Weihao Bai, Long Chen, Qianwen Gao, Zhenfeng Zhang
The MPC-in-the-Head framework has been proposed as a solution for Non-Interactive Zero-Knowledge Arguments of Knowledge (NIZKAoK) due to its efficient proof generation. However, most existing NIZKAoK constructions using this approach require multiple MPC evaluations to achieve negligible soundness error, resulting in proof size and time that are asymptotically at least λ times the size of the circuit of the NP relation. In this paper, we propose a novel method to eliminate the need for repeated MPC evaluations, resulting in a NIZKAoK protocol for any NP relation that we call Diet. The proof size and time of Diet are asymptotically only polylogarithmic with respect to the size of the circuit C of the NP relation, but are independent of the security parameter λ. Hence, both the proof size and time can be significantly reduced.Moreover, Diet offers promising concrete efficiency for proving Learning With Errors (LWE) problems and its variants. Our solution provides significant advantages over other schemes in terms of both proof size and proof time, when considering both factors together. Specifically, Diet is a promising method for proving knowledge of secret keys for lattice-based key encapsulation mechanisms (KEMs) such as Frodo and Kyber, offering a practical solution to future post-quantum certificate management. For Kyber 512, our implementation achieves an online proof size of 83.65 kilobytes (KB) with a preprocessing overhead of 152.02KB. The implementation is highly efficient, with an online proof time of only 0.68 seconds and a preprocessing time of 0.81 seconds. Notably, our approach provides the first reported implementation of proving knowledge of secret keys for Kyber 512 using post-quantum primitives-based zero-knowledge proofs.
Zheyuan He, Zihao Li, Ao Qiao, Xiapu Luo · 9 authors
Blockchains, with intricate architectures, encompass various components, e.g., consensus network, smart contracts, decentralized applications, and auxiliary services. While offering numerous advantages, these components expose various attack surfaces, leading to severe threats to blockchains. In this study, we unveil a novel attack surface, i.e., the state storage, in blockchains. The state storage, based on the Merkle Patricia Trie, plays a crucial role in maintaining blockchain state. Besides, we design Nurgle, the first Denial-of-Service attack targeting the state storage. By proliferating intermediate nodes within the state storage, Nurgle forces blockchains to expend additional resources on state maintenance and verification, impairing their performance. We conduct a comprehensive and systematic evaluation of Nurgle, including the factors affecting it, its impact on blockchains, its financial cost, and practically demonstrating the resulting damage to blockchains. The implications of Nurgle extend beyond the performance degradation of blockchains, potentially reducing trust in them and the value of their cryptocurrencies. Additionally, we further discuss three feasible mitigations against Nurgle. At the time of writing, the vulnerability exploited by Nurgle has been confirmed by six mainstream blockchains, and we received thousands of USD bounty from them.
Zero-Knowledge (ZK) proofs were introduced in the seminal work of Goldwasser, Micali, and Rackoff (STOC 1985) and remain one of the cornerstones of modern cryptography. With the advent of Blockchains, there has been reinvigorated interest in deploying ZK-proof systems in the form of ZK-SNARKs. ZKSNARKs are an attractive variant as they are non-interactive (in fact, publicly verifiable) and succinct. Yet, current deployments require huge running times and/or very large memory, and scaling them to large circuits cannot be accomplished on commodity hardware. We design and implement an efficient sublinear non-interactive zero-knowledge system, Ligetron that can be deployed as a web application and scales to billions of gates. Core to our construction is identifying a good intermediate representation, namely Web Assembly (WASM) that is: (1) versatile to represent complex computations, (2) can be compiled from most popular high-level languages, and (3) embodies rich semantics to derive space-efficiency. On the backend, we design and implement a space-efficient variant of the Ligero ZK system introduced in the work of Ames et al. (ACM CCS 2017) that can leverage the semantics of WASM. Ligetron is the first post-quantum ZK-SNARK to scale to billion gates and run from a browser. On commodity hardware, Ligetron scales to arbitrarily large circuits while showcasing competitive prover/verifier running times and better proof lengths than all previous post-quantum ZK-SNARKs.
