Arcium: Secure Data Collaboration for a New Era

Revolutionizing Data Privacy and Confidentiality with Cutting-Edge Technologies

Table of Contents:
1) Secure Multi-party Computation (SMPC)
2) SHE VS FHE
3) Cheating Identification Protocol
4) Confidential Inference
5) Arcium Architecture
6) Multi-Party Execution Environments (MXEs)
7) Why Solana?
8) Arcium: Making Data Work for You, Privately (Real-world Use Cases)
9) My Humble Opinion (Serves as a Conclusion)

Today, organizations struggle to securely share and process confidential/sensitive data. This problem is especially critical in (i) Healthcare, (ii) Supply chains, (iii) AI, (iv) Finance, and (v) Crypto, where data breaches can have severe consequences.

To wit:

• In 2017, the ransomware attack “NotPetya” crippled global shipping giant Maersk. It encrypted critical data and shut down operations, costing the company an estimated $300 million in lost revenue and recovery costs.
• The “Facebook-Cambridge Analytica” scandal severely damaged Facebook’s (now Meta) reputation.
• The “Anthem health insurance” data breach in 2015.
• ‘Mt. Gox’, one of the earliest and most infamous crypto breaches, Mt. Gox, once the largest Bitcoin exchange, lost around 850,000 Bitcoins (worth billions today) to hackers.

These are just some examples of the severe consequences that can result from a data breach.

Organizations need to collaborate on sensitive data for research, analysis, and innovation, but they also must ensure data privacy and security. Traditional methods of sharing data pose risks of breaches and unauthorized access.

How can organizations safely share and work on sensitive data without compromising privacy or efficiency?

Introducing Arcium: Revolutionizing Secure Data Collaboration

Arcium is a parallelized confidential computing network. Pioneering for secure data collaboration, the Arcium Network is particularly beneficial to industries reliant on sensitive or valuable data like blockchain, healthcare, and artificial intelligence (AI). The Arcium Network leverages a distributed architecture, consisting of multiple nodes capable of executing Multi-Party Computation (MPC) tasks.[1]

To give you a quick background, Arcium was created by the team behind Elusiv (which has been building for Solana for 2 & half years now), an application-layer zero-knowledge (ZK) privacy protocol based on Solana that sunsetted in March 2024.

Moreover, Arcium /ˈɑːrkyum/ is a genitive plural of arx — a Latin word meaning “fortress”, “citadel” or “stronghold”. This etymology underscores the network’s foundational principle of “security and protection”.

Arcium tackles the challenge of secure data collaboration by leveraging cutting-edge confidential computing concepts:

1. Secured Multi-Party Computation (SMPC). Enables multiple parties to jointly compute functions over their inputs while keeping them private.
2. Somewhat Homomorphic Encryption (SHE). Allows basic computations on encrypted data without decrypting it.[4]
3. Cheating Identification Protocol. Detects and excludes malicious nodes to maintain computation integrity.[4]
4. Confidential Inference. Performs machine learning predictions on encrypted data.[4]
5. Blockchain Integration (Solana). Ensures transparent, verifiable, and tamper-proof transactions and computations.[4]

These are some key concepts that ensure the Arcium network to secure private data, and be reliable for industries handling sensitive data.

I'll try to unpack them for you.

1) Secure Multi-party Computation (SMPC)

Secure multi-party computation (SMPC) a.k.a (Multi-party Computation or MPC) allows a set of parties to collaboratively execute a distributed computation using a cryptographic protocol, with the same security and privacy guarantees that would result from relying on a Trusted Third Party (TTP) to compute the same functionality in an ideally secure setting.[2]

How does it work?

Calculating a Company’s Total Revenue:

Imagine four departments in a company (P1, P2, P3, P4) each have their own sales figures (x1, x2, x3, x4). They want to calculate the total revenue of the company without revealing each department’s individual sales figures to each other or to a central authority.

