BC TECH
Saved by @ThomassRichards

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.
Previously used a method called "swapping" with secret parameters
* differential privacy is open and we can talk about privacy loss/accuracy tradeoff
* swapping assumed limitations of the attackers (e.g. limited computational power)
Needed to design the algorithms to get the accuracy we need it and tune the privacy loss based on that.

Change in the meaning of "privacy" as relative -- it requires a lot of explanation and overcoming organizational barriers.
By 2017 thought they had a good understanding of how differential privacy would fit -- just use the new algorithm where the old one was used, to create the "micodata detail file".
Surprises:
* different groups at the Census thought that meant different things
* before, states were processed as they came in. Differential privacy requires everything be computed on at once
* required a lot more computing power
* differential privacy system has to be developed with real data; can't use simulated data to do this because the algorithms in the literature weren't designed for dats anything like as complex as the real data (multiracial people, different kinds of households, etc)
* to understand the privacy/accuracy trade-off requires a lot of runs, representing a *lot* of computer time
Census bureau was 100% behind the move
* initial implementation was by Dan Kiefer, who took a sabbatical
* expanded team to with Simson and others
* 2018 end to end test
* original development was on an on-prem Linux cluster
* then got to move to AWS Elastic compute... but the monitoring wasn't good enough and had to create their own dashboard to track execution
* it wasn't a small amount of compute
* republished the 2010 census data using the differentially private algorithm and then had a conference to talk about it
* ... it wasn't well-received by the data users who thought there was too much error
For example: if we add a random value to a child's age, we might get a negative value, which probably won't happen to a child's age.

If you avoid that, you might add bias to the data. How to avoid that? Let some data users get access to the measurement files [I don't follow]
In summary, this is retrofitting the longest-running statistical program in the country with differential privacy. Data users have had some concerns, but believe it will all come out.
Code is up on github and papers are up online. (@xchatty have some links?)

[end of talk]

More from Lea Kissner

Lea Kissner
Lea Kissner
@LeaKissner
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" 🥁
TECH
Lea Kissner
Lea Kissner
@LeaKissner
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.
POLITICS
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Lea Kissner
Lea Kissner
@LeaKissner
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]
WORLD
Lea Kissner
Lea Kissner
@LeaKissner
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!]
TECH
Lea Kissner
Lea Kissner
@LeaKissner
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
SCIENCE

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Novid Houellebecq (That's Hollaback)
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@GarouGothic
I want to explain what happened to tumblr overnight. And why Twitter as reached it's dream (or have come ever so close to it)

Yahoo, who bought Tumblr years ago, used to have a huge adult presence on the early net. They allowed adult groups and what not.

However, people and bots (just like now) misused the service, and Yahoo were forced to make a choice. They made private the groups (and later closed them down and sold some of it to other companies) and then ended their chatrooms on yahoo messenger...

after a incident with one of the chatrooms vid cams. The damage was done, Yahoo Messenger lost a lot of people - and with the closing of the groups - backpage and Craigslist came more important.

Now backpage is no more and Craigslist is slowly passing away. Tumblr had a semi strong community, but once 2014 came around and both porn, and political bots exploded the quality started to go down,
TECH
Shaun Russell
Shaun Russell
@_ShaunRussell
"I really want to break into Product Management"

make products.

"If only someone would tell me how I can get a startup to notice me."

Make Products.

"I guess it's impossible and I'll never break into the industry."

MAKE PRODUCTS.

Courtesy of @edbrisson's wonderful thread on breaking into comics – https://t.co/TgNblNSCBj – here is why the same applies to Product Management, too.


There is no better way of learning the craft of product, or proving your potential to employers, than just doing it.

You do not need anybody's permission. We don't have diplomas, nor doctorates. We can barely agree on a single standard of what a Product Manager is supposed to do.

But – there is at least one blindingly obvious industry consensus – a Product Manager makes Products.

And they don't need to be kept at the exact right temperature, given endless resource, or carefully protected in order to do this.

