The world is slowly making the transition into becoming a completely data-dependent landscape where every individual, agency, and business depends on data for all decisions. Data is presently one of the valuable assets for an enterprise, and companies must ensure the safety of their data. One of the important reasons for focusing on privacy enhancing technologies in 2021 largely relates to the increasing priority for data privacy and security.
Consumers are increasingly developing awareness of their personal data and the individuals responsible for managing them. According to a survey conducted recently by the Pew Research Center, almost 79% of adults expressed concerns regarding the ways in which companies use the personal data related to them. In addition, around 52% of adults stated that they would not use a product or service due to concerns regarding the collection and use of their personal information.
The continuously increasing usage patterns of privacy-enhancing technologies in recent times are a clear indicator of their popularity. As the world shifts to the digital front in almost everything, it is inevitable to wonder about privacy enhancing technologies. Will they successfully safeguard the privacy of users at all costs? What are the types of risks privacy enhancing technologies or PETs can handle? The following discussion helps you discover some of the critical basic information regarding privacy enhancing technologies or PETs.
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What’s behind Privacy Enhancing Technologies?
Enterprises are troubled by various concerns in data safety and privacy. Now, businesses have to safeguard the direct interactions with customers and the ones in B2B environments. As a result, enterprises have successfully returned back to the concept of privacy enhancing technologies or PETs.
Interestingly, privacy enhancing technologies have been around for quite a long time, although with profound recognition in recent times. PETs are a dominant category of technologies capable of enabling, enhancing, and preserving data privacy concerns throughout the data lifecycle. The proceedings on privacy enhancing technologies largely depended on the use of a data-centric approach for security and privacy.
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Reasons for Introducing Privacy Enhancing Technologies
Before defining privacy enhancing technologies or PETs in detail, it is important to understand the concerns which encourage them. Here are some of the notable factors responsible for driving extended usage patterns of privacy-enhancing technologies.
- Continuous development of functionalities in technologies that enable people to connect and communicate with each other
- Increased interest of enterprises in collecting the information generated by and about other users
- Government surveillance over personal communication and other online activities of individual users
- Major data breaches at top government agencies and private enterprises, and corporations leading to loss of multiple records of personal information
All of these reasons clearly showcase the necessity for bringing in privacy enhancing technologies in 2021. The major issue in the absence of PETs largely points out possibilities or the real threats of identity disclosure. Malicious agents could associate data traffic with identity or use a data content transfer for determining the location. However, privacy enhancing technologies help in resolving such risks with ease.
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Definition of Privacy Enhancing Technologies
When we try to find the definition of privacy enhancing technologies (PETs), there are many implications associated with them. First of all, PETs are not any new technological trend. They have been around in the academic realm for almost 30 years and now finding applications in various real-world use cases. Gartner has classified PETs as one of the top strategic technology trends for 2021 for the right reasons. In order to understand privacy enhancing technologies examples technologies, you must get an overview of the technical definition of PETs.
Privacy enhancing technologies actually refers to an umbrella term that describes the technologies responsible for the security of data while in use. In addition, PETs are also significantly crucial for safeguarding and improving data privacy and security during the execution of searches or analytics. The different types of privacy enhancing technologies are tailored for individual use cases, and some of them have common points too.
In the case of privacy enhancing technologies examples technologies, you could find some nuanced differences according to use cases and applications. On the contrary, better security with a concerned technology is responsible for dictating the extent of privacy safeguarding and privacy enhancing capabilities it can offer.
Working of Privacy Enhancing Technologies
However, the general definition of privacy enhancing technologies skips the element of ‘people centricity. Gartner has presented an interesting yet comprehensive definition of privacy enhancing technologies by breaking down the work of PETs. The definition of privacy enhancing computation outlined by Gartner can help in understanding how PETs work. As a matter of fact, the three important processes in PETs for protecting data while in use provide exceptional privacy enhancing technologies benefits.
- First of all, PETs rely on a trusted environment where you could carry out analysis and processing of sensitive data.
- The second important process in PETs refers to the execution of processing and analytics tasks in a decentralized fashion.
- Another crucial task in PETs refers to the encryption of data and algorithms prior to the analytics or processing tasks.
