Computer Standards & Interfaces最新文献_第3页

A secure reversible image hiding approach combining block based intelligence with dual stego matrix encoding 一种基于分块智能和双隐进矩阵编码相结合的安全可逆图像隐藏方法

IF 3.1 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Standards & Interfaces

Pub Date : 2026-04-01 Epub Date: 2026-01-19 DOI: 10.1016/j.csi.2026.104131

Minakshi Sarkar , Kankana Datta , Bidesh Chakraborty , Indrajit Banerjee

With the rapid growth of communication technologies, securing private data during transmission over public networks has become a significant challenge. Traditional data hiding methods, such as modifying the least significant bits (LSBs) of image pixels, often lead to visible distortion, especially when embedding large amounts of data. To address this issue, we propose a novel image steganography method that combines AES encryption, a Fine Tuning Transformer (FTT) classifier, and LSB embedding integrated with a Binary Lower Triangular Matrix (BLTM) for secure data hiding. In the proposed approach, the secret image is first encrypted using AES to ensure data confidentiality. The FTT classifier then predicts three block labels that determine the amount of data to be embedded in each block. Using the BLTM concept along with LSB substitution, the encrypted data is embedded into both cover images. Finally, to further enhance security, the two stego images are encrypted using a master key. Experimental results show that the proposed scheme provides high imperceptibility. Even at the maximum embedding rate of 0.93 bpp, the PSNR values remain above 56 dB, while the Mean Square Error (MSE) is low and the Structural Similarity Index (SSIM) stays above 0.97. The proposed dual-image steganographic framework advances secure multimedia communication by supporting image authentication, tamper detection, and forgery prevention benefiting domains such as healthcare, defense, and digital rights protection. It also offers adaptive payload allocation and strong robustness against noise, salt-and-pepper, opaque masking, and grid occlusion attacks, making the system both reliable and attack resilient.

随着通信技术的快速发展，在公共网络上传输私有数据的安全性已成为一个重大挑战。传统的数据隐藏方法，如修改图像像素的最低有效位（LSBs），通常会导致可见的失真，特别是在嵌入大量数据时。为了解决这个问题，我们提出了一种新的图像隐写方法，该方法结合了AES加密、微调变压器（FTT）分类器和集成了二进制下三角矩阵（BLTM）的LSB嵌入，以实现安全的数据隐藏。在该方法中，首先使用AES对秘密图像进行加密，以确保数据的机密性。然后，FTT分类器预测三个块标签，这些块标签确定要嵌入每个块中的数据量。使用BLTM概念和LSB替换，加密的数据被嵌入到两个封面图像中。最后，为了进一步提高安全性，使用主密钥对两个隐写图像进行加密。实验结果表明，该方案具有较高的隐蔽性。即使在最大嵌入率为0.93 bpp时，PSNR值仍保持在56 dB以上，均方误差（MSE）较低，结构相似指数（SSIM）保持在0.97以上。提出的双图像隐写框架通过支持图像认证、篡改检测和伪造预防，提高了安全的多媒体通信，有利于医疗保健、国防和数字版权保护等领域。它还提供自适应有效载荷分配和强大的抗噪声、盐和胡椒、不透明掩蔽和网格遮挡攻击的鲁棒性，使系统既可靠又具有抗攻击能力。

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引用次数: 0

Graph-based interpretable dialogue sentiment analysis: A HybridBERT-LSTM framework with semantic interaction explainer 基于图的可解释对话情感分析：一个带有语义交互解释器的HybridBERT-LSTM框架

IF 3.1 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Standards & Interfaces

