New technologies take time to develop, but we believe that with continued iteration we can build solutions that support a free and open Internet.

On Aug. 11, Facebook released a proposal for new privacy-enhancing technology on its website and advocated for a freer and more open Internet, mentioning that the new privacy-enhancing technology aims to protect users’ privacy and reduce Internet companies’ reliance on personal and third-party data. The new technology will help Internet companies filter the amount of personal information they do not have to process without affecting the way they show ads to people and measure the effectiveness of advertisers’ ads.

The Fate of Internet Companies: The Game of Privacy and Profit

Using “user profiles” to make money is a regular business model in the Internet industry, but the way user information is used directly determines whether the Internet company is at risk of violating user privacy.

Many of the major Internet companies that we are familiar with have been punished for improper use of user information.

In September 2017, Facebook was fined 1.2 million euros by the Spanish government after collecting personal information (including gender, religion, personal preferences, browsing history, etc.) from local users without informing them of its use and using it for its advertising business.

In 2018, Facebook was eventually fined $5 billion by the U.S. Federal Trade Commission (FTC) for working with Cambridge Analytica’s data analytics firm to use more than 87 million users’ data for big data work to influence the presidential election.

In June 2020, Google was fined $5 billion for tracking users’ Internet use in “untracked” browser mode and collecting user information through Google Analytics, Google Ad Manager, and other applications, as well as website plug-ins, including smartphone apps, regardless of whether users clicked on Google-supported ads.

Turning to China, the most impressive case is the DIDI incident in July this year, in which DIDI Travel APP was taken off the shelves by the State Internet Information Office on July 4 due to serious violations of the law on the collection and use of personal information. Then seven departments jointly stationed at DIDI to investigate the incident.

As the privacy regulatory environment continues to change, we have to admit that the model of Internet companies relying on digital advertising to make money is becoming increasingly risky. And for the Internet majors who always say they are high-tech companies, how to rely on technology to reduce this risk has become a subject that has to be considered.

Three major applications of privacy-enhancing technologies: secure multi-party computing (MPC), device-based autonomous learning, and differential privacy

In August of this year, Facebook released its privacy-enhancing technology and its latest solution. It was mentioned that Privacy Enhanced Technology (PET) minimizes the amount of data processed to help protect personal information. This technology can be used in many different environments, such as COVID-19 contact tracking, identifying urban relocation trends and sending electronic payments.

Meanwhile, Facebook has released three solutions for building and measuring personalized ads in conjunction with its practice - secure multi-party computing (MPC), device-based autonomous learning, and differential privacy. The following are brief descriptions of the three.

Secure Multi-Party Computing: Secure Multi-Party Computing (MPC) allows two or more organizations to work together while limiting the information to which participants have access. In MPC, data is encrypted end-to-end: during transmission, storage, and use, ensuring that neither party can see the other’s data.

Device-based autonomous learning: Device-based autonomous learning is similar to edge computing. It trains algorithms based on insights computed on the device without sending personal data (such as shopping lists or personal email addresses) to a remote server or cloud. This technology can be used to find new ways to display relevant ads without having to understand what users are doing on other applications and websites.

Differential privacy: Scoring privacy is a technique that can be used alone or applied to other privacy-enhancing techniques to protect data from re-identification. Differential privacy works by including carefully calculated “noise” in the data set. For example, if 118 people purchased a product after clicking on an ad, the Differentiated Privacy system adds or subtracts a random number from that number. As a result, people using the system will see a number like 120 or 114 instead of 118.

For more information, please visit the Facebook website at

https://about.fb.com/news/2021/08/privacy-enhancing-technologies-and-ads

Visionary social giants: Beyond technology

Back to Facebook’s release highlights, which states, “We’ve been investing for years in building a range of privacy-enhancing technologies and working with our peers to develop standards to support the next era.”

As early as last year, Facebook and partners tested a Private Lift Measurement solution that applies privacy-enhancing technology with secure multi-party computing to help advertisers add an additional layer of privacy to limit access to platforms like Facebook while understanding the effectiveness of their campaigns. Facebook mentioned that this solution will be widely available to advertisers in 2022. It will also be open sourced private computing solution framework to facilitate the industry to develop products based on this technology.

Facebook, as a giant, is well aware of this, so along with its privacy-enhancing technology, Facebook is calling on platforms, publishers, developers and other players to build industry standards and solutions. Data Use Cases

  • Data use cases: What are the most important issues that privacy-enhancing technologies need to address when advertisers are using Internet data?
  • Proposals: What proposals can we develop to use privacy-enhancing technologies well and without delaying the normal use of data?
  • Feedback: How can we collaborate to iterate and improve existing proposals?

Over the next few months, Facebook will be engaging more frequently with customers, peers and partners through events to discuss the next era of personalized experiences and how we can work together to develop solutions. We believe that through continued iteration, we can build solutions that support a free and open Internet."

Reference link.

https://www.facebook.com/business/news/building-for-the-future