Batched Threshold Encryption: Unlocking Fair DeFi and Ending Extractive MEV

The decentralized finance (DeFi) landscape promises transparency and equal opportunity. However, a significant challenge persists: Maximal Extractable Value (MEV). This hidden tax on users undermines the core principles of **blockchain fairness**. Fortunately, a revolutionary solution is emerging: **Batched Threshold Encryption** (BTE). This advanced cryptographic technique holds the potential to reshape DeFi, ensuring transaction privacy and ending extractive practices. Understanding BTE is crucial for anyone invested in the future of decentralized systems.

Understanding the MEV DeFi Problem

On most modern blockchains, transaction data is publicly visible. This occurs in the mempool before sequencing, execution, and confirmation within a block. While transparency offers benefits, it also creates vulnerabilities. Sophisticated parties exploit this visibility through extractive practices known as Maximal Extractable Value (MEV).

MEV essentially refers to the maximum value that can be extracted from block production. Block proposers, often miners or validators, can reorder, include, or omit transactions for financial gain. This power allows them to capitalize on user activity.

Common Forms of Extractive MEV

Typical forms of MEV exploitation remain pervasive, particularly on Ethereum. These attacks negatively impact ordinary users. Here are the primary methods:

• Frontrunning: An attacker sees a pending transaction and submits their own transaction with a higher gas fee. Their transaction executes first, profiting from the original user’s move.
• Sandwich Attacks: This involves two transactions. The attacker places one transaction immediately before and another immediately after a target transaction. They manipulate the price of an asset, profiting from the victim’s trade.
• Arbitrage: Exploiting price differences across decentralized exchanges. While not always ‘extractive’ in the same way, block proposers can prioritize their own arbitrage transactions.
• Liquidations: When a collateralized loan falls below a certain threshold, it can be liquidated. Searchers compete to be the first to liquidate, earning a bonus.

These exploits can lead to substantial losses for users. For instance, during a flash crash on Oct. 10, an estimated $2.9 million was extracted on Ethereum alone. Measuring total extractive MEV is difficult. Roughly 32% of these attacks are privately relayed to miners. Some involve over 200 chained subtransactions in a single exploit. This hidden nature makes detection and prevention challenging.

The Promise of DeFi Privacy Through Encryption

The inherent transparency of blockchain mempools, while foundational, inadvertently enables MEV. Therefore, researchers have sought solutions to prevent MEV by redesigning mempools. These designs hold pending transactions encrypted until block finalization. This approach prevents other blockchain participants from seeing pending trades or actions. Consequently, it eliminates the information advantage that MEV extractors exploit.

Many encrypted mempool proposals use some form of Threshold Encryption (TE). TE splits a secret key that can unveil transaction data among several servers. Akin to a multisig wallet, a minimum number of signers must work together. They combine their key shares to unlock the data. This distributed control ensures no single entity can access or manipulate transactions prematurely. Early TE-encrypted mempool schemes, such as Shutter, laid the groundwork for these privacy-preserving systems. However, standard TE faces limitations when scaling to meet the demands of growing DeFi ecosystems.

Introducing Batched Threshold Encryption (BTE)

While standard Threshold Encryption (TE) offers a foundational layer of **DeFi privacy**, it struggles with scalability. Every server must decrypt each transaction separately. Then, it broadcasts a partial decryption share for it. These individual shares are recorded on-chain for aggregation and verification. This process creates a heavy server communication load. It consequently slows the network and increases chain congestion. Such inefficiencies hinder widespread adoption in high-throughput environments.

Batched Threshold Encryption (BTE) solves this critical limitation. BTE allows each server to release a single, constant-sized decryption share. This single share unlocks an entire batch of transactions, regardless of its size. This innovation drastically reduces communication overhead. It also improves network efficiency, making encrypted mempools far more practical for real-world applications. BTE builds on foundational concepts such as threshold cryptography. These concepts enable secure collaboration among multiple parties. They do so without exposing sensitive data to any single participant. BTE represents a significant evolution in the pursuit of secure and scalable transaction privacy.

The Evolution of Batched Threshold Encryption Technology

The journey of **Batched Threshold Encryption** has seen remarkable advancements. Each iteration tackles previous limitations, pushing towards greater efficiency and practicality. For now, all existing work on BTE remains at the prototype or research stage. However, its potential to shape the future of decentralized ledgers is undeniable.

Original BTE (Choudhuri et al., 2024)

The first functional version of BTE emerged from the work of Arka Rai Choudhuri, Sanjam Garg, Julien Piet, and Guru-Vamsi Policharla in 2024. This scheme utilized the KZG commitment scheme. It allowed a committee of servers to lock a polynomial function to a public key. The function remained hidden from both users and committee members initially. Decrypting transactions encrypted to this public key required proving they fit into the polynomial. Since a polynomial of fixed degree is determined by a set number of points, servers only needed to exchange a small amount of data collectively. This provided the necessary proof. Once the shared curve was established, they could send a single, compact piece of information. This unlocked all transactions in the batch at once. Importantly, transactions not fitting the polynomial remained locked. This ensured selective revelation of encrypted transactions, preserving privacy for others. Current TE implementations, like Ferveo and MEVade, could integrate this BTE to maintain privacy for non-batch-included transactions.