Tianyi Liu, Tiancheng Xie, Jiaheng Zhang, Dawn Song · 5 authors
In the past decade, blockchains have seen various financial and technological innovations, with cryptocurrencies reaching a market cap of over 1 trillion dollars. However, scalability is one of the key issues hindering the deployment of blockchains in many applications. To improve the throughput of the transactions, zkRollups and zkEVM techniques using the cryptographic primitive of zero-knowledge proofs (ZKPs) have been proposed and many companies are adopting these technologies in the layer-2 solutions. However, in these technologies, the proof generation of the ZKP is the bottleneck and the companies have to deploy powerful machines with TBs of memory to batch a large number of transactions in a ZKP.In this work, we improve the scalability of these techniques by proposing new schemes of fully distributed ZKPs. Our schemes can improve the efficiency and the scalability of ZKPs using multiple machines, while the communication among the machines is minimal. With our schemes, the ZKP generation can be distributed to multiple participants in a model similar to the mining pools. Our protocols are based on Plonk, an efficient zero-knowledge proof system with a universal trusted setup. The first protocol is for data-parallel circuits. For a computation of M sub-circuits of size T each, using M machines, the prover time is O(T log T + M log M), while the prover time of the original Plonk on a single machine is O(MT log(MT )). Our protocol incurs only O(1) communication per machine, and the proof size and verifier time are both O(1), the same as the original Plonk. Moreover, we show that with minor modifications, our second protocol can support general circuits with arbitrary connections while preserving the same proving, verifying, and communication complexity. The technique is general and may be of independent interest for other applications of ZKP.We implement Pianist (Plonk vIA uNlimited dISTribution), a fully distributed ZKP system using our protocols. Pianist can generate the proof for 8192 transactions in 313 seconds on 64 machines. This improves the scalability of the Plonk scheme by 64×. The communication per machine is only 2.1 KB, regardless of the number of machines and the size of the circuit. The proof size is 2.2 KB and the verifier time is 3.5 ms. We further show that Pianist has similar improvements for general circuits. On a randomly generated circuit with 225gates, it only takes 5 s to generate the proof using 32 machines,24.2× faster than Plonk on a single machine.
2 source records
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Peiyao Sheng, Chenyuan Wu, Dahlia Malkhi, Michael K. Reiter · 7 authors
This paper introduces and develops the concept of ``ticketing'', through which atomic broadcasts are orchestrated by nodes in a distributed system. The paper studies different ticketing regimes that allow parallelism, yet prevent slow nodes from hampering overall progress. It introduces a hybrid scheme which combines managed and unmanaged ticketing regimes, striking a balance between adaptivity and resilience. The performance evaluation demonstrates how managed and unmanaged ticketing regimes benefit throughput in systems with heterogeneous resources both in static and dynamic scenarios, with the managed ticketing regime performing better among the two as it adapts better. Finally, it demonstrates how using the hybrid ticketing regime performance can enjoy both the adaptivity of the managed regime and the liveness guarantees of the unmanaged regime.
Rishik Yadav, Anurag Sharma, Sachin Kumar, Paramita De
Effective portfolio management tools are becoming more and more necessary as the cryptocurrency industry grows in order to assist investors in navigating the potential and hazards associated with it. The creation of an all-inclusive cryptocurrency portfolio management system that uses realtime data tracking and analysis to assist investors in making wise selections has been presented in this study. The trustworthy and dependable library for password hashing, bcrypt, is incorporated with a focus on user data protection. This is done in order to protect sensitive data and personal information. The platform gives users access to performance graphs and comprehensive details for each cryptocurrency, in addition to realtime statistics covering a wide range of cryptocurrencies. In addition, it can display the current live price of each supported cryptocurrency. One can keep an eye on price fluctuations around-the-clock and watch the assets in real time.
C. Li, Sidi Mohamed Beillahi, Guang Yang, Ming Wu · 6 authors
Authenticated storage access is the performance bottleneck of a blockchain, because each access can be amplified to potentially O (log n ) disk I/O operations in the standard Merkle Patricia Trie (MPT) storage structure. In this article, we propose a multi-Layer Versioned Multipoint Trie (LVMT), a novel high-performance blockchain storage with significantly reduced I/O amplifications. LVMT uses the authenticated multipoint evaluation tree vector commitment protocol to update commitment proofs in constant time. LVMT adopts a multi-layer design to support unlimited key–value pairs and stores version numbers instead of value hashes to avoid costly elliptic curve multiplication operations. In our experiment, LVMT outperforms the MPT in real Ethereum traces, delivering read and write operations 6× faster. It also boosts blockchain system execution throughput by up to 2.7×.
