Privacy Enhancing Computation
Believe it or not, data in internet, is forever! In a data driven world, COVID-19 has urged almost every organization to function in a cloud environment. When it comes to organizations, data privacy is always their primary concern and thanks to cybersecurity companies, who have managed to protect the data in internet using privacy enhancing technologies (PET). Privacy enhancing computation (PEC), being one in the PET has now become among the top technology trends of the year 2021 in Gartner.
“This trend enables organizations to collaborate on research securely across regions and with competitors without sacrificing confidentiality. This approach is designed specifically for the increasing need to share data while maintain privacy or security” (Privacy enhancing computation is one of Gartner's top tech trends in 2021, 2021)
In the technical point of view, privacy enhancing computation handles levels of technologies which uses mathematical schemes allowing sharing of data without compromising its privacy and security while it is being used and at rest. Levels include Homomorphic Encryption (HE), Secure Multiparty Computation (SMPC), Differential Privacy and Trusted Execution Environments (TEE) where Homomorphic Encryption being the most secure.
Looking away from technical definition, privacy enhancing computations functioning basics can be easily understood with this: Consider a friendly battle between you and your friend to guess the security pin number of each other. You could get a third person to judge the results by telling them the real pin but that will reveal your pin to the third person which is not safe. Instead, you both agree on a large random number, add the pin to that number and let know the new large number to the third person and they will inform if it’s a match. In this manner you will not reveal your pin to the third person and play the challenge. This is how PEC works in the basic view while the real scenario is played under several complex mathematical operations at the end offering a very safe method to share data confidentially.
HE, SMPC, TEE and Differential Privacy technological levels may seem of a new tech term to you, but surprisingly everyone of us are using it these days and that is functioning right in front of us!
• Do you trust this device?
• Confirm sign in
• Allow location access?
• Two factor authentications required
• Allow access to all photos?
Are some of the message boxes with yes/no options we get every time we use any data containing application or platform and yes, this is one of the levels in privacy enhancing tech we experience known as Trusted Execution Environment (TEE). As from experience we know access for such execution is allowed only from a main device of selection. This technology extends its privacy by asking for password, email or phone verification and much more to allow data transfer or access to another device.
Generally speaking, we all know what an encryption is and how it works and we are also aware that to secure data in a cloud it should be encrypted and needs to be decrypted to use it again using a public key. Would you believe if I told you there is no need of decrypting the data now to process it after it is encrypted? You would for a certain extend because that is what technology does, EVOLVE!
Homomorphic encryption (HE) is a new type of encryption which allows operations on data which is encrypted without decrypting while preserving the integrity and confidentiality. In simple words, allows third party access to encrypted data without knowing the contents of the decrypted data. Forensic applications, medical applications, smart vehicles etc use HE for secure data management.
Well, similar to above tech briefing, secure multi-party computation, differential privacy and much more privacy enhancing technologies, have their differences but all share one goal, that is to protect unauthorized access and operations on confidential information while having options to share. Thanks to cyber security offering organizations, the limits of data privacy continue to expand and anonymity of confidential data is increased.
REFERENCES
Decentriq. 2021. Privacy enhancing computation is one of Gartner's top tech trends in 2021. [online] Available at: <https://blog.decentriq.com/privacy-enhancing-computation.../> [Accessed 5 March 2021].
NEWS BBVA. 2021. What are PET technologies?: how to maximize data value while preserving privacy. [online] Available at: <https://www.bbva.com/.../what-are-pet-technologies-how.../> [Accessed 6 March 2021].
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