They find their own way.
TECH
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Tinker \u274e
Tinker ❎
@TinkerSec
Singing the Blues:
Taking Down an Insider Threat

"I had all of the advantages. I was already inside the network. No one suspected me. But they found my hack, kicked me off the network...

...and physically hunted me down."


Many pentests start from the outside, wanting to see how the perimeter might be breached.

This pentest started from the inside. My client wanted to assume they had already been breached, and, if breached, how far could an attacker go.

Could they stop me once I was inside?

So they snuck me in. Disguised me as a new employee. Gave me a work computer, an ID badge, an account in their system... hell, I even had a cubicle w/my assumed name on it.

The only person who knew who I really was was their CISO. Everyone else thought I was Jeremy in Marketing.

During most of the first morning, I completed onboarding, made introductions, and completed menial tasks.

But I had to act quick. I only had a week onsite. I had to hack their network while not raising suspicion.

So I set about it.

You have to understand... most "Internal Pentests" are straight forward. The hard part is breaching the network, but once you're inside, it's a target rich environment. End of Life computers, default passwords, everyone a Local Administrator...
TECH
Mukund Mohan
Mukund Mohan
@mukund
EV Battery overview
Batteries are the key differentiator between the various EV manufacturers. The amount of energy stored in the battery determines the range of the EV, thought to be a major limitation on EV sales.


Consumers tend to worry that an EV with a range of 80 to 250 miles on a single charge would be inconvenient for long trips due to the time it takes to recharge the battery. Commercial batteries need to ensure there is quick recharge and less time between charges


The lithium-ion battery is important because it makes EVs expensive than ICEs. Battery costs per kilowatt-hour (kWh) declined from roughly $1,000 per kWh in 2010 to $227 in 2016


Lithium-ion batteries made up 70 percent of the rechargeable battery market in 2016
BNEF projects that global production capacity for lithium-ion batteries will increase from 103 gigawatt-hours (GWh) in the first quarter of 2017 to 273 GWh by 2021.


The battery manufacturing supply chain has three main parts:

cell manufacturing,

module manufacturing, and

pack assembly.
TECH
Aviral Bhatnagar
Aviral Bhatnagar
@aviralbhat
Fintech firms will become digital layers around central banks, just like banks were physical layers

Central banks will create plug and play digital infrastructure (e.g. UPI, Aadhar) on which fintech products are built

Central banks will enable fintechs to replace banks
TECH

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IT WAS RISHI KANADA WHO GAVE THE ATOMIC THEORY & TALKED ABOUT THE GRAVITY OF EARTH, 2600 YEARS BEFORE AN APPLE FELL IN FRONT OF NEWTON'S EYES:

Scientists of the modern world credit an English scientist John Dalton (1766 CE -1844 CE) for the Atomic Theory.


And this is because, most of us are not even aware of an ancient Indian Sage named Kanada, who was the first to formulate the theory of atoms, almost 2600 yrs before Dalton and talk about earth's gravity.


Rishi Kanada was born around 600 BCE in Dwarka, Gujarat and he was the son of a philosopher named Ulka. He was fascinated with the minute detailing of the things right from his childhood. Once, when he was very young, he accompanied his father on a journey to Prayaga.


He saw plentiful grains scattered along the path leading to the shore of river Ganga. It's a tradition in Hindu families to scatter the grains for the ants and birds to feed on them. Suddenly, an ant caught his attention, who was feeding on a rice grain.


He was mesmerised by this very fact that how a small grain of rice becomes food for the ant but to satisfy the hunger of a person so many grains are needed together. This incidence made him realize the importance of a single grain of rice.
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Steve Stewart-Williams
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THREAD: 12 Things Everyone Should Know About IQ

1. IQ is one of the most heritable psychological traits – that is, individual differences in IQ are strongly associated with individual differences in genes (at least in fairly typical modern environments). https://t.co/3XxzW9bxLE


2. The heritability of IQ *increases* from childhood to adulthood. Meanwhile, the effect of the shared environment largely fades away. In other words, when it comes to IQ, nature becomes more important as we get older, nurture less. https://t.co/UqtS1lpw3n


3. IQ scores have been increasing for the last century or so, a phenomenon known as the Flynn effect. https://t.co/sCZvCst3hw (N ≈ 4 million)

(Note that the Flynn effect shows that IQ isn't 100% genetic; it doesn't show that it's 100% environmental.)