In the context of industrial environment, devices, such as robots and drones, are vulnerable to malicious activities such device tampering (e.g., hardware and software changes). The problem becomes even worse in a multi-stakeholder environment where multiple players contribute to an ecosystem. In such scenarios, particularly, when devices are deployed in remote settings, ensuring device integrity so that all stakeholders can trust them is challenging. Existing methods, often depend on additional hardware like the Trusted Platform Module (TPM) which may not be universally provided by all vendors. In this study, we introduce a distributed ledger technology-oriented architecture to monitor the remote devices' integrity using eUICC technology, a feature commonly found in industrial devices for cellular connectivity. We propose that using secure applets in eUICC, devices' integrity can be monitored and managed without installing any additional hardware. To this end, we present an end-to-end architecture to monitor device integrity thereby enabling all the stakeholders in the system to trust the devices. Additionally, we leverage the properties of immutable databases to provide robustness and efficiently to our model. In our primary evaluations, we measure the overhead caused by hashing our proposed data packets and performance of integrating an immutable database into our system. Our results show that performing hashing on our data packets takes order of microseconds, while reading and writing to an immutable database also requires only milliseconds.
The rise of decentralized finance (DeFi), Web 3.0, and other blockchain-based applications has led to an increased demand for on-chain data analysis across multiple blockchains. Conducting advanced queries, such as data aggregation and correlation analysis, is essential for gaining valuable insights in this context. However, multi-chain queries pose several challenges for the querying system, including compatibility with existing blockchains, supporting diverse query types, and ensuring the integrity of query results. To tackle these challenges, we propose a novel paradigm called verifiable virtual filesystem (V2FS). V2FS extends the POSIX I/O interface, shifting the focus from verifying computation to verifying data. This innovative approach empowers query clients to leverage an off-the-shelf database engine to evaluate queries using verifiable data retrieved from an indexing service provider (ISP). Our solution ensures strong integrity guarantees and can be smoothly integrated with existing database engines to support various query types. To achieve blockchain compatibility, we utilize the DCert framework to certify blocks from different blockchains, making our system applicable to various blockchain systems. Furthermore, we propose cache-based algorithms and a bloom filter-integrated algorithm to optimize query performance and minimize network communication costs. Security analysis and empirical study validate the effectiveness and efficiency of the proposed system.
Cloud storage is crucial for managing large datasets, but dependence on a single cloud space raises security concerns. Conversely, Distributed Ledger Technology (DLT) provides a secure cloud-based storage system operating on a peer-to-peer network. In our proposed system, user files are encrypted and distributed across multiple peers using the Interplanetary File System (IPFS) protocol, with hash values stored in the DLT. This project integrates DLT and a cloud platform for storing files from various users. Our project, Distributed Cloud File Sharing Technology (DCFST), merges distributed computing principles with cloud technology to overcome traditional file-sharing limitations. It enables secure file sharing, storage, and access across interconnected devices, ensuring data integrity and authentication through blockchain. Smart contracts automate access control, granting precise content control to users. DCFST orchestrates a peer-to-peer network of nodes, with a central coordinator managing node discovery, file indexing, and load balancing. The implementation utilizes Python, J avaScrlpt, and Ethereum for smart contract execution. DCFST introduces a resilient, user-centric file-sharing ecosystem by merging distributed systems with cloud infrastructure. It contributes to decentralized technology evolution, revolutionizing data collaboration and access paradigms.
Decentralized file storage has emerged as a transformative solution to address the challenges of centralized data storage, offering enhanced security, privacy, and resilience in the digital age. This research paper explores the significance of decentralized file storage systems and examines the technologies involved, including blockchain, Polygon, Web3, IPFS, and MetaMask. Through a comprehensive analysis of the architecture, implementation details, security considerations, performance evaluations, and real-world applications, key findings highlight the advantages of decentralized storage solutions over traditional centralized counterparts. The research underscores the importance of decentralization in fostering data sovereignty, transparency, and inclusivity, while offering insights into the potential impact on various industries and scenarios.
