In more Securing Democracy at #enigma2021, @ChrFolini talking about "THE ADVENTUROUS TALE OF ONLINE VOTING IN

Switzerland is a direct democracy where citizens get to vote at least 4x/year, with a lot of mail-in voting. We have a long history of online voting.

Disclaimer: THIS IS NOT SWEDEN.

[I get the picture that @ChrFolini has had to explain the difference several times.]

Process around mail-in ballots.

[tl;dr it's very complicated and wasn't threat-modeled until recently]

But the in-person ballots are complicated, too!

Most security folks don't think that we can't make a secure online voting system.

@ChrFolini says this is because of encryption
[Note: this is not the main reason that a lot of people cite -- we're more worried about things like malware but it's complicated]

Next up in Privacy Technology at #enigma2021, Kelly Huang from @ethyca speaking about "GONE, BUT NOT "FORGOTTEN"—TECHNICAL & PRACTICAL CHALLENGES IN OPERATIONALIZING MODERN PRIVACY

Just imagine there's a global pandemic forcing everyone to stay home and buy their stuff over the internet. And you've been working on your sanitization-on-demand startup. You've got more users than you can count! ... literally, because your data's all over.

Now you're a multi-national international country with privacy issues because your information is all over the place.

Now a user writes to request you delete their data. Where is it? How do you do that? Who's responsible for privacy in your business.

How do you operationalize privacy rights?

Primary stakeholders:
* Legal
* Business
* Engineering

We spend a lot of time on Twitter analyzing the legal rulings, but it's harder where the "rubber meets the code" 🥁

We're kicking off the Privacy Tech session at #enigma2021 with Mitch Negus speaking about "NO DATA, NO PROBLEM—GIVING NUCLEAR INSPECTORS BETTER TOOLS WITHOUT REVEALING STATE

A nuclear catastrophe hasn't occurred... yet. So we need to stay vigilant. Nuclear inspectors go in according to treaties to check what's going on and check compliance with treaty rules.

But as sophisticated analytics become more common, states will only want to share the minimum amount of information necessary under the treaty.

But perhaps we can use MPC -- secure multi-party computation

Yao's garbled circuits were first demonstrated on the millionaire's problem -- figuring out who's richer without revealing actual amounts.

Used for other things like cryptocurrency these days.

Can we use this for nuclear inspection?

MPC can be used to compute anything computed by a computer [but it's expensive!]

Last up in Privacy Tech for #enigma2021, @xchatty speaking about "IMPLEMENTING DIFFERENTIAL PRIVACY FOR THE 2020

Differential privacy was invented in 2006. Seems like a long time but it's not a long time since a fundamental scientific invention. It took longer than that between the invention of public key cryptography and even the first version of SSL.

But even in 2020, we still can't meet user expectations.
* Data users expect consistent data releases
* Some people call synthetic data "fake data" like
"fake news"
* It's not clear what "quality assurance" and "data exploration" means in a DP framework

We just did the 2020 US census
* required to collect it by the constitution
* but required to maintain privacy by law

But that's hard! What if there were 10 people on the block and all the same sex and age? If you posted something like that, then you would know what everyone's sex and age was on the block.

Last talk about Securing Democracy at #enigma2021: @jackhcable speaking about "THE FULL STACK PROBLEM OF ELECTION

Let's imagine that elections use all the security measures security people have been advocating: risk-limiting audits, paper ballots, etc. Would people trust the elections more?

Jack would argue no. Most people don't understand this stuff and most of the claims people are making can't be disproven. And are massively bogus already.

Georgia did a full recount on paper ballots and it very much didn't stop people from doubting the election!

Are election security results in vain? The point of election security is to convince the loser they lost.

No! Have to focus on the whole stack, from election infrastructure to campaigns to people and mis/dis-informaton

One takeaway from the talk: the parts of the stack must work in tandem. Can't fight misinformation in a vacuum, but must build on other election security measures.

Next up at #enigma2021, Sanghyun Hong will be speaking about "A SOUND MIND IN A VULNERABLE BODY: PRACTICAL HARDWARE ATTACKS ON DEEP LEARNING"

(Hint: speaker is on the

In recent years ML models have worked from research labs to production, which makes ML security important. Adversarial ML research studies how to mess with ML

For example by messing with the training data (c.f. Tay which became super-racist super-fast) or by foiling ML models by changing inputs in ways humans can't see.

Prior work considers ML models in a standalone, mathematical way
* looks at the robustness in an isolated manner
* doesn't look at the whole ecosystem and how the model is used -- ML models are running in real hardware with real software which has real vulns!

This talk focuses on hardware-level vulnerabilities. This is particularly interesting because these can break cryptographic guarantees (because those are outside of their threat models)
e.g. fault injection attacks, side-channel attacks