We can make multi-factor authentication actually work by relying on human’s unparalleled ability to recognize acquaintances and detect impersonators.
Multi-factor authentication, a mechanism where the user provides two or more loosely coupled evidences of their identity, has become ubiquitous in access management of computer systems. Compared to a single factor authentication, no single piece of information about the user is sufficient for authentication, and account take-over requires obtaining multiple kinds of information about the user.
However, known multi-factor authentication schemes rely on a single user’s knowledge, possession, and inherence. Consequently, while breaking multi-factor authentication is harder than breaking single-factor, password or key based, authentication, it still requires access to a single entity only.
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Imagine that you have a great idea. You write it down on a napkin, show to your colleagues, they photograph the napkin with their smartphones, and will get back to you with investment proposals.
Now, what if instead of a napkin one of your colleagues has a laptop or a tablet handy? (more…)
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Imagine
- a client on an old tablet or laptop in your kitchen, (sitting on the fridge and also holding a recipe book),
- and a server serving a web page with shopping check list, automatically updated, to a mobile app.
Every time you run out of something (eggs, sugar, tea, …), you add this thing to the list of ‘missing’ goods (lookup/predictive input make adding easier). When you go shopping, whatever you added is in the shopping list, when you buy, you cross out the entry.
A background knowledge module knows how to measure different things (sugar in kg or packets, eggs are counted, etc.), and suggests default amounts to buy. If you have to buy too often, the amount is automatically increased.
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Imagine: a web app that sits on a collection of ebooks, shows the user a paragraph from a book, and asks the user whether they want
- get (buy) the whole book to read;
- read another paragraph from this book;
- read a paragraph from a similar book;
- read a paragraph from a different book.
The app can remember user’s past history to adjust suggestions. How paragraphs, similar, and different books are chosen is an interesting question.
For testing/development, free text repositories are available, for example, Project Gutenberg, but also many others.
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