Recent Posts

31 Jan 2016 : On Blockchains and Media DRM

Many people seem to think that blockchain technology would help with DRM ( or “content protection”) because blockchain tech (the Bitcoin usecase in particular) proved for the first time that creating digital scarcity is possible, and DRM is fundamentally about enforcing digital scarcity. Some are envisioning that just as a bitcoin can have its ownership transferred from one person to another there must be a way to do the same with a media file.

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13 Sep 2015 : IPFS Introduction by Example

IPFS (InterPlanetary File System) is a synthesis of well-tested internet technologies such as DHTs, the Git versioning system and Bittorrent. It creates a P2P swarm that allows the exchange of IPFS objects. The totality of IPFS objects forms a cryptographically authenticated data structure known as a Merkle DAG and this data structure can be used to model many other data structures. We will in this post introduce IPFS objects and the Merkle DAG and give examples of structures that can be modelled using IPFS.

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10 Mar 2015 : Computer security and private keys

Recent hacks of large corporations show that the current state of computer security is severely lacking and that new thinking is needed in this realm. While this is a big and complex field I’m going to focus on a few specific areas and suggest some ways that security may be enhanced.

The popularity of cryptocurrencies like Bitcoin has created an evolutionary pressure to build very secure systems for handling cryptographic private keys. Since the stakes are high – loss of private keys often mean direct loss of money – there is great interest in developing hardware based systems for securing and handling private keys.

We will discuss the current landscape and suggest some ideas for improving computer security in the specific areas of Payment systems, Authentication and Data storage. The main idea is to transform the various security requirements of these areas into the one security requirement of handling and securing cryptographic private keys.

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11 May 2014 : Why we love Cosplay Hulk

This is our first post which is about neither statistics nor bitcoin. It is about something we like almost as much: Cosplay Hulk. Who?!? He is the wonderful guy shown in the picture to the left who blurs the line between idiocy and genius.

Like most Americans, we spend too much time reading reddit which, for better or worse, gives us some insight into what it’s like to do things we never ever actually do in real life, such as playing video games (because we have too little time) or worrying about school (because we are way too old). Cosplay falls squarely into this category. We think it’s really cool that people build costumes from scratch and put themselves out there for all to admire and/or mock. For those of you who don’t know what cosplay is, think Halloween taken to a freakish new level by nerds. And while some cosplayers are hot, many are not, but all have one thing in common: too much free time on their hands.

Cosplay costumes are a much bigger investment in effort, time, and money than average laymen like us would ever dare to spend in a costume. As a result, most of them are pretty good, and a few of them are downright amazing. Enter Cosplay Hulk, who has smashed the bounds on what it means to be bad at something. In his debut photo, he can be seen hanging out with his cosplay Avenger friends. We consider his co-Avengers to be quite lucky because their costumes are shitty enough to merit a fair amount of ridicule, yet nobody notices them because…oh my god WHO is that on the right?!?!?!

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04 May 2014 : Bitcoin transactions, technically (Part 2)

In our previous post we introduced bitcoin transactions by using the metaphor of safes and coins, in order to develop an intuitive sense of the concept. Here we will investigate bitcoin transactions from a more technical standpoint using the Python bitcoin library pybitcointools, by exploring the transaction data structures directly.

As an example we will be using a real transaction which we selected randomly from the blockchain. The transaction can be viewed here:…

The reader is encouraged to look at the transaction above and cross-check the information there with what we investigate below.

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26 Apr 2014 : Warning: Beware the p!

Bijou beware!

We recently stumbled onto a delightful demonstration called dance of the values by statistical cognition researcher Geoff Cumming. If you have ten minutes to spare, we highly recommend that you watch this video. If you don’t have ten minutes to spare, then we can save you some time and summarize the video in three words: “don’t trust .” In the video, Cumming sets up a series of experiments to demonstrate the fickleness of the . In this post we reproduce his demonstration in R.

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18 Apr 2014 : Introducing Bitcoinista

Ever since Apple decided to disallow bitcoin wallets in the App Store, bitcoin users who use iOS devices have done one of two things: either ditched (or even destroyed) their iPhones, or tried to find workarounds. One obvious workaround is to jailbreak the device, but this comes with its own complications since it’s not officially supported by Apple. The non-jailbreak workarounds have been either web-based HTML5 wallets such as CoinPunk or native apps distributed through ways that may or may not violate the Apple Enterprise Licence. Today we introduce a new workaround using Python.

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06 Apr 2014 : What does mean mean, really?

Shayne Fletcher is hooked on computer programming, and we are hooked on his blog. His most recent posts are a irresistible introduction to some fundamental statistics via OCaml programming, among them a total of five different definitions of the mean value of a sequence. In this post we continue Shayne’s discussion with a side dish of calculus and R thrown in for good measure. You should really read Shayne’s blog posts on statistics and power means before you continue reading this.

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29 Mar 2014 : Bitcoin transactions, metaphorically (Part 1)

If you’re reading this post it means you are alive, and if you’re alive it means you’ve probably heard about bitcoin. That in itself is quite remarkable seeing as just a few years ago pretty much the only people who had any exposure to bitcoin were the core bitcoin developers, people trading illicit substances for bitcoins on silk road, and undercover FBI agents trying to catch people trading illicit substances for bitcoins on silk road. Today silk road is gone and bitcoin is a household name making headlines almost daily. Here is one of many from Bloomberg. Even the WSJ has a dedicated bitcoin news blog called BitBeat.

So all the cool kids are talking about bitcoin these days, and we certainly don’t want to be uncool. But what are said cool kids actually talking about? We will try to answer this question, i.e. we will try to gain some understanding of the technical underpinnings of the bitcoin protocol through a series of posts.

In this first post we will give metaphors that will try to provide a heuristic, high-level understanding. A subject like bitcoin requires very strict adherence to computer security standards. It’s not reasonable for non-technical users to fully understand technical aspects like cryptographic hash functions or decentralized P2P networks, but bitcoin can be very unforgiving if you have the wrong ideas. It’s quite easy to end up doing the bitcoin equivalent of leaving a suitcase full of cash in the trunk of a taxi cab and having the taxi drive away as you get out, except in the case of the taxi there is still a chance that you might get your lost money back.

Security researcher Bruce Schneier describes how metaphors are a necessary tool to train people in computer security, and we fully agree with this. We will try to develop metaphors that are easy to grasp but at the same time maps to the correct underlying technical details. This is important because if you are using a metaphor that is not technically correct you run a real risk of losing coins, as we will see below.

Without further ado, let’s dive into our metaphors.

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28 Mar 2014 : Getting our hands dirty with beta functions

We just finished watching a YouTube tutorial on Dirichlet distributions given by Foursquare data scientist Max Sklar. According to Wikipedia, the Dirichlet distribution is the “multivariate generalization of the beta distribution.” Yikes! We confess that the last time we saw a beta distribution was around the time Bill Clinton was being impeached. In this post we brush the cobwebs from our minds and derive a basic identity between beta and gamma functions and illustrate our calculations with R.

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