Most have been in this situation before: one of the providers or services we use is a victim of a data breach and we want to determine if our personal user data has been impacted. This is where fully homomorphic encryption (FHE) comes into play. With FHE, the encrypted, personal password is compared against the data set of stolen user data and potential matches are identified without ever revealing the user’s password.

Use cases for this type of privacy-enhancing technology (PET) are numerous. They range from applications in medicine, where third-party service providers can analyze health data without compromising a patient’s privacy, to performing machine learning and AI algorithms on encrypted data, allowing organizations to derive insights from sensitive data sets without exposing the data to potential breaches or privacy violations.

How It Works

Fully homomorphic encryption allows calculations to be performed on encrypted data without having to decrypt it first. Confidentiality is maintained, as even the results are encrypted and can be viewed only with the appropriate decryption key. Further techniques for processing encrypted data are multi-party computation (MPC) and trusted execution environments (TEE).

Mathias Kohler, research manager at Â鶹ԭ´´ Security Research, outlines the differences: “While FHE is the most known of the encryption technologies, MPC is the ideal candidate if working with several parties exchanging encrypted data across company borders. And it can be substantially faster than FHE.” While both are software-based technologies, TEE is hardware-based, which makes it the fastest choice. The downside: TEEs, unlike MPC and FHE, require decrypting the data for processing. While decryption happens in a trusted hardware environment isolated from the operating system, it can allow data leakage via side-channel attacks. Notably, PETs do not need to be considered in isolation and can augment each other. For example, MPC can encrypt and distribute an FHE decryption key, protecting the FHE key and ensuring no single party can decrypt everything.

Why It’s Relevant

There is a demand for this kind of technology. By 2025, 60% of large organizations will use at least one privacy-enhancing computation technique in analytics, business intelligence, or cloud computing, according to .

Fully homomorphic encryption has numerous applications, especially in scenarios where privacy and security are paramount, such as secure computation in the cloud, privacy-preserving data analysis, and secure outsourcing of computations. As long as one party is performing the data processing centrally, FHE is the encryption method of choice. FHE enables organizations to share encrypted data with partners or third parties for analysis or monetization purposes while maintaining data confidentiality. This is particularly relevant in industries such as advertising and market research.

Interesting use case scenarios from Â鶹ԭ´´â€™s perspective could be secure benchmarking and predictive maintenance.

Secure Benchmarking

Companies often assess their competitiveness relative to industry peers and compare business-relevant KPIs, such as automation rate or return rates, with peers and even competitors. With fully homomorphic encryption, all participating parties can share encrypted KPIs without revealing individual data. As a result, they learn about relevant statistics, such as averages or medians, to assess their relative competitiveness and decide where to improve and invest.

Predictive Maintenance

Predictive maintenance is a machine learning technique to forecast demand for maintenance or spare parts based on historical data. “In certain industries, required data, such as usage patterns and failures, is considered sensitive and is not easily shared with data scientists or maintenance operators,” says Anselme Tueno, senior researcher at Â鶹ԭ´´ Security Research. By computing on encrypted data, however, no sensitive information is revealed while still allowing for the required insights to be gathered for prediction tasks.

Carbon Footprint Calculation with Multi-Party Computation

While it is early days from a product availability perspective, Â鶹ԭ´´ is working on potential use cases with customers and partners. One key example is calculating carbon footprints of products.

Prime examples for complex collaborations are today’s supply chains, intricate networks that encompass various levels of suppliers, manufacturers, and processed goods. Unfortunately, there is often a lack of comprehensive visibility across the entire process – either for technical reasons or because businesses are often reluctant to share sensitive data across supply chains that often include direct competitors.

However, to accurately assess and disclose a product’s carbon footprint, sensitive production details and associated carbon costs for production-relevant parts and materials are required. Here, MPC can reveal only the required carbon footprint without disclosing associated, proprietary manufacturing details with other supply chain participants.

Currently, Â鶹ԭ´´ is working with Bosch on cloud-native software for secure multi-party computation called .