4. IQ predicts many important real world outcomes.

For example, though far from perfect, IQ is the single-best predictor of job performance we have – much better than Emotional Intelligence, the Big Five, Grit, etc. https://t.co/rKUgKDAAVx https://t.co/DWbVI8QSU3


5. Higher IQ is associated with a lower risk of death from most causes, including cardiovascular disease, respiratory disease, most forms of cancer, homicide, suicide, and accident. https://t.co/PJjGNyeQRA (N = 728,160)
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Anu Satheesh \U0001f1ee\U0001f1f3
Anu Satheesh 🇮🇳...
@AnuSatheesh5
Thiruvizha Mahadeva Kshetram
#Alappuzha 
#Keralatemples 🚩

Thiruvizha Mahadeva Kshetram is located in Cherthala and it is believed that Prathishta of temple was done by Vilwamangalam Swamy. Paramashiva is Swayambhu here and is worshipped as Kalakandha which means who swallowed


Halahala visham to save the world during Samudra mathanam. 

It is a famous temple where people seek the blessings, for curing the Kaivisham. The poison given by someone to destroy a person is made to vomit here. This is removed by making them vomit the poison by a special


medicine.
The medicine for vomiting is made from a plant near temple by Palodathu family. The milk offered to Bhagwan is mixed with the extracts of the plant.

Story says that once this place was a dense forest, and a woman was looking for the presence of a tortoise in the pond


and the tip of her stick hit the bottom and it started bleeding in the pond. 
Frightened, the lady informed every one and after searching in pond people found Swayambhu Lingam inside the pond. Thus Prathishta was done here.

Om Namah Shivaye
Shambo Mahadeva
🙏🕉🙏
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Patrick Chovanec
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I'm going to do two history threads on Ethiopia, one on its ancient history, one on its modern story (1800 to today). 🇪🇹

I'll begin with the ancient history ... and it goes way back. Because modern humans - and before that, the ancestors of humans - almost certainly originated in Ethiopia. 🇪🇹 (sub-thread):


The first likely historical reference to Ethiopia is ancient Egyptian records of trade expeditions to the "Land of Punt" in search of gold, ebony, ivory, incense, and wild animals, starting in c 2500 BC 🇪🇹


Ethiopians themselves believe that the Queen of Sheba, who visited Israel's King Solomon in the Bible (c 950 BC), came from Ethiopia (not Yemen, as others believe). Here she is meeting Solomon in a stain-glassed window in Addis Ababa's Holy Trinity Church. 🇪🇹


References to the Queen of Sheba are everywhere in Ethiopia. The national airline's frequent flier miles are even called "ShebaMiles". 🇪🇹
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Nicolas
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A brief analysis and comparison of the CSS for Twitter's PWA vs Twitter's legacy desktop website. The difference is dramatic and I'll touch on some reasons why.

Legacy site *downloads* ~630 KB CSS per theme and writing direction.

6,769 rules
9,252 selectors
16.7k declarations
3,370 unique declarations
44 media queries
36 unique colors
50 unique background colors
46 unique font sizes
39 unique z-indices

https://t.co/qyl4Bt1i5x


PWA *incrementally generates* ~30 KB CSS that handles all themes and writing directions.

735 rules
740 selectors
757 declarations
730 unique declarations
0 media queries
11 unique colors
32 unique background colors
15 unique font sizes
7 unique z-indices

https://t.co/w7oNG5KUkJ


The legacy site's CSS is what happens when hundreds of people directly write CSS over many years. Specificity wars, redundancy, a house of cards that can't be fixed. The result is extremely inefficient and error-prone styling that punishes users and developers.

The PWA's CSS is generated on-demand by a JS framework that manages styles and outputs "atomic CSS". The framework can enforce strict constraints and perform optimisations, which is why the CSS is so much smaller and safer. Style conflicts and unbounded CSS growth are avoided.
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