Chicago, June 27, 2024 (GLOBE NEWSWIRE) -- The global Secure Multiparty Computation (SMPC) Market size is projected to grow from USD 824 million in 2024 to USD 1,412 million by 2029 at a Compound Annual Growth Rate (CAGR) of 11.4% during the forecast period.
As data breaches and privacy issues become more prevalent, organizations are seeking secure ways to process and share sensitive information. SMPC offers a solution by allowing data to be computed jointly without exposing it to all parties involved. As organizations prioritize secure computation, the demand for SMPC solutions continues, fostering market expansion.
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Secure Multiparty Computation Market Dynamics:
Drivers:
- Demand for private key security with SMPC
- Data privacy regulations compliance
Restraints:
- Increased computational time
- High communication costs involved in key decentralization (or distribution)
Opportunities:
- Adoption of AI and ML
- Integration with cloud computing platforms
List of Key Players in Secure Multiparty Computation Market:
- Microsoft (US)
- IBM (US)
- Google (US)
- Fireblocks (US)
- Blockdaemon (US)
- Qredo (British Virgin Islands)
- Penta Security (South Korea)
- Zengo (Israel)
- Inpher (US)
- CYBAVO (Singapore)
- Liminal Custody (Singapore)
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Trend: Cloud Computing
Cloud platforms provide computational power and storage capabilities vital for processing and analyzing data while ensuring security and privacy through encryption and access control mechanisms. Cloud computing enables organizations to execute complex computations on encrypted data without compromising confidentiality, thereby facilitating secure collaboration and data analysis across distributed environments. This integration enhances scalability, reliability, and performance, allowing organizations to access computing resources on-demand and scale operations efficiently.
Trend: Homomorphic Encryption (HE)
Homomorphic encryption (HE) is a critical component used in Secure Multiparty Computation (SMPC) to enhance data privacy and security during collaborative computations. Security Homomorphic Encryption acts as the foundation for SMC enabling computations on encrypted data without decryption and safeguarding sensitive information during collaborations. HE allows multiple parties with encrypted datasets to perform joint analysis without revealing their underlying data. MPC protocols leverage HE properties like addition and multiplication. The extension enables functions to be evaluated on encrypted data without decryption, enhancing privacy in scenarios like cloud computation.
By offering, the solution segment accounts for a larger market share.
Secure Multiparty Computation (SMPC) solutions are designed to enable multiple parties to collaboratively perform computations on their data while ensuring that their individual inputs remain private. These solutions are particularly beneficial in key management and computation contexts. By distributing the cryptographic keys among the parties involved, SMPC eliminates single points of failure, thereby enhancing security. Each party holds a share of the key, and computations can be performed without ever reconstructing the entire key, reducing the risk of exposure. Additionally, SMPC ensures that computations are executed securely, with each party contributing their input in an encrypted form. This approach not only protects the data during processing but also maintains the confidentiality and integrity of the results. Overall, SMPC solutions provide a robust framework for secure and private computations, making them invaluable for scenarios that require high levels of data security and privacy.
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By deployment mode, the cloud segment accounts for the highest CAGR during the forecast period.
Leveraging the cloud for SMPC offers a compelling solution for data analysis in today's privacy-conscious world. Cloud platforms provide the horsepower to perform complex computations on encrypted data, addressing concerns about sharing sensitive information. With SMPC in the cloud, multiple parties can collaborate on tasks involving confidential data without any party ever seeing the raw information of others. This enables valuable data insights to be extracted from combined datasets across different organizations, such as healthcare institutions analyzing disease patterns or financial institutions jointly detecting fraud. Cloud-based SMPC fosters secure collaboration while adhering to data privacy regulations and keeping sensitive information within each party's control..
Opportunity: Adoption of advanced technologies like AI/ML
The growing adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies presents a lucrative opportunity for the Secure Multiparty Computation (SMPC) market. SMPC's capacity to conduct computations on encrypted data ensures that sensitive information remains safeguarded throughout the collaborative learning process. As AI and ML technologies continue to permeate various sectors, the need for privacy-preserving solutions like SMPC is set to rise, fueling growth and innovation within the SMPC market. A paper published in the 35th Conference on Neural Information Processing Systems (NeurIPS) in 2021, by Brian Knott, Shobha Venkatraman and others, describes a software framework CRYPTEN that integrates SMPC into familiar abstractions commonly used in modern machine learning frameworks.
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