Dmitri Krioukov (et. al.):

Several users of our AS relationship inference data (this http URL), released with cs/0604017, asked us why it contained AS relationship cycles, e.g., cases where AS A is a provider of AS B, B is a provider of C, and C is a provider of A, or other cycle types. Having been answering these questions in private communications, we have eventually decided to write down our answers here for future reference.

On Cycles in AS Relationships

We consider the problem of securing a multicast network against a wiretapper that can intercept the packets on a limited number of arbitrary network links of his choice. We assume that the network implements network coding techniques to simultaneously deliver all the packets available at the source to all the destinations. We show how this problem can be looked at as a network generalization of the Ozarow-Wyner Wiretap Channel of type II. In particular, we show that network security can be achieved by using the Ozarow-Wyner approach of coset coding at the source on top of the implemented network code. This way, we quickly and transparently recover some of the results available in the literature on secure network coding for wiretapped networks. We also derive new bounds on the required secure code alphabet size and an algorithm for code construction.

On Wiretap Networks

Programming Legend Charles Petzold unlocks the secrets of the extraordinary and prescient 1936 paper by Alan M. Turing

Mathematician Alan Turing invented an imaginary computer known as the Turing Machine; in an age before computers, he explored the concept of what it meant to be computable, creating the field of computability theory in the process, a foundation of present-day computer programming.

The book expands Turing’s original 36-page paper with additional background chapters and extensive annotations; the author elaborates on and clarifies many of Turing’s statements, making the original difficult-to-read document accessible to present day programmers, computer science majors, math geeks, and others.

Interwoven into the narrative are the highlights of Turing’s own life: his years at Cambridge and Princeton, his secret work in cryptanalysis during World War II, his involvement in seminal computer projects, his speculations about artificial intelligence, his arrest and prosecution for the crime of "gross indecency," and his early death by apparent suicide at the age of 41.

From the Back Cover:

Before digital computers ever existed, Alan Turing envisioned their power and versatility...but also proved what computers could never do.

In an extraordinary and ultimately tragic life that unfolded like a novel, Turing helped break the German Enigma code to turn the tide of World War II, later speculated on artificial intelligence, fell victim to the homophobic witchhunts of the early 1950s, and committed suicide at the age of 41. Yet Turing is most famous for an eerily prescient 1936 paper in which he invented an imaginary computing machine, explored its capabilities and intrinsic limitations, and established the foundations of modern-day programming and computability.

This absorbing book expands Turing's now legendary 36-page paper with extensive annotations, fascinating historical context, and page-turning glimpses into his private life. From his use of binary numbers to his exploration of concepts that today's programmers will recognize as RISC processing, subroutines, algorithms, and others, Turing foresaw the future and helped to mold it. In our post-Turing world, everything is a Turing Machine — from the most sophisticated computers we can build, to the hardly algorithmic processes of the human mind, to the information-laden universe in which we live.

The Annotated Turing: A Guided Tour Through Alan Turing's Historic Paper on Computability and the Turing Machine

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jGrowl is a jQuery plugin that raises unobtrusive messages within the browser, similar to the way that OS X's Growl Framework works.

jGrowl

MemeStreams is the next Google.

Chayes: I think that recommendation systems are going to be as important as search algorithms. In a recent piece of work, we came up with a list of desired properties for a recommendation system, and what we ended up doing was proving mathematically that there is no possible recommendation system that has all these desired properties. So I would have to choose which properties I am willing to give up and design recommendation systems that preserve the properties I want most.

TR: What kinds of properties?

Chayes: There's transitivity. If I trust the recommendation of person B, and person B trusts the recommendation of person C, then I should trust the recommendation of person C.

It could be that at some point somebody could go onto a social network and say, "Here are the properties that I want for my recommendation system," and a different person could go in and say, "Here are the properties that I want," and they could get two different recommendation systems.