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Why Focus on PETs Now?
Privacy enhancing technologies have been around, and many other data privacy solutions have come up in recent times. However, PETs have a unique significance for data privacy in present times. Here are the critical reasons for which PETs are important for businesses.
- Data protection laws like CCPA and GDPR are evolving with the addition of new precedents for organizations to safeguard consumer data. Businesses are likely to incur fines due to non-compliance or on account of data breaches. According to the DLA Piper GDPR Data Breach Survey 2020, GDPR fines in the time from May 2018 to January 2020 amounted to a total of $126 million.
- The second reason for increasing usage patterns of privacy-enhancing technologies refers to the need for third-party organizations to test data. Such scenarios may emerge due to the lack of adequate resources for analytics and application testing. With the help of PETs, enterprises could achieve efficient privacy protection while offering data-sharing functionalities.
- Another prominent reason for the emphasis on privacy enhancing technologies in 2021 refers to the impact of privacy breaches on reputation. At the same time, privacy breaches could also affect the business operations and customers of an enterprise. So, you can face the risks of losing valuable customers as they wouldn’t want to interact with brands that cannot assure privacy.
Renowned Use Cases of PETs
The next important aspect in understanding privacy enhancing technologies or PETs refers to their applications. Here are some of the top use cases of PETs to showcase the value of privacy enhancing technologies’ benefits.
- Financial transactions are the foremost targets for PETs. Financial institutions have the responsibility of safeguarding the private information of their customers. It will provide assurance to customers regarding their freedom to carry out private transactions and deals with other parties.
- PETs are also useful in test data management use cases. In some cases, third-party providers take over the application testing and data analysis tasks. Even with in-house management of application testing and data analysis, companies have to reduce internal access to customer data. Therefore, the use of an ideal PET alternative without affecting test results significantly can help organizations in such cases.
- Businesses are working as intermediaries between two parties also need the value advantages of PETs. The use of privacy enhancing technologies is important for such businesses as they have to protect privacy of information from both parties.
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Examples of Privacy Enhancing Technologies
The proceedings on privacy enhancing technologies in this discussion should also focus on some notable examples of PETs. As a matter of fact, you can find various technologies in the scope of PETs in the present times. Here are some of the notable entries among PETs that are commonly used today.
Homomorphic encryption is one of the most secure PETs that allow performing operations on encrypted data. The operations on encrypted data would deliver results just like in the way if they were performed on unencrypted data. So, enterprises could use homomorphic encryption for analysis use cases without compromising the anonymity and privacy of data. However, the practical applications of homomorphic encryption are restricted in terms of data volumes. You can use homomorphic encryption privacy enhancing technologies in 2021 only for limited volumes of data.
Zero Knowledge Proofs
Zero Knowledge Proofs or ZKPs have emerged as a prolific answer for data privacy woes affecting modern enterprises. ZKPs ensure that you can prove to someone that you are having knowledge of a certain fact without revealing the fact. It would be like proving your eligibility to vote in elections without having to show your date of birth.
ZKPs are basically a series of cryptographic algorithms which have set new benchmarks for maintaining privacy in a data-centric world. The applications of ZKPs have created promising value-based opportunities for use cases in the banking and finance domains. In such use cases, ZKPs could ensure the accessibility of products and services which need private customer information without exposing data.
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Secure Multi-Party Computation
Another top example in the proceedings on privacy enhancing technologies in 2021 refers to secure multi-party computation. Secure multi-party computation cryptographic technology is basically a sub-category of homomorphic encryption. It enables complex computation and analytical operations on larger amounts of encrypted data.
Subsequently, secure multi-party computation also enables the application of machine learning models to encrypted data. Interestingly, big names in the world of techs such as Facebook and Google have already taken huge strides in the implementation of secure multi-party computation.
For example, you can find secure multi-party computation privacy enhancing technology in products such as the machine learning tool, Tensor Flow. The machine learning tool helps in training models by leveraging encrypted third-party data. In this case, enterprises share encrypted data with a third-party responsible for its analysis and returning back the analysis results. The third party must not compromise the privacy of the data’s content.