Viktor Valaštín, Roman Bitarovský, Kristián Košťál, Ivan Kotuliak
Blockchain is a technology that is often used to share data and assets. However, in the decentralized ecosystem, blockchain-based systems can be utilized to share information and assets without the traditional barriers associated with solo responsibility, e.g., multi-sig wallets. This paper describes an innovative approach to blockchain networks based on a non-fungible token that behaves as an account (NFTAA). The key novelty of this article is using NFTAA to leverage the unique properties of NFTs to manage your ownership better and effectively isolate them to improve the security, transparency, and even interoperability possibilities. Additionally, the account-based solution gives us the ability and flexibility to cover regular use cases such as staking and liquid equities, but also practical composability. This article offers a simple implementation, which allows developers and researchers to choose the best solution for their needs in demand of abstract representation in any use case.
In blockchain-based data marketplaces, the cross-chain solution based on relay chains has become an effective way to support digital asset transfer between heterogeneous blockchains. If a digital asset is popular, it will be frequently transferred between multiple data marketplaces. Digital assets are typically represented as (Non-fungible Tokens) NFTs. However, when utilizing a cross-chain transfer scheme based on a relay chain that involves locking, unlocking and burning of the NFT, it can lead to significant transaction costs. Due to the frequent minting and burning of popular NFTs, they tend to consume a significant amount of gas, resulting in high transaction costs. To address this issue, we propose the DART scheme, a secure and low-cost cross-chain transaction scheme for popular digital assets based on (dynamic NFT) DNFT and relay chain. The scheme mainly includes three aspects: Firstly, the initial owner of (Data NFT) DataNFT locks it onto the gateway contract on SChain, mints a (Cross-chain NFT) CNFT on the relay chain that references the DataNFT for resale, and minted DataNFT on the destination blockchain until the CNFT is no longer being resold. Secondly, the DNFT standard is utilized to implement CNFTs. The DNFT standard records the transaction hash of each CNFT resale, ensuring the secure reselling of DataNFTs. Thirdly, the metadata of DataNFT is encrypted to ensure its security during cross-chain transmission. Finally, we selected Axelar Network as the relay network and successfully implemented a prototype of the system. The experimental results demonstrate the feasibility of our proposed scheme.
Financial markets, particularly cryptocurrency markets, are characterized by high volatility and sudden price jumps, making it essential to develop models that can capture these dynamics effectively. In this paper, our focus lies on the Merton’s jump diffusion model, employing jump processes characterized by the compound Poisson process. Our primary objective is to forecast the drift and volatility of the model using a variety of methodologies. We adopt an approach that involves implementing different drift, volatility, and jump terms within the model through various machine learning techniques, traditional methods, and statistical methods on price-volume data. Additionally, we introduce a path-dependent Monte Carlo simulation to model cryptocurrency prices, taking into account the volatility and unexpected jumps in prices. The results indicate that incorporating jump processes significantly improves forecasting accuracy, especially in volatile markets. Our findings highlight the effectiveness of combining machine learning and traditional methods for more robust predictions.
Verifiable encryption (VE) is a protocol where one can provide assurance that an encrypted plaintext satisfies certain properties, or relations. It is an important building block in cryptography with many useful applications, such as key escrow, group signatures, optimistic fair exchange, and others. However, the majority of previous VE schemes are restricted to instantiation with specific public-key encryption schemes or relations. In this work, we propose a novel framework that realizes VE protocols using zero-knowledge proof systems based on the MPC-in-the-head paradigm (Ishai et al. STOC 2007). Our generic compiler can turn a large class of zero-knowledge proofs into secure VE protocols for any secure public-key encryption scheme with the undeniability property, a notion that essentially guarantees binding of encryption when used as a commitment scheme. Our framework is versatile: because the circuit proven by the MPC-in-the-head prover is decoupled from a complex encryption function, the work of the prover is focused on proving the encrypted data satisfies the relation, not the proof of plaintext knowledge. Hence, our approach allows for instantiation with various combinations of properties about the encrypted data and encryption functions. We then consider concrete applications, to demonstrate the efficiency of our framework, by first giving a new approach and implementation to verifiably encrypt discrete logarithms in any prime order group more efficiently than was previously known. Then we give the first practical verifiable encryption scheme for AES keys with post-quantum security, along with an implementation and benchmarks.
