Adding noise does an OK job of protecting an individual response, but after years of submitting survey responses to many web surveys, there'd be plenty of data to make excellent estimates of your personal attributes.
How many users are aware that many of the sites they visit pool data?
There's an enormous body of research on how to hide individual records in databases, ranging from adding noise to preventing queries that access fewer than a set number of records. In the end, none of the methods work well - all have simple or clever workarounds. Even individual records aren't very well protected by adding noise if the record size is large enough and fields are dependent.
(Biases: I spent my undergraduate and graduate years at one of the big-name schools, getting a PhD in C.S. from MIT about 3 years ago.)
If you're interested in cutting-edge computer science, I'd encourage you to try for one of the big-name schools. Here's why:
Graduate study, at least at the PhD level, is much less about classwork than about research. Often for undergraduate classwork the same textbooks and curricula are used in many schools, and a smart and diligent student can learn as well at one place as another. But graduate research is different.
Most PhD students spend years exploring different areas trying to find a niche that they enjoy and excel in. It's harder than you think: there are so many avenues for exploration in computer science, and so many people working in the field, that it's easy to end up working on problems that famous people solved 50 years ago, or that to be properly solved demand skills you don't have, or that are so obviously the next step that every Tom, Dick and Harry will be writing exactly the same code as you. It takes time to become aware of this and to learn to judge what work is worthy of sustained investigation.
In my opinion, the biggest advantage that top-tier schools offer is that the people around you, professors and (more importantly) students, provide examples of what kinds of problems are worth pursuing, and help evaluate your own ideas. At smaller schools, or schools where few students are capable or driven enough to participate in leading research, you're much less likely to find excited people who can fairly evaluate your own ideas, and who can explicitly or implicitly guide you to interesting topics. (For this reason, when choosing schools I would pay more attention to the caliber and interests of your fellow students than to measures like the breadth of class offerings.)
The difference between different schools' students is often glaringly apparent at conferences. Relative to the students from the big-name schools, students from the small-name schools tend to submit work that isn't bad per se, but is often out of date or subsumed by more general results others have produced. I feel this is more a reflection of a poor environment around them than their own capabilities.
Slashdot Mirror
Adding noise does an OK job of protecting an individual response, but after years of submitting survey responses to many web surveys, there'd be plenty of data to make excellent estimates of your personal attributes.
How many users are aware that many of the sites they visit pool data?
There's an enormous body of research on how to hide individual records in databases, ranging from adding noise to preventing queries that access fewer than a set number of records. In the end, none of the methods work well - all have simple or clever workarounds. Even individual records aren't very well protected by adding noise if the record size is large enough and fields are dependent.
(Biases: I spent my undergraduate and graduate years at one of the big-name
schools, getting a PhD in C.S. from MIT about 3 years ago.)
If you're interested in cutting-edge computer science, I'd encourage you to try
for one of the big-name schools. Here's why:
Graduate study, at least at the PhD level, is much less about classwork than
about research. Often for undergraduate classwork the same textbooks and
curricula are used in many schools, and a smart and diligent student can learn
as well at one place as another. But graduate research is different.
Most PhD students spend years exploring different areas trying to find a niche
that they enjoy and excel in. It's harder than you think: there are so many
avenues for exploration in computer science, and so many people working in the
field, that it's easy to end up working on problems that famous people solved 50
years ago, or that to be properly solved demand skills you don't have, or that
are so obviously the next step that every Tom, Dick and Harry will be writing
exactly the same code as you. It takes time to become aware of this and to
learn to judge what work is worthy of sustained investigation.
In my opinion, the biggest advantage that top-tier schools offer is that the
people around you, professors and (more importantly) students, provide examples
of what kinds of problems are worth pursuing, and help evaluate your own ideas.
At smaller schools, or schools where few students are capable or driven enough
to participate in leading research, you're much less likely to find excited
people who can fairly evaluate your own ideas, and who can explicitly or
implicitly guide you to interesting topics. (For this reason, when choosing
schools I would pay more attention to the caliber and interests of your fellow
students than to measures like the breadth of class offerings.)
The difference between different schools' students is often glaringly apparent
at conferences. Relative to the students from the big-name schools, students
from the small-name schools tend to submit work that isn't bad per se, but is
often out of date or subsumed by more general results others have produced. I
feel this is more a reflection of a poor environment around them than their own
capabilities.
Best of chances, regardless.