Pub Date : 2026-04-01 Epub Date: 2025-11-12 DOI: 10.1016/j.csi.2025.104086

Ercan Atagün , Günay Temür , Serdar Bi̇roğul

Conversational sentiment analysis in natural language processing faces substantial challenges due to intricate contextual semantics and temporal dependencies within multi-turn dialogues. We present a novel HybridBERT-LSTM architecture that integrates BERT’s contextualized embeddings with LSTM’s sequential processing capabilities to enhance sentiment classification performance in dialogue scenarios. Our framework employs a dual-pooling mechanism to capture local semantic features and global discourse dependencies, addressing limitations of conventional approaches. Comprehensive evaluation on IMDb benchmark and real-world dialogue datasets demonstrates that HybridBERT-LSTM consistently improves over standalone models (LSTM, BERT, CNN, SVM) across accuracy, precision, recall, and F1-score metrics. The architecture effectively exploits pre-trained contextual representations through bidirectional LSTM layers for temporal discourse modeling. We introduce WordContextGraphExplainer, a graph-theoretic interpretability framework addressing conventional explanation method limitations. Unlike LIME’s linear additivity assumptions treating features independently, our approach utilizes perturbation-based analysis to model non-linear semantic interactions. The framework generates semantic interaction graphs with nodes representing word contributions and edges encoding inter-word dependencies, visualizing contextual sentiment propagation patterns. Empirical analysis reveals LIME’s inadequacies in capturing temporal discourse dependencies and collaborative semantic interactions crucial for dialogue sentiment understanding. WordContextGraphExplainer explicitly models semantic interdependencies, negation scope, and temporal flow across conversational turns, enabling comprehensive understanding of both word-level contributions and contextual interaction influences on decision-making processes. This integrated framework establishes a new paradigm for interpretable dialogue sentiment analysis, advancing trustworthy AI through high-performance classification coupled with comprehensive explainability.

由于多回合对话中复杂的语境语义和时间依赖性，自然语言处理中的会话情感分析面临着巨大的挑战。我们提出了一种新的HybridBERT-LSTM架构，它将BERT的上下文嵌入与LSTM的顺序处理能力相结合，以增强对话场景中的情感分类性能。我们的框架采用双池机制来捕获局部语义特征和全局话语依赖，解决了传统方法的局限性。对IMDb基准和真实世界对话数据集的综合评估表明，HybridBERT-LSTM在准确性、精密度、召回率和f1分数指标上持续优于独立模型（LSTM、BERT、CNN、SVM）。该体系结构通过双向LSTM层有效地利用预训练的上下文表示进行时间话语建模。我们介绍了WordContextGraphExplainer，这是一个图论可解释性框架，解决了传统解释方法的局限性。与LIME的线性可加性假设独立处理特征不同，我们的方法利用基于微扰的分析来模拟非线性语义交互。该框架生成语义交互图，节点表示词贡献，边编码词间依赖关系，可视化上下文情感传播模式。实证分析表明，LIME在捕捉对对话情感理解至关重要的时间话语依赖和协作语义交互方面存在不足。WordContextGraphExplainer明确地对语义相互依赖、否定范围和跨会话回合的时间流进行建模，从而能够全面理解单词级别的贡献和上下文交互对决策过程的影响。这个集成框架为可解释的对话情感分析建立了一个新的范式，通过高性能分类和全面的可解释性来推进可信赖的人工智能。

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引用次数: 0

V-Bridge: A dynamic cross-shard blockchain protocol based on off-chain payment channel V-Bridge：基于链下支付通道的动态跨分片区块链协议

IF 3.1 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Standards & Interfaces

Pub Date : 2026-04-01 Epub Date: 2025-12-31 DOI: 10.1016/j.csi.2025.104123

Xueting Huang , Xiangwei Meng , Kai Zhang , Ce Yang , Wei Liang , Kuan-Ching Li

Sharding technology effectively improves system throughput by distributing the blockchain transaction load to multiple shards for parallel processing, and it is the core solution to the scalability problem of blockchain. However, as the number of shards increases, the frequency of cross-shard transactions increases significantly, leading to increased communication and computational overhead, transaction delays, uneven resource allocation, and load imbalance, which becomes a key bottleneck for performance expansion. To this end, this article proposes the cross-shard transaction protocol V-Bridge, which draws on the concept of off-chain payment channels to establish distributed virtual fund channels between Trustors in different shards, convert cross-shard transactions into off-chain transactions and realize the logical flow of funds. To further enhance cross-shard transaction performance, our V-Bridge integrates an intelligent sharding adjustment mechanism, and a cross-shard optimized critical path protection algorithm (CSOCPPA) to dynamically balance shard loads, alleviate resource allocation issues, and minimize performance bottlenecks. Experimental results show that compared with existing state-of-the-art protocols, our proposed V-Bridge’s average throughput is increased by 26% to 46%, and transaction delays are reduced by 15% to 24%.

