DeepSafe encryption random verification proxy technology: a new paradigm of Decentralization security

The encryption asset market has developed into a massive economic system. By the beginning of 2025, the total market value of global encryption assets exceeded $3 trillion, with Bitcoin’s single asset market value surpassing $1.5 trillion, and the Ethereum ecosystem’s market value approaching $1 trillion. This scale is comparable to the total national economy of some developed countries, and encryption assets are gradually becoming an important component of the global financial system.

However, the security issues behind such a large asset scale have always loomed over all users. From the collapse of FTX in 2022 to the oracle governance attack incident in early 2024, security events have frequently occurred in the encryption field, profoundly exposing the hidden “centralization traps” in the current ecosystem. Although the underlying public chain itself is relatively decentralized and secure, the cross-chain services, oracles, wallet management, and other facilities built on it often rely on a limited number of trusted nodes or institutions, effectively reverting to a centralized trust model, creating weak links in security.

According to statistics, between 2023 and 2024 alone, hackers have stolen more than $3 billion worth of encryption assets through attacks on various blockchain applications, with cross-chain bridges and centralized verification mechanisms being the main targets. These security incidents have not only caused significant economic losses but have also severely damaged users’ trust in the entire encryption ecosystem. In the face of a trillion-dollar market, the lack of decentralized security infrastructure has become a key obstacle to the further development of the industry.

True decentralization is not just about dispersing execution nodes, but fundamentally redistributing power—from the hands of a few to the entire network of participants, ensuring that the system’s security does not depend on the honesty of specific entities. The essence of decentralization is to replace human trust with mathematical mechanisms. DeepSafe’s encryption random verification agent (CRVA) technology is the concrete practice of this idea.

CRVA integrates four cutting-edge cryptographic technologies: zero-knowledge proofs (ZKP), ring verifiable random functions (Ring-VRF), multi-party computation (MPC), and trusted execution environments (TEE) to build a truly decentralized verification network, achieving a mathematically provable secure blockchain application infrastructure. This innovation not only breaks the limitations of traditional verification models in technology but also redefines the implementation path of decentralization conceptually.

encryption random verification agent ( CRVA ): The technological core of DeepSafe

Encryption Random Verification Agent ( Crypto Random Verification Agent, CRVA ) is the core of the DeepSafe technology architecture. It is essentially a distributed verification committee composed of multiple randomly selected verification nodes. Unlike traditional verification networks that explicitly specify certain validators, the nodes in the DeepSafe network do not know who has been chosen as validators, fundamentally eliminating the possibility of collusion and targeted attacks.

The CRVA mechanism addresses the long-standing “key management dilemma” in the blockchain world. In traditional solutions, verification permissions are often centralized in fixed multi-signature accounts or sets of nodes. If these known entities are attacked or collude to commit wrongdoing, the entire system’s security will be at risk of collapse. CRVA achieves an “unpredictable, untraceable, and untargetable” verification mechanism through a series of cryptographic innovations, providing a mathematical level of assurance for asset security.

The operation of CRVA is based on three principles: “Hidden members and verification content + Dynamic rotation + Threshold control.” The identities of the verification nodes in the DeepSafe network are kept strictly confidential, and the verification committee will be randomly restructured on a regular basis. During the verification process, a threshold multi-signature mechanism is used to ensure that only when a specific proportion of nodes cooperate can the verification be completed. Verification nodes in the DeepSafe network are required to stake a large amount of tokens, and the penalty mechanism set for non-participating nodes increases the cost of attacking verification nodes. The dynamic rotation and hiding mechanism of CRVA, combined with the penalty mechanism for verification nodes, makes it theoretically challenging for hackers to attack DeepSafe verification nodes to steal transactions, approaching the difficulty of “attacking the entire network.” With current computing power, it is practically impossible to meet the threshold to attack DeepSafe verification nodes.

The technological innovation of CRVA stems from a profound reflection on traditional security models. Most existing solutions only focus on “how to prevent known validators from acting maliciously,” while CRVA raises a more fundamental question: “How to ensure that no one knows who the validators are, including the validators themselves?” This achieves internal prevention of malicious actions and external defense against hackers, eliminating the possibility of power centralization. This shift in thinking realizes a leap from “human honesty assumptions” to “mathematically proven security.”

In-Depth Analysis of the Four Core Technologies of CRVA

Technology Overview and Synergy

The innovation of CRVA is based on the deep integration of four cutting-edge encryption technologies, which together construct a mathematically provably secure verification system. Before delving into each technology, let’s briefly understand their basic functions and collaborative relationships:

1. Ring Verifiable Random Function (: Provides verifiable randomness and anonymity from external observers, making it impossible for both internal and external parties to determine which nodes are selected as validators.

2. Zero-Knowledge Proof ) ZKP (: Allows nodes to prove their eligibility for transaction verification without exposing their identity, protecting node privacy and communication security.

3. Multi-Party Computation ) MPC (: Achieves distributed key generation and threshold signing, ensuring that no single node has complete control over the key. At the same time, distributed keys and threshold signing thresholds can effectively prevent efficiency issues caused by single point failures of nodes leading to system paralysis.

4. Trusted Execution Environment ) TEE (: Provides a hardware-level isolated execution environment that protects the security of sensitive code and data, and neither the node holders nor the maintenance personnel of the node devices can access or modify the internal data of the node.

