Online Identity Credential
A secure, reliable and user-friendly online identity credential would help protect you in your online interactions. Creating such a credential has been challenging, however, because there is an inherent tension between security and ease-of-use. To date, the only solutions that generate a high-security identity credential require users to reveal very detailed information about themselves, often through an in-person proofing process. However, users have typically refused to use solutions that make unreasonable demands of time, effort, money and the information they are asked to reveal about themselves.
AssertID has found a way to create a high-security credential without making such unreasonable demands.
Embeddedness as a Predictor of Social Behavior
Although online social networks are a relatively recent phenomenon, offline social interactions have long been studied by social scientists, first through qualitative case studies and, more recently, through computational analysis techniques. These studies have revealed specific patterns that remain consistent across a wide variety of settings. One such pattern reflects an individuals entanglement in social relationships. An individual's degree of entanglement, i.e. their embeddedness, can be summarized as follows:
- Human beings are entangled in webs of social relationships (i.e., social networks)
- The way they are entangled (embedded) affects their behavior
- The greater a person’s embeddedness in a social network, the less likely that person is to deceive and/or cheat other members of that network
An individuals' embeddedness can be a reliable predictor of how they will behave in social interactions. AssertID has developed certain proprietary algorithms that allow us to derive a quantitative measure for an individuals' embeddedness from the data users already provide to their online social networks.
Your Social-graph holds the Means to Verify your Identity
Typical social network profiles (e.g. Facebook, MySpace or LinkedIn), provide all of the identity data needed to establish someone's online identity, (first name, last name, photo, age, location, etc.) However, the identity data provided in these profiles is self-asserted, and not everyone asserts truthful information about themselves.
AssertID has developed a verification process which allows individuals to vouch for each other, verifying that their close friends are who they say they are. By analyzing the number and connection pattern of these verifications (the “social graph”), AssertID can assess the trustworthiness of individuals’ self-asserted profile attributes. In a very simple analogy, AssertID functions much like a credit rating (e.g. FICO) generated through something that superficially looks like Google’s PageRank algorithm.
By combining insights gained from social network analysis with best-practices from the online security world, AssertID has created a low-friction means to verify an individuals' identity and indicate how an individual is likely to conduct themselves on the social web. In this way we believe that AssertID can promote trust and civility in social-web interactions.