"surveillance" entries

Four short links: 9 March 2016

Four short links: 9 March 2016

Surveillance Capitalism, Spark in Jupyter, Spoofing Fingerprints, and Distributing SSH Keys

  1. The Secrets of Surveillance CapitalismThe assault on behavioral data is so sweeping that it can no longer be circumscribed by the concept of privacy and its contests. […] First, the push for more users and more channels, services, devices, places, and spaces is imperative for access to an ever-expanding range of behavioral surplus. Users are the human nature-al resource that provides this free raw material. Second, the application of machine learning, artificial intelligence, and data science for continuous algorithmic improvement constitutes an immensely expensive, sophisticated, and exclusive 21st century “means of production.” Third, the new manufacturing process converts behavioral surplus into prediction products designed to predict behavior now and soon. Fourth, these prediction products are sold into a new kind of meta-market that trades exclusively in future behavior. The better (more predictive) the product, the lower the risks for buyers, and the greater the volume of sales. Surveillance capitalism’s profits derive primarily, if not entirely, from such markets for future behavior. (via Simon St Laurent)
  2. Thunder — Spark-driven analysis from Jupyter notebooks (open source).
  3. Hacking Mobile Phones Using 2D-Printed Fingerprints (PDF) — equipment costs less than $450, and all you need is a photo of the fingerprint. (like those of government employees stolen en masse last year)
  4. SSHKeyDistribut0r (Github) — A tool to automate key distribution with user authorization […] for sysop teams.
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Four short links: 3 February 2016

Four short links: 3 February 2016

Security Forecast, Machine Learning for Defence, Retro PC Fonts, and Cognitive Psych Research

  1. Software Security Ideas Ahead of Their Time — astonishing email exchange from 1995 presaged a hell of a lot of security work.
  2. Doxxing Sherlock — Cory Doctorow’s ruminations on surveillance, Sherlock, and what he found in the Snowden papers. What he found included an outline of intelligence use of machine learning.
  3. Old-School PC Fonts — definitive collection of ripped-from-the-BIOS fonts from the various types of PCs. Your eyes will ache with nostalgia. (Or, if you’re a young gun, wondering how anybody wrote code with fonts like that) (my terminal font is VT220 because it makes me happy and productive)
  4. Cognitive Load: Brain GemsWe distill the latest behavioural economics & consumer psychology research down into helpful little brain gems.
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Four short links: 12 June 2014

Four short links: 12 June 2014

Our New Robot Overlords, Open Neuro, Anti-Surveillance Software, and LG's TV Made of Evil and Tears

  1. Norbert Weiner (The Atlantic) — His fears for the future stemmed from two fundamental convictions: We humans can’t resist selfishly misusing the powers our machines give us, to the detriment of our fellow humans and the planet; and there’s a good chance we couldn’t control our machines even if we wanted to, because they already move too fast and because increasingly we’re building them to make decisions on their own. To believe otherwise, Wiener repeatedly warned, represents a dangerous, potentially fatal, lack of humility.
  2. Open Ephys — open source/open hardware tools for neuro research. (via IEEE)
  3. Startups Selling Resistance to Surveillance (Inc) — growing breed of tools working on securing their customers’ communications from interception by competitors and states.
  4. Not-So-Smart TV (TechDirt) — LG’s privacy policy basically says “let us share your viewing habits, browsing, etc. with third parties, or we will turn off the `smart’ features in your smart TV.” The promise of smart devices should be that they get better for customers over time, not better for the vendor at the expense of the customer. See Weiner above.
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Four short links: 19 May 2014

Four short links: 19 May 2014

Surveillance Devices, Economic Apologies, Logo Trends, and Block Chain API

  1. Your Coffee Machine is Watching You (Mary Beard) — the future of surveillance isn’t more CCTV cameras, it’s every device ratting you out, all the time.
  2. Economics of Apologiesapologies work to restore relationships but are costly for the apologiser.
  3. Logo TrendsDimension and detail are necessarily removed so that these logos read properly on mobile screens. Designs have become more and more flat. Surfaces are plain and defined by mono-weight lines. Great examples.
  4. Chainthe Block Chain API for developers.
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Pursuing adoption of free and open source software in governments

LibrePlanet explores hopes and hurdles.

Free and open source software creates a natural — and even necessary — fit with government. I joined a panel this past weekend at the Free Software Foundation conference LibrePlanet on this topic and have covered it previously in a journal article and talk. Our panel focused on barriers to its adoption and steps that free software advocates could take to reach out to government agencies.

