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.

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.

The London “festival of A.I. and emerging technology” that takes place each June.

This year, due to Covid-19, the event took place completely online.

(For more about how CogX pulled that off, look here.)

One of the sessions veered towards privacy.

One of the most interesting sessions I tuned into was on privacy-preserving machine learning. This is becoming a hot topic, particularly in healthcare, and especially now due to the interest in applying machine learning to healthcare records that the coronavirus pandemic is helping to accelerate.

The Hook Up puts 10 indoor cameras to the test to figure out which one gives the most features while retaining your privacy.

My top 3 choices for those without the ability (or desire) to block cameras from the internet:

  1. EufyCam Pan & Tilt (Ships June): https://www.eufylife.com/activities/indoorcampreorder 
  2. IoTeX UCAM (Ships July): https://ucam.iotex.io/ 
  3. WyzeCam V2 (Shipping Now): https://amzn.to/2ZVdTWZ

Using data for machine learning and analytics can potentially expose private data. 

How can we leverage data while ensuring that private information remains private?

In this video, learn how differential privacy can be used to preserve privacy and get a demo on how you can use newly released open source system, WhiteNoise, to put DP into your applications.

Learn More:

Databricks  recently hosted this online tech talk on Delta Lake.

The General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) both aim to guarantee strong protection for individuals regarding their personal data and apply to businesses that collect, use, or share consumer data, whether the information was obtained online or offline. This remains one of the top priorities for the companies to be compliant and they are spending a lot of time and resources on being GDPR and CCPA compliant.

Your organization may manage hundreds of terabytes worth of personal information in your cloud. Bringing these datasets into GDPR and CCPA compliance is of paramount importance, but this can be a big challenge, especially for larger datasets stored in data lakes.

Can security surveillance systems and associated analytics work in a station environment without disrupting the rail network?

An interesting competition us underway in the UK that will surely raise privacy and security concerns the world over.

The Innovate UK challenge aims to develop a system capable of automatically detecting potential passenger/rail safety issues, intending to enhance manual control room activities and station security and safety as a whole. The vision is to have video data inform control room operators of potential problems as and even before they occur.

The Innovate UK challenge aims to develop a system capable of automatically detecting potential passenger/rail safety issues, intending to enhance manual control room activities and station security and safety as a whole. The vision is to have video data inform control room operators of potential problems as and even before they occur.