“Â鶹ԭ´´ participates in this open-source project and supports the development of Carbyne Stack’s storage and processing services and the deployment of Carbyne Stack on Amazon Web Services (AWS),” Kohler explains. “For Bosch, Carbyne Stack is a type of cloud-native operating system for MPC workloads that manages resources to run as efficiently as possible in multi-cloud deployments.” This effort can help Â鶹ԭ´´ in the long run to integrate MPC as technology into Â鶹ԭ´´ solutions and services while running in a cloud-native environment.

What’s Next?

Despite all the benefits around processing data, encryption introduces significant computational overhead due to the complexity of performing operations on encrypted data. Slow processing speeds, especially for complex operations and large data sets, makes fully homomorphic encryption impractical for real-time applications or large-scale data processing. Although the performance of FHE has greatly improved in recent years, its practical adoption is still limited due to the processing overhead and performance considerations. Ongoing research is focused on the design of FHE-specific hardware accelerators.

“PETs for computing on encrypted data have the power to amplify data-driven business collaborations and reshape the future of cloud computing,” explains Jonas Böhler, senior researcher at Â鶹ԭ´´ Security Research. By safeguarding data, they enable access to previously untapped information while minimizing privacy risks and thwarting data breaches. The future of computing is encrypted.

This is why Â鶹ԭ´´ and Bosch have joined forces to harness the power of secure multi-party computation (MPC) and help enable secure and privacy-preserving data analysis across different organizations and industries.  

Bringing Secure Computation to the Industry Level 

MPC is an advanced cryptographic technique that can offer significant benefits to Â鶹ԭ´´ customers and partners that often deal with sensitive data from various sources and stakeholders. MPC allows multiple parties to jointly perform a computation without revealing any sensitive information that may be contained in their input data.  

That’s a great achievement because companies often fear that the risk of sharing their data openly is greater than the potential value of the sharing itself. One example is the supply chain, where multiple parties are involved. Object-level tracking allows companies to collect large amounts of data, such as time, location, or handling of the goods they produce. Combining the data collected by the different companies involved can have significant benefits. However, two companies may only be willing to share information about common items that they have both handled along the supply chain. MPC can help solve this dilemma with secure and private computation. 

As a result, organizations can perform complex data analysis and processing without compromising confidentiality or compliance. predicts that by 2025, 60% of large organizations will use at least one privacy-enhancing computation technique in analytics, business intelligence, or cloud computing.

“Companies can thrive the most when collaborating in business networks, and sharing data is a key component of these ecosystems. MPC can help protect sensitive data from unauthorized access and misuse while still enabling valuable insights and analytics,” says Volkmar Lotz, head of Â鶹ԭ´´ Security Research at . Powering secure benchmarking, fraud detection, supply chain optimization, or personalized services, MPC facilitates data sharing and collaboration across different organizations and sectors, creating new opportunities for innovation and growth. 

Lifting MPC into the Cloud 

In response to the demand for greater data privacy, Bosch Research has initiated the open-source project , which makes MPC available for a cloud environment. This way, confidentiality and privacy are maintained when data is processed by cloud services.   

“Carbyne Stack is a kind of cloud-native operating system for MPC workloads, managing resources to make them run as efficiently as possible in multi-cloud deployments,” explains Sven Trieflinger, senior project manager and group lead at Bosch Research. “From a business perspective, it’s the seed for an upcoming open ecosystem of technology building blocks that will accelerate the development and adoption of MPC technology across multiple industries.” 

Â鶹ԭ´´ has recently joined Carbyne Stack as a contributor. Building on both partners’ leadership in data security, cloud computing, and business applications, the collaboration will explore the potential of MPC for various use cases and industries currently constrained by security and privacy concerns. One of the first topics for Â鶹ԭ´´ will be to make the Carbyne Stack storage and processing services easily consumable from within the browser and to add support for deploying Carbyne Stack on Amazon Web Services (AWS). These changes will help Â鶹ԭ´´ work towards its vision of providing services for privacy-preserving data operations across different organizations and sectors, creating new opportunities for innovative business cases. 

“By combining the strengths of Â鶹ԭ´´ and Bosch, we aim to advance the state of the art in MPC and enable new business cases for our customers and partners,” says Lotz. 

Â鶹ԭ´´ targets use cases in industries such as automotive, manufacturing, healthcare, and finance. The exploration of MPC’s potential holds the opportunity to revolutionize those industries by solving critical data privacy and security challenges without compromising collaboration and innovation.  

