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Presidential Candidate Andrew Yang Has Quantum Encryption Policy

At least one presidential candidate has a policy about quantum computing and encryption.

It has two basic planks. One: fund quantum-resistant encryption standards. (Note: NIST is already doing this.) Two, fund quantum computing. (Unlike many far more pressing computer security problems, the market seems to be doing this on its own quite nicely.)

Okay, so not the greatest policy — but at least one candidate has a policy. Do any of the other candidates have anything else in this area?

Yang has also talked about blockchain: “

“I believe that blockchain needs to be a big part of our future,” Yang told a crowded room at the Consensus conference in New York, where he gave a keynote address Wednesday. “If I’m in the White House, oh boy are we going to have some fun in terms of the crypto currency community.”

Okay, so that’s not so great, either. But again, I don’t think anyone else talks about this.

Note: this is not an invitation to talk more general politics. Not even an invitation to explain how good or bad Andrew Yang’s chances are. Or anyone else’s. Please.

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Applied Cryptography is Banned in Oregon Prisons

My Applied Cryptography is on a list of books banned in Oregon prisons. It’s not me — and it’s not cryptography — it’s that the prisons ban books that teach people to code. The subtitle is “Algorithms, Protocols, and Source Code in C” — and that’s the reason.

My more recent Cryptography Engineering is a much better book for prisoners, anyway.

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Google Releases Basic Homomorphic Encryption Tool

Google has released an open-source cryptographic tool: Private Join and Compute. From a Wired article:

Private Join and Compute uses a 1970s methodology known as “commutative encryption” to allow data in the data sets to be encrypted with multiple keys, without it mattering which order the keys are used in. This is helpful for multiparty computation, where you need to apply and later peel away multiple layers of encryption without affecting the computations performed on the encrypted data. Crucially, Private Join and Compute also uses methods first developed in the ’90s that enable a system to combine two encrypted data sets, determine what they have in common, and then perform mathematical computations directly on this encrypted, unreadable data through a technique called homomorphic encryption.

True homomorphic encryption isn’t possible, and my guess is that it will never be feasible for most applications. But limited application tricks like this have been around for decades, and sometimes they’re useful.

Boing Boing article.

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Yubico Security Keys with a Crypto Flaw

Wow, is this an embarrassing bug:

Yubico is recalling a line of security keys used by the U.S. government due to a firmware flaw. The company issued a security advisory today that warned of an issue in YubiKey FIPS Series devices with firmware versions 4.4.2 and 4.4.4 that reduced the randomness of the cryptographic keys it generates. The security keys are used by thousands of federal employees on a daily basis, letting them securely log-on to their devices by issuing one-time passwords.

The problem in question occurs after the security key powers up. According to Yubico, a bug keeps “some predictable content” inside the device’s data buffer that could impact the randomness of the keys generated. Security keys with ECDSA signatures are in particular danger. A total of 80 of the 256 bits generated by the key remain static, meaning an attacker who gains access to several signatures could recreate the private key.

Boing Boing post.

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MongoDB Offers Field Level Encryption

MongoDB now has the ability to encrypt data by field:

MongoDB calls the new feature Field Level Encryption. It works kind of like end-to-end encrypted messaging, which scrambles data as it moves across the internet, revealing it only to the sender and the recipient. In such a “client-side” encryption scheme, databases utilizing Field Level Encryption will not only require a system login, but will additionally require specific keys to process and decrypt specific chunks of data locally on a user’s device as needed. That means MongoDB itself and cloud providers won’t be able to access customer data, and a database’s administrators or remote managers don’t need to have access to everything either.

For regular users, not much will be visibly different. If their credentials are stolen and they aren’t using multifactor authentication, an attacker will still be able to access everything the victim could. But the new feature is meant to eliminate single points of failure. With Field Level Encryption in place, a hacker who steals an administrative username and password, or finds a software vulnerability that gives them system access, still won’t be able to use these holes to access readable data.

