Smart home security is always an area of concern. Leaving convention behind, Rutgers engineers have looked to finger vibrations as a way to verify users in a new system called VibWrite.
According to the research, current smart home access systems rely on cameras, cards, fingerprints, and intercoms to validate users. Downsides to existing solutions include password theft, installing expensive equipment, and device maintenance.
VibWrite presents itself as a low-cost and low-power tangible user interface that authenticates users when they touch any solid surface.
“Everyone’s finger bone structure is unique, and their fingers apply different pressures on surfaces, so sensors that detect subtle physiological and behavioral differences can identify and authenticate a person,” says Yingying (Jennifer) Chen, a professor in the Department of Electrical and Computer Engineering at Rutgers University-New Brunswick.
As shown in Figure 1(a), “when a vibration motor actively excites a surface resulting in the alteration of the shockwave propagation, the presence of the object or finger touching in contact with the surface can thus be sensed by analyzing the vibrations received by the sensor,” according to the research.
In Figure 1(b), users can decide between three confidential security measures, including a specific gesture, lock pattern, and PIN number.
“Smart access systems that use fingerprinting and iris-recognition are very secure, but they’re probably more than 10 times as expensive as our VibWrite system, especially when you want to widely deploy them,” says Chen.
During trials outlined in the paper, the system was able to verify users with 95 percent accuracy. False positive rates were less than 3 percent.
Although the system uses a unique approach, performance improvements are necessary, since multiple attempts are sometimes needed to gain entry. Plus, the system needs further tests to measure its performance in various outdoor conditions. The team plans to refine hardware, upgrade algorithms, and include multiple sensor pairs to remedy these issues.
You can read the full details of the study online, featured on the Association for Computing Memory (ACM) Digital Library (DL).