MPC allows multiple parties to collaboratively compute a function while preserving the privacy of their individual inputs, which has applications in secure data analysis, privacy-preserving machine learning, and other scenarios where data privacy is crucial.

This method ensures that the computation is done collaboratively without compromising the privacy of individual inputs.

• Each department (P1-P4) represents a party in the MPC protocol.
• Their sales figures (x1-x4) are their private inputs.
• The function f(x1, x2, x3, x4) is the calculation to sum up the sales figures to get the total revenue.

Using MPC, each department can contribute their sales figures in a way that only the final result, the total revenue, is revealed. No individual department learns the sales figures of the other departments.

How does it impact Finance?

MPC has significant applications in finance, particularly in areas where privacy and security are paramount:

1. Privacy-Preserving Data Sharing. Financial institutions can collaborate on risk assessments, fraud detection, or credit scoring without sharing sensitive customer data.
2. Secure Auctions. MPC can be used to conduct auctions where bids remain confidential until the auction is complete, ensuring fairness and preventing collusion.
3. Distributed Key Generation. In crypto wallets, MPC can be used to generate and manage private keys in a distributed manner, enhancing security by eliminating a single point of failure.
4. Privacy-Preserving Financial Derivatives. MPC can enable the creation of complex financial instruments where the underlying assets and trading strategies remain confidential.

Overall, by utilizing MPC, Arcium empowers these sectors to conduct secure data analysis, preserve data privacy in DeFi/TradFi transactions, and engage in collaborative computations without compromising the confidentiality of individual inputs. This groundbreaking approach mitigates the risks of data breaches while unlocking the full potential of data-driven insights.

2) SHE VS FHE

FHE (Fully-Homomorphic Encryption) theoretically allows for any computation on encrypted data, but it is currently very computationally expensive and impractical for most real-world applications due to performance bottlenecks.

On the other hand, SHE (Semi-Homomorphic Encryption or Somewhat Homomorphic Encryption) Supports a limited number of operations (like addition or multiplication) on encrypted data. While less flexible than FHE, SHE is significantly more efficient and practical for many use cases.

Practical reasons:

• Performance. For high-throughput applications like DeFi (Decentralized Finance), performance is crucial. SHE’s efficiency makes it more suitable than FHE for such scenarios.
• Cheater Detection. In multi-party environments, it’s important to ensure that participants adhere to the protocol. SHE can facilitate efficient cheater detection mechanisms, ensuring the integrity of computations.
• Optimization for Specific Needs. By focusing on the specific operations required, SHE can be optimized for maximum efficiency, striking a balance between security and performance.
• Verification Mechanisms. SHE enables simpler and more efficient verification of computations, which is essential for ensuring correctness without compromising data privacy.

SHE Allows computation of circuits of low-depth Batching — enables scaling to nontrivial datasets Can perform statistical analysis on encrypted data with “reasonable” overhead. [17]

To learn more about the technical details [13]👈.

How does it work?

Imagine an election where you want your “vote” to remain secret, but the votes still need to be tallied.

Simplified SHE diagram

SHE is like a special ballot box system:

1. Plaintext Data (Your Vote). Your voting preference (e.g., candidate A) is like the plaintext data — the raw, unencrypted information.
2. Encryption (Sealing the Ballot). You place your vote into a special ballot envelope that locks once sealed. This is like encrypting your vote with a public key — anyone can put a vote in, but only someone with the right key can open it.
3. Encrypted Data (Sealed Ballots). The locked ballot envelopes are like the encrypted data (ciphertext). The contents are hidden, but they still exist inside.
4. Computation (Counting). Election officials can open the outer layer of the envelopes, revealing a second, inner envelope. This allows them to sort the votes by candidate without seeing the individual votes inside. This is like performing a limited computation (e.g., counting) on encrypted data.
5. Computation Result (Sorted Ballots). The sorted piles of inner envelopes represent the computation result — it’s still encrypted (you can’t see the votes), but it provides meaningful information (which candidate has more votes).
6. Decryption (Counting the Votes). Only after the sorting is done, election officials with the private key (special tool) can open the inner envelopes and count the individual votes. This is like decrypting the final result to get the plaintext outcome.
7. Plaintext Result (Election Outcome). Finally, the total vote count for each candidate is announced — this is the plaintext result, the outcome of the election.