The virtue of data forgetting has become a substantial demand in the digital era. Once online content has served its purpose, the concept of forgetting arises to ensure that data remains private between data owners and service providers. Despite significant advancements in supporting data forgetting through approaches like access heuristics, elastic expiration times, and manual revocation, the existing research falls short in addressing the demand for a multi-level forgetting structure that can cater to diverse audience-based expiration requirements while considering additional criteria. To the best of our knowledge, no prior works have investigated this gap, emphasizing the need for a comprehensive solution that can effectively accommodate the varying expiration needs of different audience groups. In this paper, we introduce a novel disjunctive multi-level forgetting scheme designed to meet the aforementioned demand for data forgetting. Our scheme introduces unique expiration periods for the encrypted data the service provider stores, called levels. Users are grouped into different levels based on priorities assigned by the data owners. Each level corresponds to a specific expiration threshold, enabling designated user groups to access the content within its validity period before it is forgotten. This approach enables selective data forgetting for one group while enabling concurrent access and retention for other user groups until the stipulated expiration period elapses. To achieve this, we have devised a cutting-edge system that integrates a hierarchical and dynamic scheme utilizing a key decay for managing expiration periods. Moreover, we introduce an innovative approach that harnesses smart contracts on a local Ethereum blockchain to enforce regulations and streamline the secure and efficient expiration and deletion of data. Finally, we thoroughly evaluate our proposed scheme, focusing on decay sensitivity, computational complexity, and rigorous security analysis.
Open access
Advanced Steganography and Watermarking Techniques
In the realm of Distributed Ledgers (DLs), a solution to enhancing maximum peak throughput involves establishing multiple independent blockchains that evolve concurrently. However, an excess of parallel chains in comparison to the application's demands can result in increased latency in content delivery, squandered bandwidth, and heightened computational strain on network nodes.
Distributed ledger technology (DLT) as an rising alternative for improving safety and transparency in reportsharing structures is very promising. In this regard, the existing have a look at is providing a blockchain-based system for file sharing where allotted ledgers may be used to conquer the restrictions of centralized structures. To make certain that the records shared is secure, unchangeable, and necessary, the gadget applies consensus, hashing, and encryption strategies. The use of clever contracts lets in for automatic execution of documentsharing transactions in a steady manner, thus lowering the capability risks associated with fraud or prison troubles. Furthermore, users are furnished with more control by letting them specify permissions and get right of entry to constraints for his or her documents. To make it smooth to use the blockchain and combine those technologies, the system makes use of decentralized file storage primarily based on Blockchain. Also, the databases used by this machine are FileCoin for login information and Web3 Token for document sharing and storing, which brings protection into the scene, makes storage decentralized, and increases transparency.
The Financial system has witnessed rapid technological changes. The rise of Bitcoin and other crypto assets based on Distributed Ledger Technology mark a fundamental change in the way people transact and transmit value over a decentralized network, spread across geographies. This has created regulatory and tax policy blind spots, as governments and tax administrations take time to understand and provide policy responses to this innovative, revolutionary, and fast-paced technology. Due to the breakneck speed of innovation in blockchain technology and advent of Decentralized Finance, Decentralized Autonomous Organizations and the Metaverse, it is unlikely that the policy interventions and guidance by regulatory authorities or tax administrations would be ahead or in sync with the pace of innovation. This paper tries to explain the principles on which crypto assets function, their underlying technology and relates them to the tax issues and taxable events which arise within this ecosystem. It also provides instances of tax and regulatory policy responses already in effect in various jurisdictions, including the recent changes in reporting standards by the FATF and the OECD. This paper tries to explain the rationale behind existing laws and policies and the challenges in their implementation. It also attempts to present a ballpark estimate of tax potential of this asset class and suggests creation of global public digital infrastructure that can address issues related to pseudonymity and extra-territoriality. The paper analyses both direct and indirect taxation issues related to crypto assets and discusses more recent aspects like proof-of-stake and maximal extractable value in greater detail.
This paper presents, for the first time, the Mediterraneous protocol. It is designed to support the development of an Internet of digital services, owned by their creators, and consumed by users by presenting their decentralised digital identity and a proof of service purchase. Mediterraneous is Self-Sovereign Identity (SSI) native, integrating the SSI model at the core of its working principles to overcome the limitations resulting from using pseudonyms and centralised access control of existing Web3 solutions.