分片技术通过将区块链事务负载分配给多个分片并行处理，有效提高了系统吞吐量，是解决区块链可扩展性问题的核心方案。但是，随着分片数量的增加，跨分片事务的频率显著增加，导致通信和计算开销增加，事务延迟，资源分配不均匀，负载不平衡，成为性能扩展的关键瓶颈。为此，本文提出了跨分片交易协议V-Bridge，该协议利用链下支付通道的概念，在不同分片的受托人之间建立分布式虚拟资金通道，将跨分片交易转化为链下交易，实现资金的逻辑流动。为了进一步提升跨分片的事务性能，我们的V-Bridge集成了智能分片调整机制和跨分片优化关键路径保护算法（CSOCPPA），以动态平衡分片负载，缓解资源分配问题，最大限度地减少性能瓶颈。实验结果表明，与现有最先进的协议相比，我们提出的V-Bridge的平均吞吐量提高了26%至46%，事务延迟降低了15%至24%。

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引用次数: 0

A multi-criteria process for IT project success evaluation–Addressing a critical gap in standard practices IT项目成功评估的多标准流程——解决标准实践中的关键差距

IF 3.1 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Standards & Interfaces

Pub Date : 2026-04-01 Epub Date: 2025-12-24 DOI: 10.1016/j.csi.2025.104122

João Carlos Lourenço , João Varajão

The evaluation of project success is widely recognised as valuable for improving IT (Information Technology) project performance and impact. However, many processes fail to adequately address the requirements for a sound evaluation due to their inherent complexity or by not complying with fundamental practical and theoretical concepts. This paper presents a process that combines a problem structuring method with a multi-criteria decision analysis approach to evaluate the success of IT projects. Put into practice in the context of a software development project developed for a leading global supplier of technology and services, it offers a new way of creating a model for evaluating project success and tackling uncertainty, bringing clarity and consistency to the overall assessment process. A strong advantage of this process is that it is theoretically sound and can be easily applied to other evaluation problems involving other criteria. It also serves as a call to action for the development of formal standards in evaluation processes. Practical pathways to achieve such standardization include collaboration through industry consortia, development and adoption of ISO frameworks, and embedding evaluation processes within established maturity models. These pathways can foster consistency, comparability, and continuous improvement across organizations, paving the way for more robust and transparent evaluation practices.

项目成功的评估被广泛认为对提高IT（信息技术）项目的绩效和影响有价值。然而，由于其固有的复杂性或不符合基本的实践和理论概念，许多过程未能充分解决对健全评价的要求。本文提出了一个将问题结构化方法与多准则决策分析方法相结合的过程，以评估IT项目的成功。在为全球领先的技术和服务供应商开发的软件开发项目的背景下付诸实践，它提供了一种创建评估项目成功和处理不确定性的模型的新方法，为整个评估过程带来了清晰度和一致性。这个过程的一个强大的优点是，它在理论上是可靠的，可以很容易地应用于涉及其他标准的其他评价问题。它还呼吁采取行动，制定评价过程中的正式标准。实现这种标准化的实际途径包括通过行业联盟进行协作，开发和采用ISO框架，以及在已建立的成熟度模型中嵌入评估过程。这些途径可以促进组织间的一致性、可比性和持续改进，为更健壮和透明的评估实践铺平道路。

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引用次数: 0

Assessing the quantum readiness of cryptographic standards: Recommendations toward quantum-era compliance 评估加密标准的量子就绪性：对量子时代遵从性的建议