3) Cheating Identification Protocol (CIP)

Cheating Identification Protocol a.k.a “Cheater identification” or “Cheater Detection” in secure MPC allows the honest parties to agree upon the identity of a cheating party, in case the protocol aborts. In the context of a dishonest majority, this becomes especially critical, as it serves to thwart DOS (denial-of-service) attacks and mitigate known impossibility results in ensuring fairness and guaranteed output delivery.[14]

Moreover, CIP is a mechanism used within BFT (Byzantine Fault Tolerance) systems to identify and isolate nodes that are acting maliciously or dishonestly.

BFT simplified. This multi-step process helps ensure that all honest nodes can agree on the state of the system, even if some nodes are behaving maliciously or have failed.

High-Level Overview:

CIP is an essential component of BFT protocols. BFT systems are designed to function correctly even in the presence of Byzantine faults, which include arbitrary and potentially malicious behavior.

Further, BFT protocols assume that a certain fraction of nodes (typically up to 1/3) may be faulty or malicious. Identifying these “cheaters” is crucial for the system to maintain correct operation.

BFT protocols operate in environments where not all participants can be trusted. CIP helps manage and validate these trust assumptions. By detecting and mitigating the impact of cheaters, BFT protocols ensure the integrity and reliability of the overall system.

4) Confidential Inference

Confidential inference (or Confidential ML Inference) involves performing machine learning predictions on encrypted data. Arcium leverages confidential inference techniques to enable AI models to operate on sensitive data without exposing the data itself. This is particularly beneficial for industries like “healthcare”, where patient data privacy is paramount.

To enable this, Trusted Execution Environments (TEEs) like Intel SGX or Apple’s PCC “Secure Enclave” act as secure “black boxes” within an Arx node’s processor. This isolation ensures that sensitive data and the code performing the analysis are protected from unauthorized access, even by the operating system or cloud provider.

The Core Idea

Performing computations (like machine learning predictions) on sensitive data while keeping the data itself hidden, even from the system running the computation.

Simplified Confidential ML Inference workflow for one data owner and one model owner.

Basically,

• The model owner (Alice) has a trained machine learning model (eg. encrypted TensorFlow model).
• The data owner (Bob) has input data (encrypted input data) that needs to be processed by the model.
• Both the model and the input data are sent to a confidential ML inference platform.
• The platform performs the inference process (making predictions) on the encrypted data using the encrypted model.
• The result is also encrypted and sent back to the data owner.

The key point is that neither the model owner nor the platform sees the input data, and neither the data owner nor the platform sees the model. This ensures the confidentiality of both the model and the data during the inference process.

5) Arcium Architecture

The Arcium Network utilizes an on-chain orchestration mechanism running on the Solana blockchain, which facilitates all network management tasks, including computation scheduling, compensation for computational work, and punishment enforcement to maintain network integrity.[1]

i) Solana Blockchain (& other chains in the future):

Arcium network has Dedicated “Programs” a.k.a “Smart contracts” on Solana that facilitates:

• On-chain Orchestration
• Mempool for Pending Computations
• Compensation and Incentive Management

ii) Arcium Network:

• Clusters. Collections of Arx (MPC) nodes (the “hardware”)
• MXEs (MPC Execution Environments). Dedicated environments for computations (the “state”)
• Computation Definitions. Functions for executing tasks
• Scheduled Computations. Individual instances of function calls

iii) Arcium Network Stakeholders[11]