Despite its breakthroughs, this initial BTE version had two major drawbacks:

• It required a full reinitialization of the system. This included a new round of key generation and parameter setup for each new batch of transactions.
• Decryption consumed significant memory and processing power. Nodes worked intensively to combine all partial shares.

These factors limited BTE’s practicality. Frequent Distributed Key Generation (DKG) execution for committee refresh and block processing made the scheme prohibitive. This was true even for moderately sized permissioned committees, let alone scaling to a permissionless network.

Upgrades to BTE: Enhancing Efficiency and Trust

Subsequent research rapidly addressed the initial limitations of BTE, leading to significant improvements:

One-Time Setup BTE (Choudhuri, Garg, Policharla, Wang, 2025)

Choudhuri, Garg, Policharla, and Wang introduced the first upgrade in 2025. Their scheme, the one-time setup BTE, improved server communication. It required only a single initial Distributed Key Generation (DKG) ceremony. This DKG ran once across all decryption servers. However, a multiparty computation protocol was still necessary to set up the commitment for each batch. This marked a step forward but still left room for further optimization.

BEAT-MEV (Bormet, Faust, Othman, Qu, 2025)

The first truly epochless BTE scheme arrived in August 2025 with BEAT-MEV. Bormet, Faust, Othman, and Qu achieved a single, one-time initialization that could support all future batches indefinitely. This breakthrough used two advanced tools: puncturable pseudorandom functions and threshold homomorphic encryption. Servers could reuse the same setup parameters indefinitely. Each server only needed to send a small piece of data during decryption. This kept server communication costs remarkably low, a critical step for scalability.

BEAST-MEV (Silent Batched Threshold Encryption)

Down the line, another paper introduced Silent Batched Threshold Encryption (SBTE), or BEAST-MEV. This innovative concept removed the need for any interactive setup between servers. It replaced repeated coordination with a non-interactive, universal one-time setup. This allowed nodes to operate independently. However, combining all partial decryptions afterward still required heavy interactive computation. To fix this, BEAST-MEV borrowed BEAT-MEV’s sub-batching technique. It then used parallel processing. This allowed the system to decrypt large batches (up to 512 transactions) in under one second. These advancements demonstrate a clear path towards practical and efficient BTE implementation.

The following table summarizes how each successive BTE design improves on the original design:

BTE’s Impact on Layer 2 Security and Scalability

The integration of **Batched Threshold Encryption** holds immense potential for **Layer 2 Security** and scalability. Layer-2 rollups, such as Metis, Espresso, and Radius, already pursue fairness and privacy. They often use time-delay encryption or trusted sequencers. However, BTE offers a more robust and trustless approach. By incorporating BTE, these rollups can achieve an ordering process that is entirely trustless. This prevents anyone from exploiting transaction visibility. Arbitrage or liquidation gains, common MEV tactics, become virtually impossible. Furthermore, BTE’s efficiency in handling batches directly contributes to the scalability goals of Layer 2 solutions. It processes more transactions securely without increasing network congestion.

BTE ensures that pending transactions remain encrypted. Only after block finalization does decryption occur. This eliminates the window of opportunity for malicious actors. It protects users from frontrunning and sandwich attacks. Moreover, for cases of selective decryption, BTE makes all decryption shares publicly verifiable. This transparency allows anyone to detect dishonest behavior. Consequently, it enables the penalization of offenders via slashing mechanisms. This feature maintains reliability, provided a threshold of honest servers remains active. Therefore, BTE strengthens the security guarantees of Layer 2 networks. It also fosters a more equitable environment for all participants.

Ensuring Blockchain Fairness with BTE

The core promise of **Batched Threshold Encryption** is to restore **blockchain fairness**. By encrypting transactions in the mempool, BTE directly addresses the information asymmetry that MEV exploits. No longer can sophisticated parties peek into pending transactions to gain an unfair advantage. This means the playing field becomes level for all users.

BTE’s ability to provide epochless, constant-size decryption shares is a game-changer. It offers pending transaction privacy for Layer-2 rollups. This is crucial for protocols like CoW Swap. CoW Swap already mitigates MEV through batch auctions and intent-based matching. Yet, parts of its order flow remain exposed in public mempools. Integrating BTE before solver submission would effectively seal this gap. It would provide end-to-end transaction privacy. This ensures that even in complex trading environments, user intentions remain confidential until execution. Ultimately, BTE empowers users by protecting their financial interests from predatory practices. It moves DeFi closer to its ideal of an open, equitable, and fair financial system.

The Road Ahead for DeFi Privacy and Adoption

While still in research and prototype stages, the potential for **Batched Threshold Encryption** is undeniable. Its evolution from basic Threshold Encryption to sophisticated, epochless, and silent schemes demonstrates rapid progress. This creates a clear opportunity for more research and potential adoption. Protocols that prioritize user protection and fair execution will likely be early adopters. For now, Shutter Network remains the most promising candidate for early implementation. Other protocols will likely follow once implementation frameworks become more mature and battle-tested.

The ongoing development of BTE signifies a critical step forward for **DeFi privacy**. It moves beyond theoretical concepts to practical, scalable solutions. As the DeFi ecosystem continues to grow, protecting users from extractive MEV becomes paramount. BTE offers a robust cryptographic primitive to achieve this. It ensures that the future of decentralized finance remains true to its foundational principles of transparency, security, and most importantly, fairness for all participants.

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