IF 3.1 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Standards & Interfaces

Pub Date : 2026-04-01 Epub Date: 2025-12-17 DOI: 10.1016/j.csi.2025.104114

Vikas Chouhan , Mohammed Aldarwbi , Somayeh Sadeghi , Ali Ghorbani , Aaron Chow , Robby Burko

Cryptography is fundamental to securing digital data and communications, yet established algorithms face increasing risk from emerging quantum capabilities. With the progression of quantum computing, the urgency for cryptographic standards that remain secure in both classical and quantum settings has intensified, governed not only by cryptanalytic risk but also by compliance, interoperability, and country-specific regulatory frameworks. This paper presents a structured evaluation framework that depicts the hierarchy of cryptographic standards, encompassing block ciphers, stream ciphers, hash and MAC functions, key establishment mechanisms, digital signatures, lightweight cryptography, entity authentication, public key infrastructure, and authentication and communication protocols. We define a standards-to-protocol recommendation flow that propagates compliant guidance across layers, from foundational primitives to PKI/authentication and hybridization, and extends to country-specific recommendations and protocols. Our contributions include explicit decision criteria for assessing cryptographic primitives under classical and quantum threat models, yielding both immediate and alternative deployment recommendations aligned with NIST-compliant guidelines. We further analyze hybrid schemes to ensure backward compatibility and secure integration, quantifying storage and network overheads for signatures, encryption, and key exchange to identify practical engineering trade-offs. Consolidated results are presented in reference tables detailing standardization year, purpose, notes, and migration recommendations for both classical and post-quantum contexts. Additionally, we examine the security strength of cryptographic primitives that are currently classically secure or quantum-resistant. This framework offers a reproducible, extensible path toward quantum-ready cryptographic systems.

密码学是确保数字数据和通信安全的基础，但现有算法面临着新兴量子能力带来的越来越大的风险。随着量子计算的发展，在经典和量子环境中保持安全的密码标准的紧迫性已经加剧，不仅受密码分析风险的制约，还受合规性、互操作性和国家特定监管框架的制约。本文提出了一个结构化的评估框架，描述了加密标准的层次结构，包括分组密码、流密码、哈希和MAC功能、密钥建立机制、数字签名、轻量级加密、实体认证、公钥基础设施以及认证和通信协议。我们定义了一个从标准到协议的推荐流程，该流程跨层传播合规指导，从基础原语到PKI/身份验证和杂交，并扩展到特定国家的建议和协议。我们的贡献包括在经典和量子威胁模型下评估加密原语的明确决策标准，生成与nist兼容的指导方针一致的即时和替代部署建议。我们进一步分析混合方案以确保向后兼容性和安全集成，量化签名、加密和密钥交换的存储和网络开销，以确定实际的工程权衡。综合结果在参考表中给出，详细介绍了标准化年份、目的、注释和经典和后量子上下文的迁移建议。此外，我们还研究了目前经典安全或抗量子的加密原语的安全强度。这个框架为量子就绪的加密系统提供了一个可复制的、可扩展的路径。

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引用次数: 0

How AI agents transform reflective practices: A three-semester comparative study in socially shared regulation of learning 人工智能代理如何转变反思实践：社会共享学习规则的三个学期比较研究

IF 3.1 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Standards & Interfaces

Pub Date : 2026-04-01 Epub Date: 2025-11-11 DOI: 10.1016/j.csi.2025.104094

Yumin Zheng , Fengjiao Tu , Fengfang Shu , Chaowang Shang , Lulu Chen , Jiang Meng

High-quality reflection has been a challenging barrier in the socially shared regulation of learning (SSRL). Especially with the emergence of generative artificial intelligence (GAI), traditional methods such as reflection reports may increase the students' risk of superficial reflection. This study uses an artificial intelligence agent (AI agent) to design a reflection assistant, which aims to enhance students' reflection ability through continuous questioning and real-time, content-specific feedback based on their written reflections. Through a comparative experiment conducted over three semesters, this study demonstrates the different impacts of three reflection methods, reflection reports, reflection short-answer questions, and AI agents, on the quality of university students' reflections. The results indicate that there is a significant difference in the quality of reflection among the three reflection methods. Students using AI agents show the highest levels of reflection, characterized primarily by connective reflection and critical reflection. Epistemic network analysis further reveals that the AI agent reflection method is more effective in improving the reflection quality of low-performance teams than that of high-performance teams. This expands AI agents' use in SSRL reflection, introduces new methods for the GAI era, and provides practical experience and reflection intervention strategies for teachers and instructional designers in SSRL.