• Computation Customers. Buy confidential computing services, define computations, and pay fees based on complexity and priority.
• Arx Operators. Run software (Arx MPC node software) on their hardware to execute computations, stake collateral, and earn rewards based on performance and reputation. Liable to “slashing” for misbehavior.
• 3rd-Party Delegators. Delegate stake to Arx nodes to earn rewards, pay fees for infrastructure, and share risks and rewards.

iv) Key Relationships and Flow:

• Solana ↔ Arcium. The Solana blockchain acts as the control center, managing the state of the Arcium Network, scheduling Computations, and handling compensation flows.
• Clusters ↔ MXEs. Clusters provide the computational resources (Arx nodes) for running MXEs, which are the isolated environments where confidential computations take place.
• Computation Definitions ↔ Scheduled Computations. Computation Definitions define the tasks to be performed, and Scheduled Computations are the actual executions of those tasks within MXEs.
• Compensation Flow. Rewards for successful Computations flow from “Customers” to Arx Operators and Delegators, incentivizing participation and ensuring network security.

Important to note that while the Arcium Network’s orchestration functionality will be solely integrated with Solana at launch, the Arcium Network is blockchain-agnostic by design and will become a multi-chain Network (currently in Testnet). The Arcium Network offers both a web-based graphical interface for easier access and interaction and a comprehensive Solana-compatible Software Development Kit (SDK) for developers looking to build custom confidential applications.

To learn more about Arx (“the node”) and become an operator click here.

6) Multi-Party Execution Environments (MXEs)

MXEs are the fundamental building blocks of the Arcium Network, as the bespoke environments where computational work is carried out. MXEs are created and configured by Computation Customers for their specific use cases and applications. They are highly configurable, enabling fine-tuning of data provisioning and handling, encryption schemes, and more. MXEs come in two primary forms: Single Use MXEs which can only be used to execute a single computation before they are automatically discarded, and Persistent MXEs which are reusable.[6]

What are MXEs?

MXEs are secure, isolated environments where multiple parties can jointly execute computations while keeping their data confidential from each other. They are often implemented using Trusted Execution Environments (TEEs) like Intel SGX, ARM TrustZone, or Apple’s PCC.

How do they work?

MXEs are the primary environment for encrypted computations. While TEEs can optionally be used for added security, Arcium core approach doesn’t rely on them. Arcium actively confronting these challenges. As Yannik Schrade in his blog posts hardware-based security and cryptographic protocols like our implementation can be used symbiotically. The decision to incorporate TEEs rests with the computational customer and/or node operators. Within MXEs, data is typically encrypted before entering the environment. Computations are then performed on this encrypted data, ensuring confidentiality throughout the process.

Focus:

MXEs are primarily focused on providing a secure environment for executing code, rather than on the specific cryptographic protocols used for the computations.

MXEs and SMPCs are often used together to provide a comprehensive solution for secure computation. The MXE provides a secure environment for executing the MPC protocols, further enhancing the overall security of the system.

7) Why Solana?

Solana’s incredibly high transaction throughput (currently running 2000–3000 TPS), with block production times as low as 400ms and average transaction fees around 0.000112 SOL. Choosing Solana as its foundation gives Arcium a technological edge this makes Arcium accessible and affordable to everyone, regardless of their location or background.

Moreover, Solana has caught up with Ethereum in almost every metric — users, fees, and trading volume.

Dex Volume Solana & Ethereum Credits to @21co

At the time of writing, its validator upgrade to v1.18.15. The updates aim to improve the reliability, security, and efficiency of the system.[11]

“Solana is the most performant permissionless blockchain in the world”.- Anatoly Yacovenko

8) Arcium: Making Data Work for You, Privately

Imagine a world where you could share your data for good, without giving up your privacy. That’s the promise of Arcium, a technology that lets you share and use data securely.

