UW Allen School Colloquium: Jacob Steinhardt (Stanford University)

[@kaushaltimilsina7727]

In blockchain technology, data mutability is decentralized. The idea is to not have a central authority controlling the data. To identify data attacks, some verified data is used as reference; because without reference, the attacks can shift the trusted data set and get the wrong information in the database. How do these things work together? Are many data users verified in blockchain technology, or is it like a more efficient population sampling that can analyze more samples? What happens when attacks feed in a lot of pseudo-legitimate data? In a sense that if the data seem authenitic, the radius of the confident data shrinks and so now false data can be fed into the distance closer than previously possible, and then if the user grows over time the radius increases again, now consuming the false data as legitimate. This could happen during New Year sales, where just before the sale attacks feed good data and decrease the range and add false data outside the range. But as the sales go off, the range increases and the database takes the false data as legitimate- sort of like a bounce phenomenon. Is that a sensible question to ask?

[@rimotivri]

underwater stuff are welcome. Cool.