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How Apple’s “Find My” Feature Works

Matthew Green intelligently speculates about how Apple’s new “Find My” feature works.

If you haven’t already been inspired by the description above, let me phrase the question you ought to be asking: how is this system going to avoid being a massive privacy nightmare?

Let me count the concerns:

  • If your device is constantly emitting a BLE signal that uniquely identifies it, the whole world is going to have (yet another) way to track you. Marketers already use WiFi and Bluetooth MAC addresses to do this: Find My could create yet another tracking channel.

  • It also exposes the phones who are doing the tracking. These people are now going to be sending their current location to Apple (which they may or may not already be doing). Now they’ll also be potentially sharing this information with strangers who “lose” their devices. That could go badly.

  • Scammers might also run active attacks in which they fake the location of your device. While this seems unlikely, people will always surprise you.

The good news is that Apple claims that their system actually does provide strong privacy, and that it accomplishes this using clever cryptography. But as is typical, they’ve declined to give out the details how they’re going to do it. Andy Greenberg talked me through an incomplete technical description that Apple provided to Wired, so that provides many hints. Unfortunately, what Apple provided still leaves huge gaps. It’s into those gaps that I’m going to fill in my best guess for what Apple is actually doing.

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Fraudulent Academic Papers

The term “fake news” has lost much of its meaning, but it describes a real and dangerous Internet trend. Because it’s hard for many people to differentiate a real news site from a fraudulent one, they can be hoodwinked by fictitious news stories pretending to be real. The result is that otherwise reasonable people believe lies.

The trends fostering fake news are more general, though, and we need to start thinking about how it could affect different areas of our lives. In particular, I worry about how it will affect academia. In addition to fake news, I worry about fake research.

An example of this seems to have happened recently in the cryptography field. SIMON is a block cipher designed by the National Security Agency (NSA) and made public in 2013. It’s a general design optimized for hardware implementation, with a variety of block sizes and key lengths. Academic cryptanalysts have been trying to break the cipher since then, with some pretty good results, although the NSA’s specified parameters are still immune to attack. Last week, a paper appeared on the International Association for Cryptologic Research (IACR) ePrint archive purporting to demonstrate a much more effective break of SIMON, one that would affect actual implementations. The paper was sufficiently weird, the authors sufficiently unknown and the details of the attack sufficiently absent, that the editors took it down a few days later. No harm done in the end.

In recent years, there has been a push to speed up the process of disseminating research results. Instead of the laborious process of academic publication, researchers have turned to faster online publishing processes, preprint servers, and simply posting research results. The IACR ePrint archive is one of those alternatives. This has all sorts of benefits, but one of the casualties is the process of peer review. As flawed as that process is, it does help ensure the accuracy of results. (Of course, bad papers can still make it through the process. We’re still dealing with the aftermath of a flawed, and now retracted, Lancet paper linking vaccines with autism.)

Like the news business, academic publishing is subject to abuse. We can only speculate the motivations of the three people who are listed as authors on the SIMON paper, but you can easily imagine better-executed and more nefarious scenarios. In a world of competitive research, one group might publish a fake result to throw other researchers off the trail. It might be a company trying to gain an advantage over a potential competitor, or even a country trying to gain an advantage over another country.

Reverting to a slower and more accurate system isn’t the answer; the world is just moving too fast for that. We need to recognize that fictitious research results can now easily be injected into our academic publication system, and tune our skepticism meters accordingly.

This essay previously appeared on

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Germany Talking about Banning End-to-End Encryption

Der Spiegel is reporting that the German Ministry for Internal Affairs is planning to require all Internet message services to provide plaintext messages on demand, basically outlawing strong end-to-end encryption. Anyone not complying will be blocked, although the article doesn’t say how. (Cory Doctorow has previously explained why this would be impossible.)

The article is in German, and I would appreciate additional information from those who can speak the language.

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