Here are some examples of how Arcium can make a difference in the real world:

i) Defi: The Money Stuff

• Sharing with Safety. Banks can share your information to assess your creditworthiness, fight fraud, and keep things safe, without letting everyone see your personal details.
• Trading Secrets. Companies can use Arcium to share their best investment ideas without giving away all their secrets.
• Following the Rules. Banks can prove they are following the law (like anti-money laundering rules) without revealing specific transactions.
• DeFi Privacy. Decentralized Finance (DeFi) platforms can use Arcium to hide Profit and Loss (P&L) details, ensuring privacy for traders while maintaining transparency and security.

ii) Healthcare: Keeping You Healthy, Keeping You Private

• Research with Respect. Scientists can use Arcium to study your health data, like your DNA, to find new medicines and treatments, without seeing your name or personal information.
• Your Records, Your Control. Doctors can share your medical records for the best possible care, while making sure your private information stays safe.
• Understanding Your Genes. You can share your genetic information with doctors and researchers to learn more about your health and risks, without losing your privacy.

iii) Supply Chains: From Factory to You, Securely

DEPIN (Decentralized Privacy Infrastructure Network) enables secure supply chain collaboration by protecting sensitive data. Companies can share essential information to improve efficiency and combat counterfeits while maintaining confidentiality and control over their data.

• Working Together, Keeping Secrets. Companies can cooperate to make supply chains better, without giving away their competitive advantages.
• Real Stuff, No Fakes. Arcium combines DEPIN & confidential computing can help track products and make sure they are real, fighting counterfeit goods and keeping you safe.
• Ethical Choices, Transparent Actions. Companies can show they use materials and labor ethically, without revealing their sensitive business details.

iv) Government: Helping Everyone, Protecting Everyone

• Data for the People. Government agencies can use Arcium to share data for important decisions, while protecting your privacy.
• Voting, Made Safe. Arcium can help build secure and fair online voting systems, ensuring your vote counts and stays private.
• Fair Deals for Everyone. Governments can run auctions where everyone has a fair chance to win, while protecting the strategies of each bidder.

v) Secure Multi-Party Poker Tournaments

Imagine a high-stakes poker tournament where players from different jurisdictions want to participate. Confidential computing can be used to create a secure environment

where:

1. Card Shuffling and Dealing. The process of shuffling and dealing cards is handled within a confidential computing environment, ensuring that no single party (including the platform operator) has access to the cards before they are revealed. This prevents any manipulation of the deck.
2. Hand Evaluation. The evaluation of winning hands is also done within the confidential computing environment. This guarantees that the results are fair and cannot be altered.
3. Privacy Preservation. Players’ identities and hand histories can be kept private using cryptographic techniques within the confidential computing environment. This addresses privacy concerns and allows players to participate anonymously.

Benefits:

• Enhanced Trust. By leveraging confidential computing, the tournament organizers can demonstrate that the game is fair and unbiased, which is crucial for attracting high-stakes players.
• Regulatory Compliance. The privacy-preserving aspects of confidential computing can help navigate some of the regulatory challenges associated with online gambling. Anonymity and data protection features can make the platform more compliant with various jurisdictions.
• Global Participation. Players from regions with strict gambling regulations may be more willing to participate in a tournament where their privacy is protected and the game’s integrity is guaranteed.

vi) Private Mempools: A Shield for Your Transactions

Imagine a blockchain’s mempool as a public waiting room for transactions. Everyone can see who’s waiting and what they’re carrying (transaction details). This is where MEV (Maximal Extractable Value) comes in. Miners or validators (the folks who add transactions to the blockchain) can see these pending transactions and exploit this information for profit.

This exploitation is known as MEV. It can involve:

• Front-running. A “miner” a.k.a. “Validator” sees your buy order for a token and quickly places their own buy order ahead of yours, driving up the price before you can buy.
• Sandwich attacks. A miner places a buy order before yours, then a sell order after, profiting from the price change they caused.
• Back-running. A miner sees your sell order and places their own sell order right after, profiting from the price drop they triggered.