高质量的反思一直是社会共享学习调节（SSRL）的一个具有挑战性的障碍。特别是随着生成式人工智能（GAI）的出现，传统的反思报告等方法可能会增加学生肤浅反思的风险。本研究使用人工智能代理（AI agent）设计了一个反思助手，旨在通过持续的提问和基于学生书面反思的实时、具体内容的反馈来增强学生的反思能力。本研究通过三个学期的对比实验，论证了反思报告、反思简答题和人工智能代理三种反思方式对大学生反思质量的不同影响。结果表明，三种反射方法的反射质量存在显著差异。使用人工智能代理的学生表现出最高水平的反思，主要表现为关联反思和批判性反思。认知网络分析进一步揭示了人工智能主体反思方法在提高低绩效团队反思质量方面比高绩效团队反思质量更有效。这拓展了AI agent在SSRL反思中的应用，为GAI时代引入了新的方法，为SSRL教师和教学设计师提供了实践经验和反思干预策略。

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引用次数: 0

Fully decentralized period k-times anonymous authentication with access criteria 具有访问标准的完全分散的k次匿名身份验证

IF 3.1 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Standards & Interfaces

Pub Date : 2026-04-01 Epub Date: 2025-11-19 DOI: 10.1016/j.csi.2025.104097

Hongyan Di , Yinghui Zhang , Ziqi Zhang , Yibo Pang , Rui Guo , Yangguang Tian

The explosive growth of Internet user devices highlights the strong and urgent need for digital identity infrastructure. However, the existing decentralized identity schemes are still not fully decentralized, and there is still a contradiction between publicly auditable credentials and maintaining anonymity. Therefore, using advanced cryptographic techniques such as signature proof of knowledge, Pedersen commitment, and Merkle tree, this paper propose a fully decentralized period k-times anonymous authentication with access criteria. The scheme allows user credentials to be publicly audited, users can manage their identity independently, and the verifier can not only verify the user’s identity, but also implement access control. The issuer does not need to hold a key or maintain a list, and it can still authenticate even after the trusted center is attacked, and only three zero-knowledge proofs are needed for registration and verification. The security analysis indicates that this scheme satisfies unforgeability, anonymity, unlinkability and attribute privacy. Performance evaluation shows significant improvements in both computational and communication efficiency over existing schemes.

互联网用户设备的爆炸式增长凸显了对数字身份基础设施的强烈而迫切的需求。然而，现有的去中心化身份方案仍然没有完全去中心化，公开可审计的凭证和保持匿名之间仍然存在矛盾。因此，本文利用知识签名证明、Pedersen承诺和Merkle树等先进的密码学技术，提出了一种具有访问标准的完全分散的k次匿名身份验证方法。该方案允许对用户凭证进行公开审计，用户可以独立管理自己的身份，验证者不仅可以验证用户的身份，还可以实现访问控制。发行者不需要持有密钥，也不需要维护列表，即使在可信中心受到攻击后，发行者仍然可以进行身份验证，注册和验证只需要三个零知识证明。安全性分析表明，该方案满足不可伪造性、匿名性、不可链接性和属性隐私性。性能评估表明，与现有方案相比，计算效率和通信效率都有显著提高。

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引用次数: 0

Integrating IoT security practices into a risk-based framework for small and medium enterprises (SMEs) 将物联网安全实践整合到中小型企业（SMEs）的基于风险的框架中

IF 3.1 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Standards & Interfaces

