Here's a short paper that talks about generating prime numbers. It's pretty interesting:
http://www.cs.hmc.edu/~oneill/papers/Sieve-JFP.pdf.
Friday, November 30, 2007
Wednesday, November 28, 2007
What Happened to the Quants in August 2007?
ahh the credit crunch. we've been through this sort of thing before, when black-shoals had a failing in its fundamental assumptions. found this paper via a buttonwood column in the economist, Heart of darkness, Oct 25th 2007, from The Economist print edition.
Khandani, Amir E and Lo, Andrew W., "What Happened to the Quants in August 2007?" (November 4, 2007). Available at SSRN.
During the week of August 6, 2007, a number of quantitative long/short equity hedge funds experienced unprecedented losses. Based on TASS hedge-fund data and simulations of a specific long/short equity strategy, we hypothesize that the losses were initiated by the rapid unwind of one or more sizable quantitative equity market-neutral portfolios. Given the speed and price impact with which this occurred, it was likely the result of a forced liquidation by a multi-strategy fund or proprietary-trading desk, possibly due to a margin call or a risk reduction. These initial losses then put pressure on a broader set of long/short and long-only equity portfolios, causing further losses by triggering stop/loss and de-leveraging policies. A significant rebound of these strategies occurred on August 10th, which is also consistent with the unwind hypothesis. This dislocation was apparently caused by forces outside the long/short equity sector - in a completely unrelated set of markets and instruments - suggesting that systemic risk in the hedge-fund industry may have increased in recent years.
Khandani, Amir E and Lo, Andrew W., "What Happened to the Quants in August 2007?" (November 4, 2007). Available at SSRN.
How To Break Anonymity of the Netflix Prize Dataset
reminds me of the AOL search data hacks ...
Source: How To Break Anonymity of the Netflix Prize Dataset, Authors: Arvind Narayanan, Vitaly Shmatikov.
(Submitted on 18 Oct 2006 (v1), last revised 22 Nov 2007 (this version, v2))
We present a new class of statistical de-anonymization attacks against high-dimensional micro-data, such as individual preferences, recommendations, transaction records and so on. Our techniques are robust to perturbation in the data and tolerate some mistakes in the adversary's background knowledge.
We apply our de-anonymization methodology to the Netflix Prize dataset, which contains anonymous movie ratings of 500,000 subscribers of Netflix, the world's largest online movie rental service. We demonstrate that an adversary who knows only a little bit about an individual subscriber can easily identify this subscriber's record in the dataset. Using the Internet Movie Database as the source of background knowledge, we successfully identified the Netflix records of known users, uncovering their apparent political preferences and other potentially sensitive information.
Source: How To Break Anonymity of the Netflix Prize Dataset, Authors: Arvind Narayanan, Vitaly Shmatikov.
(Submitted on 18 Oct 2006 (v1), last revised 22 Nov 2007 (this version, v2))
Monday, November 12, 2007
Windows RNG
Writing a random number generator is a lot harder than most people think. A while ago some researchers dove through the linux source code and figured out how the linux random number generator worked. Yup, they had to reverse engineer it from the source! Anyway, they found a bunch of weaknesses. Well, guess what? Someone recently reversed the Windows RNG and found even more serious weaknesses.
http://eprint.iacr.org/2007/419.pdf
If you're into security, especially web security, you should probably know about this. It puts a big chink into SSL and other systems that rely on random numbers.
http://eprint.iacr.org/2007/419.pdf
If you're into security, especially web security, you should probably know about this. It puts a big chink into SSL and other systems that rely on random numbers.
Mommy, Where do compilers come from?
A great slide deck on the process of bootstrapping a new language:
http://proglang.informatik.uni-freiburg.de/teaching/compilerbau/2004/T-diagrams.pdf
This one's a super quick read.
http://proglang.informatik.uni-freiburg.de/teaching/compilerbau/2004/T-diagrams.pdf
This one's a super quick read.
Friday, November 02, 2007
QMail retrospective
It's been ten years, what has QMail done for me lately? It certainly hasn't let me violate your security policies. DJB offers his analysis of ten years of QMail:
http://cr.yp.to/qmail/qmailsec-20071101.pdf
Good, preachy paper. DJB says why he thinks QMail was successful, why what other people are doing is a waste of time, and what we should be focussing on. Several priceless quotes from DJB and others are included.
http://cr.yp.to/qmail/qmailsec-20071101.pdf
Good, preachy paper. DJB says why he thinks QMail was successful, why what other people are doing is a waste of time, and what we should be focussing on. Several priceless quotes from DJB and others are included.
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