Promises and Challenges in Continuous Tracking Utilizing Amino Acids in Skin Secretions for Active Multi-Factor Biometric Authentication for Cyber
📝 Abstract
We consider a new concept of biometric-based cybersecurity systems for active authentication by continuous tracking, which utilizes biochemical processing of metabolites present in skin secretions. Skin secretions contain a large number of metabolites and small molecules that can be targeted for analysis. Here we argue that amino acids found in sweat can be exploited for the establishment of an amino acid profile capable of identifying an individual user of a mobile or wearable device. Individual and combinations of amino acids processed by biocatalytic cascades yield physical (optical or electronic) signals, providing a time-series of several outputs that, in their entirety, should suffice to authenticate a specific user based on standard statistical criteria. Initial results, motivated by biometrics, indicate that single amino acid levels can provide analog signals that vary according to the individual donor, albeit with limited resolution versus noise. However, some such assays offer digital separation (into well-defined ranges of values) according to groups such as age, biological sex, race, and physiological state of the individual. Multi-input biocatalytic cascades that handle several amino acid signals to yield a single digital-type output, as well as continuous-tracking time-series data rather than a single-instance sample, should enable active authentication at the level of an individual.
💡 Analysis
We consider a new concept of biometric-based cybersecurity systems for active authentication by continuous tracking, which utilizes biochemical processing of metabolites present in skin secretions. Skin secretions contain a large number of metabolites and small molecules that can be targeted for analysis. Here we argue that amino acids found in sweat can be exploited for the establishment of an amino acid profile capable of identifying an individual user of a mobile or wearable device. Individual and combinations of amino acids processed by biocatalytic cascades yield physical (optical or electronic) signals, providing a time-series of several outputs that, in their entirety, should suffice to authenticate a specific user based on standard statistical criteria. Initial results, motivated by biometrics, indicate that single amino acid levels can provide analog signals that vary according to the individual donor, albeit with limited resolution versus noise. However, some such assays offer digital separation (into well-defined ranges of values) according to groups such as age, biological sex, race, and physiological state of the individual. Multi-input biocatalytic cascades that handle several amino acid signals to yield a single digital-type output, as well as continuous-tracking time-series data rather than a single-instance sample, should enable active authentication at the level of an individual.
📄 Content
– 1 – Promises and Challenges in Continuous Tracking Utilizing Amino Acids in Skin Secretions for Active Multi-Factor Biometric Authentication for Cybersecurity
Juliana Agudelo,[a] Vladimir Privman,[b] Jan Halámek*[a]
[a] Department of Chemistry, University at Albany, State University of New York, Albany, NY
12222 (USA), E-mail: jhalamek@albany.edu
[b] Department of Physics, Clarkson University, Potsdam, NY 13699 (USA)
ChemPhysChem 18 (13), 1714-1720 (2017) DOI link http://doi.org/10.1002/cphc.201700044
We consider a new concept of biometric-based cybersecurity systems for active authentication by continuous tracking, which utilizes biochemical processing of metabolites present in skin secretions. Skin secretions contain a large number of metabolites and small molecules that can be targeted for analysis. Here we argue that amino acids found in sweat can be exploited for the establishment of an amino acid profile capable of identifying an individual user of a mobile or wearable device. Individual and combinations of amino acids processed by biocatalytic cascades yield physical (optical or electronic) signals, providing a time-series of several outputs that, in their entirety, should suffice to authenticate a specific user based on standard statistical criteria. Initial results, motivated by biometrics, indicate that single amino acid levels can provide analog signals that vary according to the individual donor, albeit with limited resolution versus noise. However, some such assays offer digital separation (into well- defined ranges of values) according to groups such as age, biological sex, race, and physiological state of the individual. Multi-input biocatalytic cascades that handle several amino acid signals to yield a single digital-type output, as well as continuous-tracking time-series data rather than a single-instance sample, should enable active authentication at the level of an individual.
Keywords: authentication · forensics · biosensing · amino acids · enzymes
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- INTRODUCTION
1.1. Overview
The security of electronic devices such as smartphones or smart watches, which are often constantly connected to applications involving sensitive and personal information, is based on reliable authentication of the actual user/owner of the particular device. However, no single authentication methodology is foolproof. While theoretically, only the owner should know the passcode — be it a phrase or a numerical combination — passwords can be duplicated, e.g., by spying on the owner while unlocking the device. Pattern-based authentication can also be bypassed. For example, fingerprint molds can be “lifted” from fingerprints left on various surfaces, which allows unauthorized users to “trick” a fingerprint reader.[1] Another aspect of the problem has been the reluctance of the users to input their password/passcode too frequently. Both of these issues have led to the advent of active authentication approaches.[2,3] These typically include trace histories[2,4] that can be based on web-use (such as browsing history, application usage), and/or digital (facial recognition or speech analysis), physical (user’s gait, touch/swipe dynamics), or global/location tracking (following the user’s routine, GPS) that uses data collection and their analyses to determine that the user is an authorized person, whose additional verification with password will otherwise be requested on each access to any sensitive application. Active authentication requires various continuous authentication and tracking methodologies[2-5] that potentially involve not only the recording of various “histories,” but also continuous monitoring of the user’s patterns of behavior.
This article reviews a new concept and also outlines initial results for utilizing forensic biometrics to develop a new (bio)chemical approach to data collection for continuous active authentication and trace-history information gathering. The methodology is not based on the electronic (digital) or pattern (physical/optical) inputs, but rather on biochemical inputs: metabolites in the user’s skin secretions. The approach is autonomous and can be used by all individuals who own or have access to technology that holds personal information. Specifically, we address a continuous and unobtrusive user authentication and physiological state monitoring approach using metabolites secreted by the skin. The latter capability: to monitor the – 3 – physiological state of the user, is unique to such a “biochemical” approach as compared to other “electronic” or “physical” continuous tracking methods, which are more useful for monitoring “lifestyle/habits” information. Therefore, besides authentication and user tracking, this methodology can potentially enable a more convenient use of electronic devices for persons with certain disabilities.
Analytes that can be used as “input signals” for
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