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Biometric security
Sébastien Marcel, Research Director at the Idiap Research Institute
Saturday, Sept. 11, 2021 · 5:30 p.m. · 17m 34s
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oh
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good afternoon good evening uh well i'm going to talk about the subject which is um
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a quite different from the fairly different from the ones that we've been
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hearing recently in the last uh our
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so um
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subject is by metrics and in particular biometric security what interest me in particular is
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the security part of the aspect you'll see in a moment what i'm talking about
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oh metrics some well maybe i you haven't heard about it or maybe thought it was a rather
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abstract but most of you have it in your pocket
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because nearly everybody has a mobile phone in that market
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and uh that's a high chance that they will be able
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to uh the carry out facial recognition or um recognise fingerprints
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you've probably being exposed to this just oh for one year ago
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when you were still able to travel freely and uh
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when you were still able to use an automatic good door uh
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and um for possible control and when i'm
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your face was recognised to automatically hope for
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most of your not been exposed to buy metrics in the area of her a crime
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uh i criminality emperor metrics are of course used by uh
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a criminal investigation offices to care tries
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traces left behind by criminals and uh
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taking samples on crime scenes in there by metrics is used as a tool
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so here i have schemata sized in simple terms what tape by metric system is in general
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i'm going to take facial recognition as an example because uh of course we all know what the faces
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when you do facial recognition what does one do want us essentially comparisons one compares one
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face with another the first thing you do is that you have to have a sensor
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you have to have a camera which it takes an image of the uh face
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since uh in english and then this image is processed in a number of stages
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so just to be able to be compared at the end
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of the closest with a reference which is contained in the database
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for example uh you have probably a recorded an image of your face in your mobile phone could be video
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surveillance application that is used for all and identity check
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application when you are entering a security building you know um
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a high has completely replace this module here model number three
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and the you um find it a lot uh here six years ago that
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was not the case six years ago you had a human being or was it
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carrying out the stage now it's being it's being done
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a automatically by computer based a large number of data
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not going to expand exactly how we do a facial recognition but want
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us in order to deceive official recognition this is one of our research subjects
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uh on the one hand we try to plant the bad guys we try to break the
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facial recognition systems that that's a very cool part of the job once we succeed in doing that
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we try to find ways and means of detecting a a tax
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so we try to ensure that the buyer metric system becomes more robust to resist attacks
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for example um as because official recognition application on my mobile phone
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the um i found ten uh is equipped with that
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but uh now you find very high and uh or or not not so high and
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the rangers sandwich i'm with the face recognition systems but they can be deceived a fairly easily
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you can do this at home not going to cite the names
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of brands but um this is that the uh low end of the
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at the lower end of the range you can deceive these
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uh telephones were easily whereas um it's much more difficult to
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uh this even i found i found time i'll explain uh i do more about this uh
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of the british know what are the attacks the attacks are represented by all these coloured dots
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is the places where we have identified faults in by metrics systems
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no uh the ones which interest us in particular other ones i'm going
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to be uh starting at the moment that's a tax numbers one and two
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it's a tech number one
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um uh to wrecked a tax
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you try to copy that by metrics you falsify someone's identity you try
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to use up so that person's identity to pass yourself off as that person
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and uh you you printed photograph and you try to process of
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office uh another person second uh attacked consists of injecting in the system
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'cause you have to have some of a a high 'cause talents in order to be able to penetrate
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the i. t. system ought to be able to do this injection uh uh not anyone can do this
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so you have to penetrate the i. t. system and inject a false
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piece of data and this is what we're going to talk about the uh
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uh fakes
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i'm going to show you some examples which show you the progress that's been
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made to since two thousand nine when we started to work on these attack problems
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this is the first and simplest to attack which was published in two thousand
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nine which was a reproduced on a larger scale in two thousand ten where we
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showed systematically uh what you need to to to uh to see for a um
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a laptop with a photograph
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you have to quantify
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uh i'm number different facial recognition in the algorithms thanks
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to this we managed to develop a pretty basic countermeasures systems
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so you are
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so um i of course some it's um normally system
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knows the difference between a photograph and a sheet of paper
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you can go further than this
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and you can imagine the folding knife or left out some of the stages we've left
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out to him though there was some intermediate steps but you can go even further you can
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make some ultra realistic masks in three dimensions is awful
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clutched masks with a whole so either to see through the multiple is made of different materials
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made of rescind we studied some in the past made
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the resin here they are ultra realistic a photo realistic
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um masks made of plastic all of silicone few for come up to the second floor
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here today you would've seen some of these masks and the systems used to detect them
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we created these masks in my research project to see
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is that you can break the systems with more elaborate attacks
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the aim of course being to create more effective countermeasures systems
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another form of attack see these attacks ah what
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we call the based on artifacts in other words
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um objects that resembled a human being in order to uh to see if the if the machine
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but you can know all to the human you can sometimes simply use makeup to change a person's appearance
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it was shown not by us but by someone else that it is