M. S. Anbarasi, P. Barath, Y. Bharath, Arun Kumar J. · 5 authors
In the realm of cloud server operations, where the sheer volume of daily transactions is immense, safeguarding data security is paramount. One of the significant challenges faced is the verification of transaction logs, as attackers may attempt to tamper with them. The current system, utilizing Proof of Work (PoW) for blockchain, falls short by lacking robust data encryption, thereby exposing a critical vulnerability. This proposed paper introduces an innovative solution by integrating the more secure and energy-efficient Proof of Stake (PoS) algorithm with Blowfish encryption. The combination of PoS and Blowfish addresses the identified weaknesses effectively. PoS introduces a novel approach by relying on validators who have a stake in the network, creating a powerful deterrent against log tampering. This not only enhances the integrity of the transaction logs but also reduces the risk of malicious activities. Additionally, the incorporation of Blowfish encryption ensures the confidentiality of log data, providing an extra layer of protection. Even if logs are accessed illicitly, the encryption prevents unauthorized individuals from deciphering sensitive information. Furthermore, the implementation of a smart contract for user registration adds another dimension to security, creating a comprehensive solution to fortify data security on Cloud servers. The proposed approach offers a promising solution to the critical cybersecurity challenge faced by cloud servers. By combining the security features of PoS and Blowfish encryption, along with the strategic use of smart contracts, the solution not only deters tampering but also safeguards sensitive information. This holistic approach contributes significantly to reinforcing the data security infrastructure of cloud servers in the face of evolving cyber threats.
Michalis Pingos, Panayiotis Christodoulou, Andreas S. Andreou
Data meshes are an approach to data architecture and organization that treats data as a product and focuses on decentralizing data ownership and access. It has recently emerged as a field that presents quite a few challenges related to data ownership, governance, security, monitoring, and observability. To address these challenges, this paper introduces an innovative algorithmic framework leveraging data blueprints to enable the dynamic creation of data meshes and data products in response to user requests, ensuring that stakeholders have access to specific portions of the data mesh as needed. Ownership and governance concerns are addressed through a unique mechanism involving Blockchain and Non-Fungible Tokens (NFTs). This facilitates the secure and transparent transfer of data ownership, with the ability to mint time-based NFTs. By combining these advancements with the fundamental tenets of data meshes, this research offers a comprehensive solution to the challenges surrounding data ownership and governance. It empowers stakeholders to navigate the complexities of data management within a decentralized architecture, ensuring a secure, efficient, and user-centric approach to data utilization. The proposed framework is demonstrated using real-world data from a poultry meat production factory.
In decentralized finance (DeFi), stablecoins like DAI are designed to offer a stable value amidst the fluctuating nature of cryptocurrencies. We examine the class of crypto-backed stable derivatives, focusing on mechanisms for price stabilization and exemplified by the well-known stablecoin DAI from MakerDAO. For simplicity, we consider a single-collateral setting. We introduce a belief parameter to the simulation model of DAI in a previous work (DAISIM), reflecting market sentiments about the value and stability of DAI, and show that it better matches the expected behavior when this parameter is set within a particular range of values. Our methods include comparing simulated data with real-world data, focusing on monthly correlations between ETH and DAI prices and scatter plots illustrating the relationship of their price trends over time. We also propose a simple mathematical model of DAI price to explain its stability and dependency on ETH price. Finally, we analyze possible risk factors associated with these stable derivatives to provide valuable insights for stakeholders in the DeFi ecosystem.
블록체인에 대한 관심이 많아지고, 이더리움의 사용량이 증가함에 따라 블록체인 상태 데이터는 폭발적으로 증가하였는데, 이는 사용자의 네트워크 참여를 어렵게 만들었다. 본 논문에서는 상태 데이터의 상당수를 차지하는 스토리지 트라이를 과거 트랜잭션 데이터를 기반으로 최적화하는 방법을 제안하고자 한다. 본 연구에서는 1,400만 블록의 거대한 스토리지 트라이 중에서 100만 블록동안 한 번도 등장하지 않은 스토리지 트라이를 삭제하여 19.6%인 10.8GB의 저장공간을 줄였다. 본 논문의 연구 결과인 데이터 기반 스토리지 트라이 최적화를 기반으로 더욱 효과적인 스토리지 트라이 최적화를 제안할 수 있을 것으로 기대한다.