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AI Unravels the Mystery of Fingerprints: Are We Truly Unique?

 


Due to its uniqueness and permanence, fingerprint analysis is regarded as a valuable tool in the field of forensics and security because no two fingerprint patterns are identical, not even identical twins. There are so many unique aspects of fingerprints that even your own fingerprints do not match with the fingerprints of others.

However, there is new research utilizing artificial intelligence (AI) that claims that forensic fingerprint identification will undergo a substantial change. There has been a recent breakthrough in forensics with the invention of a new artificial intelligence system developed by Columbia University engineers, which dispels a long-held belief in forensics: that fingerprints from a person's different fingers are not all the same.

In the field of forensics, it is widely accepted that fingerprints on different fingers of a given individual are all different from one another, and therefore, unmatchable. Columbia Engineering undergraduate student Gabe Guo led a team that challenged this widely held presumption and questioned this widely held belief. 

With no prior forensic experience, Guo found a public database containing about 60,000 fingerprints and fed the fingerprints in pairs into an artificial intelligence-powered system called a deep contrastive network based on artificial intelligence. It is possible that the pair of fingers belong to the same individual at times (but with different fingers) and at other times it is likely that the pairs belong to different individuals. 

Researchers suggest that the artificial intelligence tool was analyzing fingerprints differently from traditional methods - the algorithm focused more on the orientation of the ridges within a finger as well as how the end and fork of the ridge, which is referred to as minutiae, rather than the end of each ridge. Prof Lipson added that "there is no doubt that it is not using traditional forensic markers that have been used for decades," in the field of forensics. 

As Prof Lipson explained, he and Gabe Guo, an undergraduate student, were both surprised when they saw the outcome of this particular experiment. It seems like something has been calculated based on the curvature and angle of the swirls in the centre. 

During the Covid-19 lockdowns when Gabe Guo was stuck at home while waiting to start his freshman year at Columbia University, a professor asked Gabe Guo the following question during a casual chat. That conversation did not occur to me, but it set the stage for my life to be focused on it for three years to come. A professor from the University of Buffalo, as well as one of Guo's coauthors, Wenyao Xu, conducted a study on the subject for Columbia's Department of Computer Science during his undergraduate years and Guo led the team. 

Identical fingerprints don't exist everywhere on the planet, Guo and his colleagues argue, even though fingerprints have taken up a lot of space. This is apparently contrary to the long-established truth about fingerprints. The paper is an interesting one, said Simon Cole, a professor in the department of criminology, law and society at the University of California, Irvine who believes its practical benefit is overstated as he agreed that it is interesting. This study was not conducted by Cole, nor was he involved in any of its components. 

Essentially, Cole said that the fingerprint system could be useful at crime scenes where fingerprints found were from a different finger than those in police records, but Cole said that it would be a rare occurrence. When fingerprints are taken, all ten fingers and palms are routinely recorded when the prints are taken, so Cole said this could only happen in a few cases. It appears to me that authorities are not clear as to why they think law enforcement does not have all records of an individual's fingerprints or even some of them, he said. 

Champion and Cole both praised the decision that the team behind the study made in open-sourcing the AI code so it could be checked by others, a decision which was praised by the team behind the study as well. Despite that, Guo seems to believe that the study is of much greater importance than just fingerprints alone. 

According to Dr Hod Lipson, a Professor of Robotics at Columbia University, this activity is clearly different from the traditional forensic markings used by forensic detectives over many years. The curvature and the angle of the swirls in the middle seem to indicate that it uses something like that in the centre." However, the development comes as no surprise to an academic in England who has been working on this topic for over twenty years.

It has been reported by the BBC that Professor Graham Williams from Hull University has stated that determining what makes a fingerprint unique has never been an exact science. The uniqueness of fingerprints remains uncertain, as it is acknowledged that current knowledge is limited to the absence of demonstrated cases where two individuals possess identical fingerprints. The implications of this uncertainty call for further research, study, and deliberation. According to the report, the identified findings are not anticipated to exert a substantial influence on the field of forensics at this juncture.

Hardware Bugs Provide Bluetooth Chipsets Unique Traceable Fingerprints

 

A recent study from the University of California, San Diego, has proven for the first time that Bluetooth signals may be fingerprinted to track devices (and therefore, individuals). At its root, the identification is based on flaws in the Bluetooth chipset hardware established during the manufacturing process, leading to a "unique physical-layer fingerprint."

The researchers said in a new paper titled "Evaluating Physical-Layer BLE Location Tracking Attacks on Mobile Devices, "To perform a physical-layer fingerprinting attack, the attacker must be equipped with a Software Defined Radio sniffer: a radio receiver capable of recording raw IQ radio signals." 

The assault is made feasible by the pervasiveness of Bluetooth Low Energy (BLE) beacons, which are constantly delivered by current smartphones to allow critical tasks such as contact tracking during public health situations. 

The hardware flaws come from the fact that both Wi-Fi and BLE components are frequently incorporated into a specialised "combo chip," effectively subjecting Bluetooth to the same set of metrics that may be utilized to uniquely fingerprint Wi-Fi devices: carrier frequency offset and IQ imbalance. 

Fingerprinting and monitoring a device, therefore, includes calculating the Mahalanobis distance for each packet to ascertain how similar the characteristics of the new packet are to its previously registered hardware defect fingerprint. 

"Also, since BLE devices have temporarily stable identifiers in their packets [i.e., MAC address], we can identify a device based on the average over multiple packets, increasing identification accuracy," the researchers stated. 

However, carrying out such an attack in an adversarial situation has numerous obstacles, the most significant of which is that the ability to uniquely identify a device is dependent on the BLE chipset employed as well as the chipsets of other devices in close physical distance to the target. Other key aspects that may influence the readings include device temperature, variations in BLE transmit power between iPhone and Android devices, and the quality of the sniffer radio utilised by the malicious actor to carry out the fingerprinting assaults. 

The researchers concluded, "By evaluating the practicality of this attack in the field, particularly in busy settings such as coffee shops, we found that certain devices have unique fingerprints, and therefore are particularly vulnerable to tracking attacks, others have common fingerprints, they will often be misidentified. BLE does present a location tracking threat for mobile devices. However, an attacker's ability to track a particular target is essentially a matter of luck."