Today, we’re proud to announce our partnership with Partisia, a team of the world’s leading technologists in cryptography and Secure Multi-Party Computation. While a few of the guys at Partisia are listed in the Advisor’s section of our website, they are actually functioning as close teammates with the Insights Team. Providing more than just advisory, the Partisia team is contributing to our SMC design and will be hands on in the actual development of the SMC portion of the Insights Network Protocol and blockchain infrastructure! Before we discuss what SMC is — meet the team!
Partisia team and experiences
Partisia is the pioneer and world leading provider of SMC solutions. Partisia designs, develops and operates SMC solutions for mechanism design like auctions, privacy-preserving statistics as well as critical infrastructure like encryption key management. Some activities have been conducted in spinouts from Partisia like Sepior.
World-Renowned Crypto Experts
● Ivan Damgård is one of the founding fathers of SMC as well as the modern hash function. He is one of the top cited and most published researchers in cryptography, fellow of the IACR and received the 2015 RSA Award for Excellence in the Field of Mathematics. Co-founder of Cryptomatic, one of the first commercial firms in cryptography, as well as Partisia and Sepior.
● Jesper Buus Nielsen is one of the top cited and most published researchers in secure multiparty computation. Jesper’s primary research areas are implementing secure multiparty computation in practice. Co-founder of Partisia and Sepior.
SMC Implementation Team:
● Peter Frands Frandsen is heading the SMC implementation in Partisia. Peter has 20 years of experience in building commercially graded software and prior to Partisia, he worked as a manager at Ramboll Management Consulting. Peter Frandsen has extensive experience with complex IT solutions including several SMC solutions.
● Partisia has a handful of highly specialised SMC developers and through the ownership, Partisia collaborates with the Alexandra Institute e.g. through the open source project Fresco — which Partisia are the main contributors to.
Partisia Management:
● Kurt Nielsen is CEO and co-founded Partisia, Energiauktion.dk and Sepior.com. He holds a PhD in Business Economics and did combined graduate studies at the University of Copenhagen, University of Toronto and UC Berkeley. Since 2004 he has co-initiated numerous projects combining computer science, economics and businesses.
● Jakob Illeborg Pagter is CTO and co-founded Partisia, Energiauktion.dk and Sepior.com. He holds a PhD in computer science from Aarhus University and is a member of the Danish Council for IT Security as well as the committee for IT security at the Confederation of Danish Industry. Jakob functions as CTO of Sepior.com.
What is SMC?
Secure Multiparty Computation (SMC) is a technology that allows you to compute on encrypted numbers. This might sound impossible at first — but in fact, by using the right kind of cryptography, it is not. SMC belongs to this new generation of cryptographic solutions and allows a number of parties to jointly perform computation on private inputs, without releasing information other than that which has been agreed upon a priori. The seminal aspects of this concept can be traced back to (Shamir 1979), with the theory being founded in the 1980s, see (Chaum 1988). Although, MPC was shown, in theory, to be generally applicable in the mid-1980s, the computational complexity of MPC prevented its practical use for two decades. The first large scale and commercial use of MPC was done by the Partisia team in 2008 in Denmark, when MPC replaced a traditional auctioneer on a double auction used for the reallocation of production contracts (Bogetoft et.al 2009).
Since 2008, the technology has matured both in terms of computational speed, and the properties of the MPC protocols. The computational overhead has been reduced exponentially to 1/1,000,000 of that in 2008 (Nielsen et al 2017). Partisia has been the pioneer within commercial use of SMC, starting with the aforementioned contract exchange and energy procurement auctions (in a separate Danish spinoff Energiauktion.dk); MPC-based key management (in a separate spinoff Sepior) and recently, off-exchange matching on financial markets for securities and a number of pilot applications within privacy-preserving statistics (in a separate spinoff Secata).
What does SMC solve in Insights Network ?
SMC ensures that confidential information stays confidential — even on the blockchain. This is unlike the traditional approach, where standard encrypted information is added to the blockchain. The encrypted information is there for all to see and at some future point the encryption can be broken by brute force. The SMC solution for Insights Network is based on so-called secret sharing, which is informational secure, which means that it can not be broken by brute force.
SMC and blockchain belongs to the same class of modern cryptography that does not rely on single points of trust (sometimes referred to as “trustless”). While the two technologies both offer the same type of integrity, SMC ensures that information stays confidential while blockchain ensures full transparency about the contractual agreements. Together these two powerful technologies make up the ideal infrastructure for Insights Network.
To date, no one has succeeded in truly combining the two complementary technologies. SMC is not a single protocol but rather a growing class of solutions that differs with respect to properties and performance. The key to success in combining SMC with blockchain is the ability to design the right protocols. Partisia is highly specialized in building SMC protocols that meet the requirements for the specific application. Examples are tailored protocols applied for key management in Sepior and tailored protocols for off-exchange matching on financial markets for a Company called Tora. The SMC protocol for Insights Network is designed to meet the type of network involved in Insights Network’s P2P solution and the nature of blockchains.
Insights Network Use Cases
A number of companies rely on profiling individuals and companies not least banks and insurance companies. For a lending institution, risk assessment is an essential component both before and after a loan, or other financial product, has been issued. The fundamental problem is the lack of information about the likelihood of an individual’s or a company’s ability to fulfill its financial obligations. In economics, the two basic problems with this informational asymmetry between the lender and the borrower, are known as adverse selection and moral hazard. Adverse selection deals with the difficulties in distinguishing between low and high risk types before a loan is issued and moral hazard deals with the difficulties in distinguishing between low and high risk borrowers after a loan has been issued. In both cases, the core of the problem is lack of information.
The solution is to find or create trustworthy indicators, e.g. credit scores to be used before a loan is issued, and during the lifetime of a loan. Insurance companies have a similar challenge in distinguishing between high and low risk types. However, none of this works properly without high quality and sensitive data about individuals and companies, i.e. sensitive data from a
significant number of representative individuals and/or companies.
Insights provides the infrastructure that empowers the individual person and/or company to collaborate with e.g. banks and insurance companies to address this problem on equal terms. Combined with the built-in survey system, Insights Network will become a unique source of information for profiling individuals and companies, while protecting the consumer’s privacy and sensitive personal information.
Telegram
Make sure to join our community on Telegram to chat with the Insights and Partisia team and learn more about the project!
References
Bogetoft P, Christensen DL, Damgaard IB, Geisler M, Jakobsen T, Kroejgaard M, Nielsen JD, Nielsen, JB, Nielsen K, Pagter J, Schwartzbach MI and Toft T (2009) Secure multipartycomputation goes live, Lecture Notes in Computer Science, vol 5628, pp. 325–343.
Chaum D, Crepeau C, and Damgaard IB. (1988) Multiparty unconditionally secure protocols (extended abstract). In 20th ACM STOC, Chicago, Illinois, USA,May 24, 1988, ACM Press,pp. 11–19.
Nielsen BN, Schneider T and Trifiletti R (2017) Constant Round Maliciously Secure 2PC withFunction-independent Preprocessing using LEGO. NDSS 2017.
Shamir A (1979) How to share a secret, in Communications of the ACM 22, 11, pp. 612–613.