Private mempools change the game. They act like a VIP lounge where transactions are hidden from prying eyes. Even the node operator cannot see the details of these transactions due to the use of advanced confidential computing techniques like MPC. This prevents MEV attacks because no one knows the specifics of what transactions are waiting to be processed.

Benefits of Private Mempools:

• Fairness. Everyone’s transactions are treated equally, regardless of whether they’re big players or small fish.
• Reduced Costs. Eliminating MEV lowers transaction costs for everyone.
• Increased Privacy. Your transaction details remain confidential until they’re on the blockchain.

Arcium’s Role:

Arcium’s confidential computing technology is perfectly suited for creating private mempools. They can encrypt transaction data so that only authorized parties can access it. This ensures fair and equitable access to blockchain services, especially in areas like DeFi, where MEV extraction can be particularly problematic.

My Humble Opinion

I’ve always been fascinated by the power of on-chain technology. Arcium is quietly leading the way, proving that we don’t have to sacrifice privacy for innovation. They’re not just building tech; they’re building trust in a future where data is the new currency.

Think of Arcium as a high-security bank for your data, protecting your privacy while allowing you to unlock the full potential of your information.

In a world filled with data breaches and misuse, Arcium’s commitment to security, compliance, and data privacy sets a new industry standard. The promise of the project is to enable secure collaboration and protect sensitive information, giving businesses and individuals the confidence to innovate without fear.

Arcium is revolutionizing industries like DeFi, healthcare, and government by using advanced technologies like MPC and other confidential computing tech. They’re also tapping into DEPIN's abovementioned use cases, ensuring transparency and accountability while safeguarding sensitive data.

Yes, everything comes with a trade-off eg. processing transactions privately may introduce delays compared to traditional public mempools (ie. latency). While confidentiality is valuable, balancing it with speed is essential.

I believe that platforms like Arcium will become the norm. Imagine a future where our digital lives are both dynamic and secure, where we can innovate, collaborate, and transact with confidence. This is a future worth investing in, not just financially, but with our hopes for a better tomorrow.

“Just as a seed needs solitude to sprout, ‘Privacy’ is the foundation upon which freedom thrives”. -0xmarkdams

Can’t wait what the great team behind Arcium can offer, so Stay Tuned!

• Arcium Twitter: @ArciumHQ
• Arcium Blog for further reading
• Join our Discord
• Join Arcium on Galxe

References:

[1] https://docs.arcium.com/

[2] https://eprint.iacr.org/2016/1057.pdf

[3] https://www.researchgate.net/publication/358973097_Privacy-preserving_machine_learning_techniques

[4] https://x.com/ArciumHQ/status/1801321157338988950

[5] https://docs.arcium.com/getting-started/high-level-architecture-overview

[6] https://docs.arcium.com/multi-party-execution-environments-mxes/execution-workflow

[7] https://vitalik.eth.limo/general/2022/06/15/using_snarks.html

[8] https://chain.link/education/zero-knowledge-proof-zkp

[9] https://docs.arcium.com/solana-integration/other-blockchains

[10] https://en.wiktionary.org/wiki/arx#Latin

[11] https://github.com/solana-labs/solana/releases/tag/v1.18.15

[12] https://docs.arcium.com/getting-started/network-stakeholders

[13] https://eprint.iacr.org/2010/514.pdf

[14] https://eprint.iacr.org/2023/1548.pdf

[15] https://docs.arcium.com/arx-nodes/node-configuration-and-setup

[16] https://arxiv.org/html/2406.02239v1

[17 ]https://www.cs.utexas.edu/~dwu4/talks/SecurityLunch0214.pdf

Other References consulted are duly Hyperlinked.

Feel free to reach out to me on Twitter @Oxmarkdams with any suggestions or opinions (I value genuine feedback or critique). If you find this even slightly insightful, please share it — I’ve invested a week of refining this content, and your support means everything in helping it educate a wider audience. Thank you.