Jennifer Chayes, on Recommendation Systems

Beeswax is an information management system inspired by Lotus Agenda. It aims to recreate Agenda's flexibility and efficiency in a clutter-free, text-based (ncursesw) user interface with vi key bindings. Beeswax views & reports will have specifications for sections, columns, filtering, and sorting.

Release v0.2.0 is a somewhat stable base of functionality on which the remaining features will be built. Since columns and custom views are not yet included, it is essentially Beeswax with just a single hierarchical view of all items.

The concept is that you have a database of information stored as individual items. Each item is a bit of information shown on the screen with a small bullet character at the beginning. In addition, each item can have a note attached to it to hold more extensive information. Notes are stored within the Beeswax database, but are edited by Beeswax launching your favorite text editor. When an item has a note attached, there is a small musical note displayed at the beginning of the item.

The Beeswax database has no predefined structure; instead, the structure is built up in a flexible manner as you work with the data. Each item of information can be assigned to zero or more categories. Categories are nothing more than items that have other items assigned to them. In Agenda, there was a separate distinction between items and categories, but in Beeswax I've generalized it even further and removed this distinction. If an item has other items assigned to it, then it is considered a category. On the other hand, if an item is assigned to more than one category, then it itself can not be used as a category.

The relationships between items of information are highly flexible. An item can be easily assigned to several different categories and the view immediately displays the new relationships. An item can just as easily be detached from categories. As you move items through Beeswax, their relationship to each other remains highly flexible.

The best way to understand all this is to get into Beeswax and start using it!

Beeswax - Mind Your Own Beeswax

Reputation systems constitute an important institution to help sustain trust in online auction markets. However, only half of buyers leave feedback after transactions, and nearly all of it is positive. In this paper, I propose a mechanism whereby sellers can provide rebates (not necessarily in monetary form) to buyers contingent upon buyers' provision of reports. Using a game theoretical model, I show how the mechanism can increase unbiased reporting. There exists a pooling equilibrium where both good and bad sellers choose the rebate option, even though their true types are revealed through feedback. The mechanism also induces bad sellers to improve the quality of the contract.

Reputation, Trust, and Rebates: How Online Auction Markets Can Improve Their Feedback Mechanisms

Walter Benjamin’s famous “Work of Art” essay sets out his boldest thoughts—on media and on culture in general—in their most realized form, while retaining an edge that gets under the skin of everyone who reads it. In this essay the visual arts of the machine age morph into literature and theory and then back again to images, gestures, and thought.

This essay, however, is only the beginning of a vast collection of writings that the editors have assembled to demonstrate what was revolutionary about Benjamin’s explorations on media. Long before Marshall McLuhan, Benjamin saw that the way a bullet rips into its victim is exactly the way a movie or pop song lodges in the soul.

This book contains the second, and most daring, of the four versions of the “Work of Art” essay—the one that addresses the utopian developments of the modern media. The collection tracks Benjamin’s observations on the media as they are revealed in essays on the production and reception of art; on film, radio, and photography; and on the modern transformations of literature and painting. The volume contains some of Benjamin’s best-known work alongside fascinating, little-known essays—some appearing for the first time in English. In the context of his passionate engagement with questions of aesthetics, the scope of Benjamin’s media theory can be fully appreciated.

The Work of Art in the Age of Its Technological Reproducibility, and Other Writings on Media

Passwords are ubiquitous, and users and service providers alike rely on them for their security. However, good passwords may sometimes be hard to remember. For years, security practitioners have battled with the dilemma of how to authenticate people who have forgotten their passwords. Existing approaches suffer from high false positive and false negative rates, where the former is often due to low entropy or public availability of information, whereas the latter often is due to unclear or changing answers, or ambiguous or fault prone entry of the same. Good security questions should be based on long-lived personal preferences and knowledge, and avoid publicly available information. We show that many of the questions used by online matchmaking services are suitable as security questions. We first describe a new user interface approach suitable to such security questions that is offering a reduced risk of incorrect entry. We then detail the findings of experiments aimed at quantifying the security of our proposed method.

Love and Authentication