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possible to change one's appearance in order to uh to resemble someone else
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on the internet or some uh artists to change the appearance just by using a
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makeup not by resorting to process control c. sees a will to resemble a celebrities
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uh you have to be vitality to do that uh did yep we
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don't have those talents but uh what it can do is you can use
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make up to change a person's appearance and to uh make a personal goal that would be nice it to make it doesn't look younger but anyway
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so we managed to show that um we managed to make the person look
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all that just by using makeup it was uh one of the same day
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uh it's one the same person on the same day just by using makeup
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so uh the idea was to test the fish recognition systems to
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see whether the repressed enough to be able to deal with eighteen
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the aim was to see whether we could to detect with the system
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good to um detect whether makeup was being used and it's
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very difficult at the moment today because it's a real human being
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to his face we applied pigments which are very delicate and free
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difficult to underlies by a a computer vision
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no this is what they can do you can get a camera sees the camera sees when you do an attack
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presentation all attack can be carried out in different ways
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you can present a photograph sure photograph of different uh
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quality is all a screen and this is what the camera the the computer the machine sees no
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you see the same images as the uh computer which one is true and which one is false
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do you think this one is false
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a layout so as not to audible do you think it's true or false
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is what i can see an artifact or not
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would you would you say it's true or false the other one is true this one here true or false and this one
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this one
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everything is false everything's falls in fact
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are you gonna tell me what's the difference or two differences the first difference is that in the first column
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the fact that scared out is a sheet of paper for the gulf was printed on
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the sheet of paper but the original image was a um kept it in different ways
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the second attack was done with the screen of a mobile
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phone so the images but quality out of focus rather cluttered
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because the telephone in the uh
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a g. i. e. the uh the phone is slightly out of a focus
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you have to uh increase the distance of the detectives realistic the last attack was done on a big screen
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a day you display the photograph so i can see it even for you it was not easy to tell
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a real from full so the attacks are becoming more more realistic
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but i've not yet to got to the most realistic one this was in the early days ten years ago
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now we're trying to detect these attacks and we um
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very quickly bump up against a limit which we try to show in our project
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another is another form of attack which is really problematic in which it concerns a identity talk
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documents concerns uh it's called morphing attacks it's a number
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of countries in the world and in europe as well
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you where to um get a driver's license or
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a a a national identity card you bring along your
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photograph you complete a form you had in your
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foreman you leave them afterwards you receive your identity documents
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and uh normally there is a digital chip which is been scanned but it so happens that
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if you have touched up the photo a tinge to yourself for example by a merging two different people
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you will find the totally file it to identity document which will enable uh
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each of those two different people to travel a validly with that document so you
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you can find someone can find themselves so in uh europe with uh
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numerical uh image which is uh it's been morphed from uh
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uh uh two different people so um it complies can travel
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on the possible out of another person this is been a demonstrated
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it's been proven on state of the art facial recognition system so there is a
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uh there is so this is a vulnerability that does exist
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uh don't worry i will finish on the post it note but before that i would like to say a few words about the deep fakes
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uh keep fakes a it patrick action french
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so the idea is to uh transform the face of one person into the face of another person to make
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people believe to make you believe that this is reality
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on the right you recognise the person you recognise the actor
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who is tom cruise was not tom cruise
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you recognise tom cruise but the fact is this person this is an actor
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yours us to mime and to talk a bit like tom cruise does and then
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a deep fake okay uh uh software was used which is based on a i two
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transform uh the face in real time into that of the face of tom cruise
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subject to anyone's face can be a transformed into the
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uh phase of time 'cause that's very difficult to detect
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now here at the images of keep fakes now all these people don't exist at all don't exist at all
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he's a totally synthetic images
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this a virtual chance of these people exist uh on the planet this is scary
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because if you create a synthetic image um what what can it be used for it
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can be used to create a false profiles on the internet to do industrial or political espionage
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so it's very dangerous you can also do real time videos that's starting to emerge
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and um we're beginning to be able to combine the photos with uh the voice
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so i'm hyper realistic uh audio uh i'm
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thinking uh of my speaking terms the yep
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it's this technology's really tough follicle but um the technology
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can also be used for room good purposes these deep uh_huh
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this um for example for data confidentiality purposes
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normally you need a certain volume of the images
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uh we have to agree to a use of a a photograph and
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uh and uh you'll be regulations will soon ban the use of fish recognition as a number of application
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so it's getting very difficult to collect to these um
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photographs with the person's consent a lot of companies are using a
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him photographs of people without the consent of the question is uh
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how can i use a chain interest groups of people if i am not a lot to do so
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the onset is maybe to use these
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some t. fake technologies to create synthetic images
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and uh since you can create the synthetic images you you
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can also uh control the factors within them for example the luminosity
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and uh to change the channel to change a man to well not a for example all these images are synthetic
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and if you you can very certain factors to change the uh expression
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the uh brightness
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all the factors which unnecessary for facial recognition