These four technologies form a close security loop in CRVA, working together and reinforcing each other to build a multi-layered security architecture. Each technology addresses a core challenge of Decentralization verification, and their systematic combination makes CRVA a secure verification network that does not rely on trust assumptions.

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) Ring-VRF###: a combination of randomness and anonymity

Ring-VRF( is one of the core innovative technologies in CRVA, addressing the key question of “how to randomly select validators while protecting the privacy of the selection process.” Traditional verifiable random functions VRF) are cryptographic tools that allow users holding a specific private key to generate random numbers that can be publicly verified. However, this process exposes the identity of the generator. Ring signatures are a technique that allows the signer to hide among a group of people. Ring-VRF combines the advantages of these two technologies, achieving a unity of “verifiable randomness” and “anonymity to external observers.”

Ring-VRF innovatively places the public keys of multiple VRF instances into a “ring”. When a random number is needed, the system can confirm that the random number is indeed generated by a member of the ring, but it cannot determine exactly which one. This way, even though the process of generating the random number is verifiable, the identity of the generator remains anonymous to external observers. When a verification task comes in, each node in the network (which possesses its own long-term key pair) generates a temporary identity and puts it into a “ring”. The system uses this ring for random selection, but due to the protection of the ring signature mechanism, external observers cannot determine which specific nodes were selected.

Ring-VRF provides two layers of protection for CRVA. Ring-VRF ensures the randomness and verifiability of the node selection process while protecting the anonymity of the selected nodes, making it impossible for external observers to determine which nodes participated in the validation. This design significantly increases the difficulty of attacks against validators. In the CRVA mechanism, a complex validation participation mechanism is constructed through the deep integration of technologies such as Ring-VRF, ZKP, MPC, and TEE, greatly reducing the possibility of collusion and targeted attacks among nodes.

( Zero-Knowledge Proof ) ZKP (: Mathematical guarantees for hiding identity

Zero-Knowledge Proof ) is a cryptographic technique that allows one party to prove to another party that a certain fact is true without revealing any other information apart from the fact being true. In CRVA, ZKP is responsible for protecting the privacy of node identities and the verification process. In traditional node communication, the prover typically needs to present all evidence to the verifier. However, in zero-knowledge proofs, the prover can convince the verifier that a statement is true without disclosing any specific information supporting that statement.

CRVA uses ZKP to achieve two key functions. Each validation node in the network has a long-term identity (i.e., a permanent key pair), but directly using these identities poses security risks of exposing the node’s identity. Through ZKP, nodes can generate “temporary identities” and prove “I am a legitimate node in the network” without revealing “which specific node I am.” When nodes participate in the validation committee, they need to communicate and cooperate with each other. ZKP ensures that these communication processes do not leak the node’s long-term identity, allowing nodes to prove their qualifications without exposing their real identities. The ZKP technology ensures that even with long-term observation of network activities, attackers cannot determine which nodes participated in the validation of specific transactions, thus preventing targeted attacks and long-term analysis attacks. This is an important foundation for CRVA to provide long-term security assurances.

Multi-Party Computation ( MPC ): Distributed Key Management and Threshold Signing

Multi-Party Computation ( technology solves another key problem in CRVA: how to securely manage the keys required for verification, ensuring that no single node can control the entire verification process. MPC allows multiple parties to jointly compute a function while keeping their respective inputs private. Simply put, participants can collaborate to complete a computational task, but each person only knows their own part of the input and output, and does not know anyone else’s secret information. It’s like several people working together to complete a jigsaw puzzle, where each person is responsible for their own piece, but together they can create the complete picture.

In CRVA, when a group of nodes is selected as the validation committee, they need a common key to sign the validation results. Through the MPC protocol, these nodes jointly generate a distributed key, where each node holds only a shard of the key, and the complete key never appears in any single node. Secondly, CRVA sets a threshold (e.g., 9 out of 15 nodes), and only when the number of cooperating nodes reaches or exceeds this threshold can a valid signature be generated. This ensures that even if some nodes go offline or are attacked, the system can still operate, ensuring the efficient functioning of the entire system. MPC technology allows validation nodes to securely and efficiently complete their tasks even under unstable network conditions. This optimization takes into account the complexity and uncertainty of blockchain networks, ensuring that validation can be reliably performed in various network environments.

To further enhance security, CRVA has fully implemented the MPC technology system, including Distributed Key Generation ) DKG ###, Threshold Signature Scheme ( TSS ), and Key Handover Protocol ( Handover Protocol ). The system achieves complete key shard updates by regularly rotating the verification committee members.

This design creates a crucial “time isolation” security feature. The committee composed of CRVA nodes rotates regularly (initially approximately every 20 minutes per cycle), old key shards become invalid, and brand new key shards are generated and allocated to new members. This means that even if an attacker successfully breaches some nodes and obtains key shards during the first period, these shards will become completely invalid after the next rotation cycle.

Assuming the threshold requirement is 9 out of 15 nodes, an attacker cannot accumulate 9 valid shards by breaking into “3 nodes today, 3 nodes tomorrow, and another 3 nodes the day after” because the shards obtained in the first two days have already expired. The attacker must simultaneously control at least 9 nodes within the same rotation period to pose a threat, which significantly increases the difficulty of the attack and enables CRVA to effectively resist long-term sustained attacks.