Another interesting entry among privacy enhancing technologies examples technologies is differential privacy. It is a comprehensive cryptographic system with the capabilities for adding a ‘random noise’ layer to a data set. The ‘random noise’ ensures the lack of any possibilities for extracting specific information regarding every individual trace of information.
So, differential privacy enables sharing of results obtained through the implementation of an automated learning model to data sets with third parties. Differential privacy is a great alternative for organizations to encourage data sharing to foster collaborative learning models.
The Relation of PETs with Customer Centricity
Customer-centricity is one of the underlying forces in the working of usage patterns of privacy-enhancing technologies. Many new forces, such as technological and ideological advancements, have resulted in a completely new collection of data collaboration initiatives. The collaboration initiatives span through different sectors responsible for increasing the value of data for internal teams and external partners.
Many enterprises have been claiming their focus on customer centricity in the delivery of data privacy solutions. However, the pandemic era has completely changed the perceptions of customer-centricity. Now, the focus on digital-first and privacy-first implications has escalated profoundly.
So, many companies would have to adapt to these new changes to make it to the top. PETs offer the ideal ways for narrowing the gap between understanding and implementation of data privacy safeguards. In addition, PETs can build on customer centricity by developing a true single view of the customer. As a result, enterprises can work on delivering next-generation personalized experiences for customers in data privacy and security with PETs.
Risks of Privacy Enhancing Technologies
Even if the demand for privacy enhancing technologies in 2021 is increasing substantially, they have many profound pitfalls. A closer look at the various risks associated with privacy enhancing technologies could help in understanding them better.
- The first and foremost setback observed in PETs refers to the complexity and difficulty in using them. As a result, they can be responsible for user errors that can compromise the privacy and security of user data.
- PETs also have the prominent setback of high cost. In addition, you would need massive computational capacity for using PETs. The majority of market participants could not access the high-level computational resources. At the same time, it is also important to note that using high-end computing resources will also have profound negative impacts on the environment.
- The complexity alongside resource restrictions can also restrict the proceedings on privacy enhancing technologies. Legal authorities and policymakers would have a tough time in establishing proper auditing or governance precedents for PETs.
- The challenges of accessibility and usability with PETs can also lead to concerns of accountability. Therefore, using PETs will basically imply the development of a false sense of security or safety. As a matter of fact, the false sense of security or safety does not emerge naturally from practice. The false assurances can imply that using PETs could ensure rewards for additional data collection and sharing. Subsequently, you can end up playing down the value of core data protection principles such as data minimization.
- The lack of common definition and standards for PETs could also create many difficulties in evaluating the efficiency of PET. For example, differential privacy emerged in early 2000s as a tool for using big data while avoiding possibilities of data disclosure. Differential privacy offers data privacy while ensuring the accessibility of datasets for research and data analysis, albeit with certain trade-offs. The trade-offs include security, accuracy, comprehensibility, resilience, and fairness.
- Privacy enhancing technologies would also have to face the concerns of legitimizing activities that are perceived as concerning or objectionable. For example, the latest PETs are generally available to entities with considerable control over the digital environment with massive data resources. So, PETs are basically opening up the way for privacy to large technology companies such as Google and Apple.
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On a final note, it is clearly evident that privacy enhancing technologies in 2021 will surely make an impact. The world is shifting to the digital at an unprecedented pace following the pandemic era. As a matter of fact, the rejuvenation of the global economy during and in the aftermath of a pandemic has been largely responsible due to the digital environment.
People could buy products and services through digital platforms and work and engage with peers through digital instruments. While doing so, people will put their personal information at risk of exposure. So, corporations that use the personal information of customers have a lot to think about customer data privacy and security in 2021.
The privacy enhancing technologies benefits have brought the assurance of creating collaborative environments for data sharing. At the same time, PETs have also improved the assurance of limited interventions of third parties with user data. However, PETs also have to bear the burden of certain setbacks which affect their functionality.
In the long run, privacy would turn into a staple element of computing networks and applications which harbor personal data. Privacy is an essential requirement of users and enterprises to avoid various threats and negative consequences for operations, people, and reputation. Learn more about PETs and what they mean for the future of data privacy and security right now!
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Author: Gwyneth Iredale