To find out more about secure multi-party computation, get in touch with us at icn@sap.com.

Mathias Kohler is a research manager for Â鶹ԭ´´ Security Research.

Data privacy, risk management, and cybersecurity remain key priorities for businesses in 2023 to ensure continuous high performance and to catapult to new heights. In a recent , 43% of survey respondents said that they plan to upgrade IT and data security to reduce corporate risks. That includes security and data protection measures to keep their data safe. This becomes even more important when moving to and operating in a cloud enterprise resource planning (ERP) environment to drive continuous innovation. In the same CIO survey, 12% of the respondents said that they are planning to accelerate the move to the cloud as a service.

Adopt a Zero Trust Security Approach for the Cloud

To secure data and operations in a hybrid work environment, companies have been adopting a zero trust approach. defines zero trust as an “information security model that denies access to applications and data by default. Threat prevention is achieved by only granting access to networks and workloads utilizing policy, informed by continuous, contextual, risk-based verification across users and their associated devices.”

According to 2022 global survey data published by , 39% of companies have already begun to roll out a zero trust solution and 41% of companies have plans to adopt a zero trust strategy and are in the early phases of doing so.

My principle in life is to trust people and systems until I am provided a reason not to. The zero trust principle is the exact opposite of this.

The zero trust approach has three key principles: all entities and users are untrusted by default until authorized, the least privilege access is enforced, and extensive security monitoring is in place. In short, no connections to corporate networks and systems should be trusted at sight. All users, devices, and systems need to be authenticated, reverified, and continuously monitored when accessing networks, systems, and data.

Adopting this approach to cloud transformation has become the leading industry standard to keep operations and data safe across the entire virtual and physical network infrastructure.

Here are some best practices for putting an enterprise security plan in place that utilizes zero trust concepts to run operations safely and securely in the cloud.

Define Clear Security Roles and Responsibilities

First and foremost, ensuring security is always a shared responsibility between companies and their cloud transformation partners. It is a common goal and commitment that is independent of the type of cloud path companies take.

Like with any shared responsibility, the best way to approach it is by defining the roles and responsibilities up front. This process starts by asking these key questions: who is managing the cloud, how will everyone work together to secure the cloud, who is responsible for which part, and where are dependencies?

This will ensure that there is a clear strategy and plan to monitor and implement security policies and measures.

Keep an Eye on Users, Devices, Network, Applications, and Monitoring

Based on our experience at Â鶹ԭ´´ Enterprise Cloud Services, another best practice is to focus the zero trust security approach on five pillars: users, devices, networks, applications, and monitoring.

Eighty-seven percent of organizations consider the application layer as being the front door for data breaches. Most data breaches through cyberattacks happen because users fail to keep their credentials safe or fall prey to false identities. In addition, the number of remote users with their own devices has significantly increased in enterprise networks as well as the number of cloud-based assets that are not located within an enterprise-owned network boundary.

By regulating and monitoring user access to devices, networks, and applications, companies can protect all their resources, including assets, services, workflows, and network accounts. For example, identity management systems can manage privileged user authentication and access at a very granular level. This includes keeping administrative accounts separate from corporate accounts and applying encryption to several layers in the IT environment. Data classification makes it possible to associate the security levels with specific types of data, regardless of where that data resides – in the cloud, at endpoints, or in owned data centers.

Scaling Security Needs Faster with the Cloud

While managing the complexity of security needs for cloud transformations can be daunting, here is an added merit: companies can scale their security needs much faster in the cloud, according to research. Benefits include better automation capabilities as well as higher storage and data capacity in the cloud. Companies can push infrastructure as code and fix a security problem in real time when operating in the cloud. Automation also helps in increasing the maturity of identity management and security management systems. recommends embracing cybersecurity as a differentiator to promote greater stakeholder trust and better use of cloud-native solutions that take advantage of the cloud’s full potential.

In other words, you can shine like a diamond on your cloud platform of choice with a zero trust security approach for the cloud.

For more information, visit the site and read this chief security officer for Â鶹ԭ´´ Enterprise Cloud Services.

Peter Pluim is president of Â鶹ԭ´´ Enterprise Cloud Services and Â鶹ԭ´´ Sovereign Cloud Services.