Privacy Enhancing Computation

Better privacy for your data

Samadhi Jayawardena
LinkIT
4 min readApr 21, 2021

--

Photo by FLY:D on Unsplash

DATA, in this modern digital era data, is one of the most crucial aspects. According to the sixth edition of DOMO’s report, “Over 2.5 quintillion bytes of data are created every single day, and it’s only going to grow from there. By 2020, it’s estimated that 1.7MB of data will be created every second for every person on earth”. If this huge amount of data goes into the wrong hands then it would be an enormous disaster that we cannot even imagine.

Let me ask you one question. Have you ever thought twice before entering your personal data into websites or applications? Have you ever felt that it is unsafe to give your details? I am sure most of you have felt like this even once in your lifetime. It is a normal situation because even though modern-day technology has almost reached its peak, simultaneously the probability of data breaches and hacker attacks also have grown rapidly. Then here comes the solution, PRIVACY ENHANCING COMPUTATION.

You may wonder what this Privacy Enhancing computation means is. Simply this is a collection of technologies that provides better security and enhances the privacy of your data. This privacy-enhancing computation is a kind of a tech trend and it takes three forms as

  • Providing a secured environment for data to be processed
  • Usage of privacy-aware Machine learning for analytics
  • Keeping data confidential by transforming data and algorithms including homomorphic encryption.

Let me tell you why we need this Privacy Enhancing Computation. One of the main reasons is to prevent harm to the privacy of the users. Let’s say there is a system called ABC which does not have any protection in their system. So this is like a golden ticket for anyone who wants to use the data of this system without any permission. If this system has crucial data of their customers then this will be a threat to the users’ privacy. There are also some other reasons as human dignity violations, misinterpretations, etc.

Now let us take a look at Privacy Enhancing Computation technologies. When it comes to privacy-enhancing technologies we can mainly identify Homomorphic Encryption, Secure Multiparty Computation, Differential Privacy, and Trusted Execution Environments.

Screenshot by Author

Homomorphic Encryption

The first technology is Homomorphic Encryption. We can identify this as the most secure option in Privacy Enhancing Computation. Even though the name itself looks quite complicated this has a simple meaning. Basically, this technology lets data be processed but data will remain confidential. For example, let’s say that someone wants to do calculations or mathematical operations on some data. Simply this method allows users to process the calculation on ciphertext instead of real data. It means the user will never get to know the actual data because he is applying functions on encrypted data.

Secure Multiparty Computation

The next technology is secure multiparty computation. Let me explain this using an example. Let’s assume that a medical center wants to check a patient’s DNA with the DNA records of cancer patients. In this case, DNA is a kind of highly sensitive data. Despite the point that they can find if this patient has a higher risk of having cancer these kinds of data should not be revealed to any third party because it can be misused. In these kinds of situations, Secure Multiparty Computation protocols are very valuable. The reason is that using this protocol they can identify the most suitable category of cancer the patient’s DNA is similar to. It only reveals the most suitable category. In simple terms, Secure Multipart Computation means allowing multiple parties to operate on data together while keeping their own individual inputs secure.

Differential Privacy

The other technology is Differential Privacy which is a kind of algorithm. This algorithm basically analyzes and computes statistics on a data set. Then it will give a general dataset while describing the patterns. But it will not disclose information about individuals. Let’s say you want to analyze which is the most popular TV drama among people. You will take opinions about two dramas from 100 people. Then after analyzing data you will say that out of 100 people 70 people like ABC drama. Then the people who see your result will get to know that out of 100 people 70 like this ABC drama, but they will not know the 60 people who like this drama.

Trusted Execution Environments

Among the privacy-enhancing computation, technologies Trusted Execution Environments is likely to be the least secure one. This is a secure part of the main processor where data is stored, processed, and protected securely. This is widely used in most modern digital devices such as smartphones, tablets, etc.

In this article, I have discussed what is meant by Privacy Enhancing Computation and the type of Privacy Enhancing Computation Technologies. So in conclusion privacy is very important in this digital world. Especially when we roam in cyberspace we often face cyber threats. Day by day the number of cybercrimes and data breaches is increasing rapidly. Therefore this Privacy Enhancing Concept is very important. I hope you will gain some understanding about Privacy Enhancing Computation from my article.

If you enjoyed this article, please share it with your friends. Thanks for reading!

--

--