Privacy Enhancing Computation: Towards Secure Data Sharing

Organizations should ensure secure data sharing using Privacy Enhancing Computation Technologies.

Data is the new digital currency that empowers digital transformation. Businesses often share data through third parties thereby making Privacy Enhancing Computation (PEC) a necessary strategy in the process. All of us continuously share data online across different platforms, some of which offer encryption and data protection. But how secure is the data shared by business enterprises, considering the exposure and rising cybersecurity concerns?

The adoption of advanced data analytics has increased the flow and use of data across industries. Digital transformation has brought a digital shift but these digital platforms are also subject to a variety of cyber threats thus increasing data vulnerability.  To combat these cybersecurity challenges, data sharing protection should be on top priority in organizations. Gartner identifies Privacy Enhancing Computation as one of the top strategic technology trends in 2021 and says that it enables the organization to collaborate on research securely across regions and with competitors without compromising confidentiality.

PEC Adoption for the Best

Many industries capitalized on the boom of the data analytics industry to enhance business operations. Advanced data analysis methods are certainly shaping the industries by improving customer experience, scalability, risk management, predictive analytics, etc.

Privacy Enhancing Computation fends the security needs of big data analytics services by protecting data privacy and sensitivity while sharing data. PEC provides a collaboration of technologies that ensures data protection and privacy during data sharing by creating a trusted environment, enabling data encryption, multiparty computation, and more.

World Economic Forum elaborates these Privacy Enhancing Computation technologies by dividing them into five different technologies: Differential Privacy, Federated Analysis, Homomorphic Encryption, Zero-Knowledge Proof, and Secure Multiparty Computation.

• Differential Privacy allows data sharing without compromising the actual sensitive data and by restricting the access just to the insights and statistical outcomes and not exposing the actual data crux.

• Federated analysis holds and preserves the actual raw data in the system where it originated and allows sharing data outcomes that are generated from the raw data through third-party digital platforms.

• Homomorphic encryption as the name suggests encrypts the data before sharing it and enables computation without decrypting the shared data.

• Zero-Knowledge Proof is a cryptographic technology, which allows verification of data without actually revealing any data.

• Secure Multiparty Computation is also a cryptographic method that agrees with data sharing among multiple third parties wherein no single party can decode anything other than possible business outcomes.

Privacy Enhancing Computation technologies is an effective mechanism to cope with rising data breaches and security challenges. Adopting PEC can improve fraud detection capabilities and serve many diverse industries like finance and healthcare, where data is considered the most valuable asset and a slight breach can cost a lot.

Homomorphic Encryption: Gains and Banes

Among all the Privacy Enhancing technologies, homomorphic encryption stands out because of its popularity and unique strategy. Data encryption, while data is static, can be understood, but this technology takes a step forward by encrypting data while it is being shared. Homomorphic encryption is not new and its full potential was exhibited back in 2009 by Craig Gentry. He presented a homomorphic encryption scheme that enabled both addition and subtraction on the encrypted data.

Despite the benefits, homomorphic encryption has a slow adoption rate among industries due to many reasons. One of the important limitations is its high implementation costs and computational expenses. Another drawback is its encryption itself. Since this technology encrypts data into ciphertexts, it is not decryptable by anybody other than the provider. Even the person who encrypted the data at first needs to decrypt it, which takes a lot of time according to several reports.

Although, homomorphic encryption is hailed as one of the most beneficial methods of secure data sharing time will improve its capabilities and overcome its limitations in the near future.