Underwood Dudley published a book called mathematical cranks that talks about faux proofs throughout history. While it seems to be mostly for entertainment than anything else, I feel it has become more relevant in modern mathematics. Especially with the advent of arXiv, you can obtain research papers before they are peer reviewed by a journal. So how does one tell between a crank proof and a genuine proof? This seems to be tough to discern in general.
For instance Perelman's proof was not submitted to any journal but published online. How did professional mathematicians discern that it was a genuine proof?
So how does one spot a crank proof? It seems that John Baez once (humorously) proposed a "crackpot checklist". Would this seem like a fair criterion?
In addition to Willie's answer/comment:
About a year ago, last June, a paper by Gerhard Opfer got a bit of attention for claiming to solve the Collatz Conjecture (it didn't). It was submitted to Mathematics of Computation, which may have given it the seeming credibility that propelled it into the spotlight (this is always a mystery - I don't know what made the recent kid-who-sort-of-solved-an-old-Newton-problem thing such a firestorm either). It even got to a question here.
This prompted me to write a short blog post about the Collatz Conjecture, Opfer's paper, and as a soft-answer to this soft-question, a bit about cranks and crank papers. (Ironically, writing that blog post somehow threw the spotlight on me as a destination for crank papers, and I've received a great many since.)
I think a large part of this aspect of the post can be summed up in two links: The Alternative-Science Respectability Checklist and Ten Signs a Claimed Mathematical Breakthrough is Wrong.
But I also happened across some articles from the writer-physicist or physicist-writer Jeremy Bernstein (much of whose work is published in periodicals like the New Yorker). He wrote an article called How can we be sure that Einstein was not a crank? (this is a link to a book containing the article), and he discusses two criteria for determining whether a new physics paper is from a crank or not.
The criteria don't quite port over to math so well, but there is an idea behind them that's true, just as the ideas behind the very humourous Ten Signs a Claimed Mathematical Breakthrough is Wrong are accurate in many ways. If I were to summarize some of his key points, I would say that Bernstein looks at 'correspondence' and 'predictiveness.' In the physics sense, 'correspondence' means that the result should explain why previous theories were wrong, and how the proposed idea agrees with experimental evidence. 'Predictiveness' is just what it says: a physics breakthrough should be able to predict some phenomena. If I were to cast these in a mathematical nature, I suppose 'correspondence' would say that the math shouldn't contradict things we already know (now we can solve all quintics with radicals, for example). But if the result is a big, old one, like Collatz or the Millenium problems, I should think that one needs to introduce something new so that there is some explanation of why it hadn't been done before. Predictiveness really doesn't port so well. I suppose that the strength of a mathematical result is sometimes measured in how much 'new math' it creates, and this is a sort of predictiveness... it's not a great match.
But I'd like to end by noting that sometimes, especially in math, simple arguments for nonsimple results (whatever that really means) exist. One of my favorite examples is the paper PRIMES is in P!, the paper detailing the AKS algorithm for quickly determining whether a given number is prime. The arguments are entirely elementary, despite how big the result it. And, funny enough, there is capitalization and excitement, indicators on some of the crank-checklists. Yet the result is valid.