Categories
Security & Privacy

Twelve Million Phones, One Dataset, Zero Privacy

Twelve Million Phones, One Dataset, Zero Privacy

is part one of One nation, tracked, an New York Times investigation series of smart phone information tracking and by Stuart A. Thompson and Charlie Warzel, within their privacy project. The research covers multiple topics, only starting out with an analysis of the potential contained in smartphone tracking information.

What we learned from the spy in your pocket.

Twelve Million Phones, One Dataset, Zero Privacy

The authors analyse a large dataset of location information from New York and Washington, DC, cell phone users. With the analysis, the article debunks myths about data privacy. The key takeaway of the analysis, to my interpretation are:

Twelve Million Phones - One Mobile Phone User in Munich
Mobile Phone User – Munich
  1. Data is not anonymous – the authors successfully identified a Senior Defense Department official and his wife. And this was possible during the Women’s March. According to authors, nearly half a million descended on the capital for this event. (Other sources only mention one hundred thousand attendants)
  2. Data is not safe – the authors point out complex relationships of companies in the tracking business. Complexity makes it impossible to ensure ownership. There is no foolproof way for anyone or anywhere in the chain to prevent data from falling into the hands of a foreign security service.
  3. Affected persons cannot consent – the authors criticism seems reasonable. Virtually all companies involved with tracking require user consent. And even cell phones make the geo-tracking feature visible to users. Only barely anyone in the business makes purpose transparent. In other words, no company prominently announce how they package and sell data or insight.

One Nation, Tracked

The article is a creepy read, but worth the time spending. The series One Nation, Tracked continues with 6 other parts:

  1. discussing how to Protect Yourself
  2. National Security, which is for the the US in the article.
  3. details on How it works
  4. individual spying in One Neighborhood
  5. Protests is about how this business betrays democracy
  6. And offers Solutions through privacy rights.

Source: Opinion | Twelve Million Phones, One Dataset, Zero Privacy – The New York Times

Categories
Business & MBA

Animation: Visualizing Moore’s Law in Action (1971-2019)

Moore’s Law in Action: You’ll probably remember the prediction back from your days in University. In essence, Mr. Moore, founder of Fairchild Semi and CEO of Intel, predicted the density of transistors in modern integrated systems will double about every 18 months. He was right for a long time, while many predicted the end of his law. Visual Capitalist today linked a illustration showing the law in Action up to 2019.

Moore's Law
Moore’s Law

Can the predictions from Moore’s Law keep up with technological innovation spanning almost 50 years? Watch this stunning animation to find out.

Source: Animation: Visualizing Moore’s Law in Action (1971-2019)

Categories
Uncategorized

The most advanced MySQL raytracer on the market right now.

Raytracing with MySQL

WTF of the day. The most advanced MySQL raytracer on the market right now. A raytracer, written in a single SELECT statment, that MySQL is able to process into an image. Pure Demoscene spirit here, whatever it is, make it run an animation or raytrace some spheres, something beautiful it was not meant to produce in first place.

via BoingBoing.

Categories
Product, Projekt & Agile

Essential Product Metrics

Data driven product management requires measurements and metrics. Over at Product Management Insider, shares some detail about the pirate („AARRR!“) system and the HEART model.

The article is here.

Categories
Product, Projekt & Agile

From Data to Product

In an ideal world, product managers have plenty of data they can use to validate their idea before building the wrong product. Yana Yushkina describes her journey from a Data Analyst to a Product Manager.

She talks about characteristics a good PM should bring, that include foundational analytical understanding, curiosity not just for technology but to search for the right answers in data, a sense of responsibility and the ability to communicate.

All of that combined with the right metrics at hand and self sufficient mindset will give a Product Manager the right answer from data.

Via Product School.

Categories
Security & Privacy

Google stored G Suite passwords in plaintext

In today’s edition of privacy related topics, it is Google that apparently stored customer passwords in plaintext. Google didn’t disclose which (enterprise) customers have been affected, but was clear that improper access is out of question. With this recent incident, Google joins ranks of Facebook, Instagram, but also Twitter and LinkedIn.

Google says it discovered a bug that caused some of its enterprise G Suite customers to have their passwords stored in an unhashed form for about 14 years.

Source: Google stored some G Suite passwords in plaintext for 14 years

Categories
Business & MBA Security & Privacy

Why Do Companies Need All That Personal Data They’re Collecting?

It’s the Tech perspective, but has the potential for a good debate. Under GDPR it’s not even compliant and still plenty of companies collect all data they can get hold of. Driven by Big Data vendors telling the narrative of Data Lakes, that only require you the data today, should you want to ask any question you don’t know yet in the future.

Only – have you ever come up with a question that you could not answer based on the data that is already available? Based on data that you collected in a Data Lake?

Big disclaimer: personally I don’t conclude with the assumptions made in the initial article, but the question is worth thinking about. In particular because most organizations I met until today are not metric driven in first place.

Source: Ask Slashdot: Why Do Companies Need All That Personal Data They’re Collecting? – Slashdot

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Categories
Internet & Cloud

Not so big data.

Chris Stucchio hat einen interessanten Punkt bzgl. Big Data. Nämlich, dass Big Data heißt gar nicht Big ist. Nur weil Excel einen Datensatz nicht öffnen kann, heisst das nicht automatisch, dass Big Data Tools – in seinem Aufsatz Hadoop – notwendig sind. Gigabyteweise Daten lassen sich auch anders verarbeiten. Moderne Hardware hat nicht selten mehrere GB an Hauptspeicher. Die Geräte bei Mediamarkt waren vergangenen Samstag alleine mit mindestens 8Gb ausgestattet. Das heisst natürlich nicht, dass Hadoop oder vergleichbare Tools gar keinen Anwendungsfall hätten, aber die Use-Cases sind vielleicht anders gelagert, als man auf den ersten Gedanken annimmt.

Quelle: Dont use Hadoop – your data isnt that big – Chris Stucchio

Categories
Internet & Cloud Security & Privacy

Data and Goliath

Data and Goliath
Data and Goliath

Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World

Bruce Schneier wrote a book about Big Data, mass surveilance and the Internet of Things. Schneier talks about how this effects society and what to do about the increasing datarization of everything we’re doing.

Categories
Internet & Cloud

Six security issues to tackle before encrypting cloud data

The six issues that must be addressed are:
	- Breach notification and data residency
	- Data management at rest
	- Data protection in motion
	- Encryption key management
	- Access controls
	- Long-term resiliency of the encryption system

via: Six security issues to tackle before encrypting cloud data.