Polygon Labs Plans Partnership to Develop Less Invasive Identity Verification

Polygon Labs has planned to partner with other Web3 and blockchain companies to develop a less invasive identification mechanism. Current iris and thump print verifications have raised questions about potential privacy breaches and hacks. The new technology, if developed successfully, will be able to solve this particular concern.

Human Institute Partners with Polygon Labs

The Human Institute revealed plans to use palm recognition technology to introduce Proof of Humanity in collaboration with Animoca Brands and Polygon Labs. It claims that this is a readily available smartphone app that provides a less intrusive form of identity verification than techniques such as Worldcoin’s iris scans. Humanity Protocol’s palm recognition solution will largely cater to Web3 identity verification.

In addition to providing the team with guidance on Web3 best practices and a valuable ecosystem expansion, Animoca Brands has also contributed its knowledge of intellectual property rights. The protocol also makes use of Polygon CDK, which increases its efficiency and scalability even more.

Data Collected Through Verification Primary Concern for Many

The development of palm-based recognition technology comes at a time when iris or thumbprint-based verification technology is getting global backlash. The data that is collected via iris verification and thumbprint verification puts a lot of user information at risk. The data linked with iris and thumbprints can be used for multiple malpractices, should a hack or breach occur.

Just recently, Sam-Altman-backed Worldcoin faced issues in Hong Kong over potential privacy risks. The investigation’s primary focus was on Worldcoin’s iris verification service. Because biometric data is unique, distinct, and immutable, it is generally regarded as sensitive personal data.

Future Biometric Systems to Have Self-Learning Capabilities

At present, most biometrics like iris verifications, palm detection, and even figure print recognition have a major problem. They do not constitute factors like aging and change or alteration in a specific body part. However, development in Web3 technology and AI will help the identification process to be self-reliant in the future. Research published under the ResearchGate states that future biometric recognition will require a new algorithm that is more self-learning, humanized, and based on bio-inspired computing. Furthermore, the implementation of translation, rotation, and scale-invariant procedures depends on sophisticated automatic detection. Because it only employs a small number of well-chosen intermediate resolution levels for matching, it is less susceptible to noise and quantization mistakes and more computationally efficient. For reliable and quick recognition, the algorithm needs to be intelligent enough to recognize similarities between the features extracted from the training data set.