What Your Phone Sends Every 5 Minutes to Apple or Google

What Your Phone Sends Every 5 Minutes to Apple or Google

Apple’s push into privacy may be mostly talk as a new privacy study analyzed which data smartphones transmit to Apple and Google, even with telemetry options disabled.

It turns out, iPhones and Androids not only send a number of identifiers on average every 5 minutes, some network connections even include location and nearby devices.

Professor Doug Leith used a Google Pixel 2 and and iPhone 8 to uncover this data collection by iOS and Android and found out: It is near impossible to avoid it.

Is Your Phone Spying on You?

Is Your Phone Spying on You?

In case you’re wondering why you would want to “de-Google” your phone, then watch this Al Jazeera documentary.

In mid-2020, a mobile phone belonging to an Al Jazeera Arabic investigative team was hacked. Over the next few months, reporter Tamer Almisshal and the Canadian research group Citizen Lab investigated Pegasus, the sophisticated spyware used.

Pegasus is manufactured by an Israeli technology company called the NSO Group and is among the most advanced spyware in the world. It can access and infiltrate a smartphone without the owner clicking a link, opening an email or even answering their phone – meaning it can go undetected.

This investigation exposes how Pegasus works, how governments like Saudi Arabia and the UAE have bought the hugely expensive spyware and how it has been used beyond the stated intentions of the NSO Group of “developing technology to prevent and investigate terror and crime” – including to target journalists.

The Beauty of Data Privacy Engineering

The Beauty of Data Privacy Engineering

Privacy engineering is an emerging discipline within the software and data engineering domains aiming to provide methodologies, tools, and techniques such that the engineered systems provide acceptable levels of privacy.

In this talk, learn about Databricks’ recent work on anonymization and privacy preserving analytics on large scale geo location datasets.

In particular, the focus is on how to scale anonymization and geospatial analytics workloads with Spark, maximizing the performance by combining multi-dimensional spatial indexing with Spark in-memory computations.

In production, we have successfully achieved 1500+ times enhancements in terms of geo location anonymization, and 10+ times enhancements on nearest neighbour search based on anonymized geo datasets.