Pub Date : 2026-04-01 Epub Date: 2025-11-26 DOI: 10.1016/j.csi.2025.104099

Samer Aoudi, Hussain Al-Aqrabi

The growing integration of Internet of Things (IoT) technologies within Small and Medium Enterprises (SMEs) has introduced new operational efficiencies while simultaneously expanding the cybersecurity threat landscape. However, most SMEs lack the resources, technical expertise, and institutional maturity required to adopt existing security frameworks, which are often designed with large enterprises in mind. This paper proposes a risk-based framework specifically developed to help SMEs identify, assess, and mitigate IoT-related security risks in a structured and scalable manner. The framework integrates key components such as asset classification, STRIDE-based threat modeling, CVSS-driven vulnerability assessment, and dynamic risk prioritization through Bayesian inference. Emphasis is placed on cost-effective mitigation strategies that are feasible within SME resource constraints and aligned with regulatory requirements. The framework was validated through a real-world case study involving a digitally enabled retail SME. Results demonstrate tangible improvements in vulnerability management, security control implementation, and organizational readiness. Additionally, qualitative feedback from stakeholders highlights the framework’s usability, adaptability, and minimal disruption to operations. This research bridges a critical gap in the current literature by contextualizing established cybersecurity methodologies for the SME sector and providing a practical toolset for managing IoT risks. The proposed framework offers SMEs a viable path toward improving cybersecurity resilience in increasingly connected business environments.

物联网（IoT）技术在中小企业（SMEs）中的日益融合，在带来新的运营效率的同时，也扩大了网络安全威胁的范围。然而，大多数中小企业缺乏采用现有安全框架所需的资源、技术专长和制度成熟度，这些框架通常是为大型企业设计的。本文提出了一个基于风险的框架，专门用于帮助中小企业以结构化和可扩展的方式识别、评估和减轻物联网相关的安全风险。该框架集成了资产分类、基于stride的威胁建模、cvss驱动的漏洞评估以及通过贝叶斯推理进行的动态风险优先级排序等关键组件。重点是在中小企业资源限制范围内可行并符合监管要求的具有成本效益的缓解战略。该框架通过涉及数字化零售中小企业的实际案例研究进行了验证。结果显示了在漏洞管理、安全控制实现和组织准备方面的切实改进。此外，来自涉众的定性反馈强调了框架的可用性、适应性和对操作的最小干扰。本研究通过将中小企业部门的既定网络安全方法置于背景中，并提供管理物联网风险的实用工具集，弥合了当前文献中的关键空白。拟议的框架为中小企业在日益互联的商业环境中提高网络安全弹性提供了一条可行的途径。

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引用次数: 0

An autonomous deep reinforcement learning-based approach for memory configuration in serverless computing 无服务器计算中基于自主深度强化学习的内存配置方法

IF 3.1 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Standards & Interfaces

Pub Date : 2026-04-01 Epub Date: 2025-11-19 DOI: 10.1016/j.csi.2025.104098

Zahra Shojaee Rad, Mostafa Ghobaei-Arani, Reza Ahsan

Serverless computing has become very popular in recent years due to its cost savings and flexibility. Serverless computing is a cloud computing model that allows developers to create and deploy code without having to manage the infrastructure. It has been embraced due to its scalability, cost savings, and ease of use. However, memory configuration is one of the important challenges in serverless computing due to the transient nature of serverless functions, which are stateless and ephemeral. In this paper, we propose an autonomous approach using deep reinforcement learning and a reward mechanism for memory configuration called Auto Opt Mem. In the Auto Opt Mem mechanism, the system learns to allocate memory resources to serverless functions in a way that balances overall performance and minimizes wastage of resources. Finally, we validate the effectiveness of our solution, the findings revealed that Auto Opt Mem mechanism enhances resource utilization, reduces operation cost and latency, and improves quality of service (QoS). Our experiments demonstrate that Auto Opt Mem mechanism achieves 16.8 % lower latency compared to static allocation, 11.8 % cost reduction, and 6.8 % improve in QoS, resource utilization, and efficient memory allocation compared with base-line methods.