LibrePlanet itself is a unique conference: a techfest with mission — an entirely serious, feasible exploration of a world that could be different. Participants constantly ask: how can we replace the current computing environment of locked-down systems, opaque interfaces, intrusive advertising-dominated services, and expensive communications systems with those that are open and free? I’ll report a bit on this unusual gathering after talking about government.
Read more…

Comment: 1

Big data and privacy: an uneasy face-off for government to face

MIT workshop kicks off Obama campaign on privacy

Thrust into controversy by Edward Snowden’s first revelations last year, President Obama belatedly welcomed a “conversation” about privacy. As cynical as you may feel about US spying, that conversation with the federal government has now begun. In particular, the first of three public workshops took place Monday at MIT.

Given the locale, a focus on the technical aspects of privacy was appropriate for this discussion. Speakers cheered about the value of data (invoking the “big data” buzzword often), delineated the trade-offs between accumulating useful data and preserving privacy, and introduced technologies that could analyze encrypted data without revealing facts about individuals. Two more workshops will be held in other cities, one focusing on ethics and the other on law.

Read more…

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Four short links: 6 March 2014

Four short links: 6 March 2014

Repoveillance, Mobiveillance, Discovery and Orchestration, and Video Analysis

  1. Repo Surveillance NetworkAn automated reader attached to the spotter car takes a picture of every ­license plate it passes and sends it to a company in Texas that already has more than 1.8 billion plate scans from vehicles across the country.
  2. Mobile Companies Work Big DataMeanwhile companies are taking different approaches to user consent. Orange collects data for its Flux Vision data product from French mobile users without offering a way for them to opt-out, as does Telefonica’s equivalent service. Verizon told customers in 2011 it could use their data and now includes 100 million retail mobile customers by default, though they can opt out online.
  3. Serfdoma decentralised solution for service discovery and orchestration that is lightweight, highly available, and fault tolerant.
  4. Longomatcha free video analysis software for sport analysts with unlimited possibilities: Record, Tag, Review, Draw, Edit Videos and much more! (via Mark Osborne)
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The technical aspects of privacy

The first of three public workshops kicked off a conversation with the federal government on data privacy in the US.

Thrust into controversy by Edward Snowden’s first revelations last year, President Obama belatedly welcomed a “conversation” about privacy. As cynical as you may feel about US spying, that conversation with the federal government has now begun. In particular, the first of three public workshops took place Monday at MIT.

Given the locale, a focus on the technical aspects of privacy was appropriate for this discussion. Speakers cheered about the value of data (invoking the “big data” buzzword often), delineated the trade-offs between accumulating useful data and preserving privacy, and introduced technologies that could analyze encrypted data without revealing facts about individuals. Two more workshops will be held in other cities, one focusing on ethics and the other on law. Read more…

Comments: 7

How did we end up with a centralized Internet for the NSA to mine?

The Internet is naturally decentralized, but it's distorted by business considerations.

I’m sure it was a Wired editor, and not the author Steven Levy, who assigned the title “How the NSA Almost Killed the Internet” to yesterday’s fine article about the pressures on large social networking sites. Whoever chose the title, it’s justifiably grandiose because to many people, yes, companies such as Facebook and Google constitute what they know as the Internet. (The article also discusses threats to divide the Internet infrastructure into national segments, which I’ll touch on later.)

So my question today is: How did we get such industry concentration? Why is a network famously based on distributed processing, routing, and peer connections characterized now by a few choke points that the NSA can skim at its leisure?
Read more…

Comments: 7
Four short links: 9 December 2013

Four short links: 9 December 2013

Surveillance Demarcation, NYT Data Scientist, 2D Dart, and Bayesian Database

  1. Reform Government Surveillance — hard not to view this as a demarcation dispute. “Ruthlessly collecting every detail of online behaviour is something we do clandestinely for advertising purposes, it shouldn’t be corrupted because of your obsession over national security!”
  2. Brian Abelson — Data Scientist at the New York Times, blogging what he finds. He tackles questions like what makes a news app “successful” and how might we measure it. Found via this engaging interview at the quease-makingly named Content Strategist.
  3. StageXL — Flash-like 2D package for Dart.
  4. BayesDBlets users query the probable implications of their data as easily as a SQL database lets them query the data itself. Using the built-in Bayesian Query Language (BQL), users with no statistics training can solve basic data science problems, such as detecting predictive relationships between variables, inferring missing values, simulating probable observations, and identifying statistically similar database entries. Open source.
Comment: 1