Archive for the ‘Smart-Phones’ Category

Introspection For Your iPhone (phone security)

Thursday, July 21st, 2016

Against the Law: Countering Lawful Abuses of Digital Surveillance by Andrew “bunnie’ Huang and Edward Snowden.

From the post:

Front-line journalists are high-value targets, and their enemies will spare no expense to silence them. Unfortunately, journalists can be betrayed by their own tools. Their smartphones are also the perfect tracking device. Because of the precedent set by the US’s “third-party doctrine,” which holds that metadata on such signals enjoys no meaningful legal protection, governments and powerful political institutions are gaining access to comprehensive records of phone emissions unwittingly broadcast by device owners. This leaves journalists, activists, and rights workers in a position of vulnerability. This work aims to give journalists the tools to know when their smart phones are tracking or disclosing their location when the devices are supposed to be in airplane mode. We propose to accomplish this via direct introspection of signals controlling the phone’s radio hardware. The introspection engine will be an open source, user-inspectable and field-verifiable module attached to an existing smart phone that makes no assumptions about the trustability of the phone’s operating system.

If that sounds great, you have to love their requirements:

Our introspection engine is designed with the following goals in mind:

  1. Completely open source and user-inspectable (“You don’t have to trust us”)
  2. Introspection operations are performed by an execution domain completely separated from the phone’s CPU (“don’t rely on those with impaired judgment to fairly judge their state”)
  3. Proper operation of introspection system can be field-verified (guard against “evil maid” attacks and hardware failures)
  4. Difficult to trigger a false positive (users ignore or disable security alerts when there are too many positives)
  5. Difficult to induce a false negative, even with signed firmware updates (“don’t trust the system vendor” – state-level adversaries with full cooperation of system vendors should not be able to craft signed firmware updates that spoof or bypass the introspection engine)
  6. As much as possible, the introspection system should be passive and difficult to detect by the phone’s operating system (prevent black-listing/targeting of users based on introspection engine signatures)
  7. Simple, intuitive user interface requiring no specialized knowledge to interpret or operate (avoid user error leading to false negatives; “journalists shouldn’t have to be cryptographers to be safe”)
  8. Final solution should be usable on a daily basis, with minimal impact on workflow (avoid forcing field reporters into the choice between their personal security and being an effective journalist)

This work is not just an academic exercise; ultimately we must provide a field-ready introspection solution to protect reporters at work.

You need to copy those eight requirements out to a file for editing. When anyone proposes a cybersecurity solution, reword as appropriate as your user requirements.

An artist conception of what protection for an iPhone might look like:


Interested in protecting reporters and personal privacy? Follow Andrew ‘bunnie’ Huang’s blog.

Sparksee Mobile Graph DB for iOS/Android

Wednesday, June 11th, 2014

Graph Databases power in-device analytical appplications: Sparksee Mobile, the first graph database available for iOS and Android.

From the post:

Mobile device data analytics is going to be an important issue in the next few years. Hardware improvements like more efficient batteries, larger memories and more conscious energy consumption will be crucial to allow for complex computations in such devices. Added to that, the analytics capability analytical engines embedded in a mobile device will also allow the users to gather and manage their own private data with analytic objectives at the tip of their fingers.

Graph databases will be important in that area with situations where the mobile device will have to solve different problems like the management of the mobile data, social network analytics, mobile device security, geo-localized medical surveillance and real time geo-localized travel companion services.

Sparksee 5 mobile is an important provider player for mobile analytics applications, being the first graph database for Android and iOS. Sparksee small footprint of less that 50Kbytes* makes it especially attractive for mobile devices along with its high performance capabilities and the compact storage space required. Sparksee is powered by a research-based technology that makes an intensive use of bitmaps allowing for the use of simple logic operations and remarkable data locality to solve graph analytics.

Do you want to be among the first applications making real use of the device hardware possibilities? Have you considered resolving your analytical operations in the device, storing & querying the information in a graph database instead of having an external server? Let us know what do you think about this new possibilities and which applications do you think will benefit more of having an in-device real time process.

Download Sparksee graph database mobile for free at:

You know, we used to talk about how to deliver topic maps to cellphones.

If merging were handled server-side, delivery of a topic map as a graph to a smartphone, that could be all the navigation capability that a smartphone user would need.

Something to think about, very seriously.

Erin McKean, founder, Reverb

Saturday, May 31st, 2014

10 Questions: Erin McKean, founder, Reverb by Chanelle Bessette.

From the introduction to the interview:

At OUP, McKean began to question how effective paper dictionaries were for the English language. Every word is a data point that has no meaning unless it is put in context, she believed, and a digital medium was the only way to link them together. If the printed dictionary is an atlas, she reasoned, the digital dictionary is a GPS device.

McKean’s idea was to create an online dictionary, dubbed Wordnik, that not only defined words but also showed how words related to each other, thereby increasing the chance that people can find the exact word that they are looking for. Today, the technology behind Wordnik is used to power McKean’s latest company, Reverb. Reverb’s namesake product is a news discovery mobile application that recommends stories based on contextual clues in the words of the article. (Even if that word is “lexicography.”)

Another case where i need a mobile phone to view a new technology. 🙁

I ran across DARLING, which promises it isn’t ready to emulate an IPhone on Ubuntu.

Do you know of another iPhone emulator for Ubuntu?


I Dream of “Jini”

Thursday, June 7th, 2012

The original title reads: Argus Labs Celebrates The Launch Of The Beta Version Of Jini, The App That Goes Beyond The Check-In, And Unveils 2012 Roadmap For The First Time. See what you think:

Argus Labs, a deep data, machine learning and mobile start-up operating out of Antwerp (Belgium), will celebrate the closed beta of the mobile application the night before LeWeb 2012 at Tiger-Tiger, Haymarket in London’s West-End. From 18th June, registered users will be able to download and start evaluating the first version of the intelligent application, called Jini.

Jini is a personal advisor that helps discover unknown relations and hyper-personalised opportunities. Jini feels best when helping the user out in serendipitous moments, or propose things that respond to the affinity its user has with its environment. Having access to hot opportunities and continuously being ‘in the know’ means a user can boost the quality of offline life.

Jini aims to raise the bar for private social networks by going beyond the check-in, saving the user the effort of doing too many manual actions. Jini applies machine learning with ambient sensing technology, so that the user can focus exclusively on having an awesome social sharing and discovery experience on smart-phones.

During the London launch event users will be able to sign up and exclusively download the first beta release of the app. The number of beta users is limited, so be fast. Argus Labs love to pioneer and will also have some goodies in store for the first 250 beta-users of the app.

See the post for registration information.

I sense a contradiction between being “…continuously being ‘in the know’ means a user can boost the quality of offline life.” How am I going to be ‘in the know’ if I am offline?

Still, I suspect there are opportunities here to merge diverse data sets to provide users with “hyper-personalized opportunities,” so long as it doesn’t interrupt one “hyper-personalized” situation to advise of another, potential “hyper-personalized” opportunity.

That would be like a phone call from an ex-girlfriend at an inopportune time. Bad joss.