近年来，无服务器计算由于其节省成本和灵活性而变得非常流行。无服务器计算是一种云计算模型，它允许开发人员创建和部署代码，而无需管理基础设施。它因其可伸缩性、成本节约和易用性而受到欢迎。然而，内存配置是无服务器计算中的重要挑战之一，因为无服务器功能具有瞬时特性，它们是无状态和短暂的。在本文中，我们提出了一种使用深度强化学习和记忆配置奖励机制的自主方法，称为Auto Opt Mem。在Auto Opt内存机制中，系统学习以平衡整体性能和最小化资源浪费的方式将内存资源分配给无服务器功能。最后，我们验证了该方案的有效性，结果表明，自动选择内存机制提高了资源利用率，降低了运行成本和延迟，提高了服务质量（QoS）。我们的实验表明，与静态分配相比，自动选择内存机制的延迟降低了16.8%，成本降低了11.8%，在QoS、资源利用率和有效内存分配方面比基线方法提高了6.8%。

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引用次数: 0

Breaking cross-domain model protection via surrogate-guided unsupervised distribution transformation 通过代理引导的无监督分布转换打破跨域模型保护

IF 3.1 2区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Computer Standards & Interfaces

Pub Date : 2026-04-01 Epub Date: 2026-02-05 DOI: 10.1016/j.csi.2026.104141

Huali Ren , Pengyu Chen , Ziyu Ding , Weitong Chen , Jiachao Li , Chong-zhi Gao

Cross-domain restricted learning has emerged as a promising paradigm for safeguarding deep learning model intellectual property by establishing transferability constraints between authorized and unauthorized domains. Existing restriction-breaking approaches typically require annotated data for model fine-tuning, which not only compromises authorized domain performance but also proves impractical under API-only access scenarios. To address these limitations, we propose SDUT (Surrogate-guided Distribution Transformation), a novel unsupervised method that breaks domain restrictions by transforming unauthorized domain samples into the authorized domain distribution. Specifically, SDUT first acquires input–output data pairs through systematic querying of the restricted API and trains a functionally equivalent local surrogate model using dual-domain optimization. We then construct a distribution transformation network based on Vision Transformer with the surrogate model, combining data-level transformation objectives with individual certainty and global diversity objectives derived from model prediction characteristics. Finally, leveraging neural network transferability, the trained transformation network is applied to restricted model to achieve effective domain restriction breaking. Extensive experiments on standard benchmarks (Digits, CIFAR10, STL10) demonstrate that SDUT achieves 43% performance improvement on unauthorized domains while fully preserving authorized domain performance. Our results expose fundamental weaknesses in existing restriction mechanisms and provide important guidance for enhancing model security frameworks.

通过在授权和未授权领域之间建立可转移性约束，跨领域限制学习已成为保护深度学习模型知识产权的一种有前途的范例。现有的限制打破方法通常需要带注释的数据来进行模型微调，这不仅会损害授权域的性能，而且在仅使用api的访问场景下也被证明是不切实际的。为了解决这些限制，我们提出了SDUT（代理引导分布转换），这是一种新的无监督方法，通过将未经授权的域样本转换为授权的域分布来打破域限制。具体而言，SDUT首先通过对受限API的系统查询获取输入输出数据对，并使用双域优化训练功能等效的局部代理模型。基于Vision Transformer和代理模型，将数据级转换目标与模型预测特征衍生的个体确定性和全局多样性目标相结合，构建了基于Vision Transformer的配电网络。最后，利用神经网络的可转移性，将训练好的变换网络应用于受限模型，实现有效的域约束打破。在标准基准测试（Digits, CIFAR10, STL10）上进行的大量实验表明，在完全保持授权域性能的同时，SDUT在未授权域上实现了43%的性能提升。我们的结果揭示了现有限制机制的基本弱点，并为增强模型安全框架提供了重要的指导。

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引用次数: 0