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article imageQ&A: Vibrational biometric system for identity recognition Special

By Tim Sandle     Dec 13, 2018 in Technology
Neurophysiologist Martin Zizi has invented a new form of biometric technology that is almost impossible to crack or hack. The system uses the human nervous system as its method of authentication.
Dr. Martin Zizi of Aerendir is the inventor of NeuroPrint, a cloudless physiological biometric technology that measures micro-vibrational patterns in a user’s hands. Digital Journal caught up with Zizi to discuss his technology.
Digital Journal: What is the remit of Aerendir?
Dr. Martin Zizi: Aerendir is the pioneer developer of the only physiological and single factor authentication that uses the unique human proprioception system for identification, authentication and encryption. Our solution can also differentiate any two individuals with an accuracy of 99.1 percent, and differentiate bots and AI-bots from humans at 90 percent accuracy.
Digital Journal: What is NeuroPrint working on as a biometric solution?
Zizi: Currently, there is no technology that puts the user in complete control of their own mobile identity and data. The fact that no data is stored or exchanged across the internet protects users against hacking and ensures the right of privacy. We seek to deliver a solution that is designed to empower users to take their data back.
DJ: What type of data is produced?
Zizi: With NeuroPrint, all personal data is unique to that individual’s profile and tied directly back to their own brain signals. To summarize our technology, we fuse the idiosyncrasies of a single device (yours) to your own physiology. It is a bit like a dual factor but without the friction. The user’s profile is specific for only one device. If one has other devices, they need to be trained too. For us, training is not a big problem because our technology can reach 99% accuracy within 5-7 minutes of touching the device (whether it is a phone or a tablet).
DJ: How was the technology developed?
Zizi: The development of the NeuroPrint came as a result of the fusion of 3 areas: human brain physiology, mathematics and artificial intelligence.
NeuroPrint extracts brain signals without using any electrodes, any scanners or any EEG helmet. Our brains and nerve cells are connected to every muscle fiber in our bodies. Those fibers literally vibrate and shiver, whether we are moving or not. The process is called proprioception and is present in every muscle in our body.
This signal generates a unique proprioceptive signature, called NeuroPrint. We can easily capture those invisible vibrations in the user’s hands, using the accelerometers and the gyroscopes that are standard in today’s mobile devices. Using this neural information, we can build numerous products. The solution can be used as a standalone authentication or to add new authentication and encryption functions to an existing schema. The
NeuroPrint can also recognize if the signal is being generated by a human or an AI/bot.
DJ: How was the system tested?
Zizi: The
NeuroPrint solution was tested using smartphones with a database of over 3,000 users and resulted in a false positive ratio of less than 0.1%. This is amongst the lowest for a biometric authentication solution. This compares more than favorably to other biometrics such as fingerprint and facial recognition, both of which exhibit higher false positive rates depending on the biometric used.
DJ: What are the implications of the technology?
Zizi: The discovery of NeuroPrint means there will be a new standard for data privacy. Currently, there is no technology that puts the user in complete control of their own mobile identity and data. The fact that no data is stored or exchanged across the internet protects users against hacking and ensures the right of privacy. We seek to deliver a solution that is designed to empower users to take their data back.
DJ: What will be the main applications?
Zizi: Aerendir products will be performing identification, encryption or a combination of both. Markets it could be used in are e-commerce, mobile payments, financial transactions, the locking/unlocking of connected devices, non-clinical health solutions and the automobile industry. As our AI technology is not based on big data but on smart data, it can also be embedded directly into chips to give smart AI-enabled sensors.
In a follow up interview, Dr. Zizi provides his thoughts on advances and applications of biometric technology in general. See “
Q&A: Where is biometric technology heading next?
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