU Marie Sk\u0142odowska-Curie grant backing. This international effort combines industry and academic partners from 12 European, Asian and American countries, as well as senior forensic police as advisors.\u003C\/p\u003E\u003Cp\u003E\u2018On this project we are not only trying to identify devices, but we also want to use biometric techniques to identify people through physiological and behavioural traits,\u2019 he said.\u003C\/p\u003E\u003Cp\u003E\u2018No matter if you are going to identify devices or identify people, the underlying, enabling technologies are similar \u2014 it\u2019s computer vision, machine learning and pattern recognition. Therefore, whatever technique we develop for device identification can potentially be fine-tuned or modified to serve the purpose of people identification, or vice versa.\u2019\u003C\/p\u003E\u003C\/textarea\u003E\n\u003C\/div\u003E\n\n \u003Cdiv id=\u0022edit-body-content--description\u0022 class=\u0022ecl-help-block description\u0022\u003E\n Please copy the above code and embed it onto your website to republish.\n \u003C\/div\u003E\n \u003C\/div\u003E\n\u003Cinput autocomplete=\u0022off\u0022 data-drupal-selector=\u0022form-biqa5iyco4fbtk609gzf86cfhrawjqplp6wqwhbqtfa\u0022 type=\u0022hidden\u0022 name=\u0022form_build_id\u0022 value=\u0022form-Biqa5iyco4fbTK609gzF86cFHraWJqPLp6wQWHBqTFA\u0022 \/\u003E\n\u003Cinput data-drupal-selector=\u0022edit-modal-form-example-modal-form\u0022 type=\u0022hidden\u0022 name=\u0022form_id\u0022 value=\u0022modal_form_example_modal_form\u0022 \/\u003E\n\u003C\/form\u003E\n\u003C\/div\u003E","dialogOptions":{"width":"800","modal":true,"title":"Republish this content"}}]