Computer Law & Security Review最新文献_第8页

Digital borders and beyond: Establishing normative grounds for cybersecurity and sovereignty in international law 数字边界及其以外：在国际法中建立网络安全和主权的规范基础

IF 3.2 3区社会学 Q1 LAW

Computer Law & Security Review

Pub Date : 2025-08-12 DOI: 10.1016/j.clsr.2025.106180

Kasim Balarabe

In the rapidly evolving digital age, the confluence of cybersecurity threats and the assertion of digital sovereignty by states has created a complex, multi-dimensional challenge for international law. The existing legal regimes governing state behavior in cyberspace are fragmented, outdated, and ill-equipped to address the novel, intangible, and interconnected nature of the digital domain. This article examines the gaps and limitations in the current international legal frameworks and proposes a dynamic, adaptable approach to establishing a normative foundation for cybersecurity and digital sovereignty. The article highlights the urgent need for clear definitions and categories of cybercrimes and cyberwarfare under international law, as well as the development of appropriate legal responses and enforcement mechanisms. It also explores the tensions between state sovereignty and global Internet governance, proposing a balanced framework that upholds both the legitimate security interests of states and the fundamental principles of human rights, transparency, and multistakeholder collaboration. Central to the article's argument is the call for a flexible, evolutionary architecture of international cybersecurity law, capable of keeping pace with rapid technological advancements and the ever-changing threat landscape. This framework should incorporate mechanisms for continuous improvement, effective attribution and accountability, and the active engagement of international organizations and multistakeholder initiatives. The article further emphasizes the critical role of geopolitical challenges in shaping the development of international cybersecurity norms. It advocates for a nuanced, pragmatic approach that acknowledges the competing interests and values of different state actors while striving to find common ground and build trust through dialogue and cooperation. In an era of increasing digital interconnectedness and the erosion of traditional borders, this article presents a compelling case for the adaptation of international law to address the complex realities of the digital age. It offers valuable insights and recommendations for policymakers, legal experts, and scholars seeking to navigate the uncharted territories of cybersecurity and digital sovereignty in the 21st century.

在快速发展的数字时代，网络安全威胁和国家对数字主权的主张交织在一起，给国际法带来了复杂的、多方面的挑战。管理网络空间国家行为的现有法律制度支离破碎、过时，无法应对数字领域的新颖性、无形性和互联性。本文考察了当前国际法律框架中的差距和局限性，并提出了一种动态的、适应性强的方法来建立网络安全和数字主权的规范基础。文章强调，迫切需要在国际法下明确网络犯罪和网络战的定义和类别，以及制定适当的法律回应和执法机制。它还探讨了国家主权与全球互联网治理之间的紧张关系，提出了一个平衡的框架，既维护国家的合法安全利益，又维护人权、透明度和多利益攸关方合作的基本原则。文章的核心论点是呼吁建立一个灵活、渐进的国际网络安全法律架构，能够跟上快速的技术进步和不断变化的威胁形势。这一框架应包括持续改进、有效归因和问责机制，以及国际组织和多利益攸关方倡议的积极参与。文章进一步强调了地缘政治挑战在塑造国际网络安全规范发展中的关键作用。它主张采取细致、务实的方式，承认不同国家行为体相互竞争的利益和价值观，同时努力通过对话与合作找到共同点，建立信任。在一个数字互联性日益增强、传统边界受到侵蚀的时代，本文提出了一个令人信服的案例，即修改国际法以应对数字时代的复杂现实。它为决策者、法律专家和学者在21世纪探索网络安全和数字主权的未知领域提供了宝贵的见解和建议。

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引用次数: 0

Towards semi-automating European legislative harmonisation analysis: A harmonised glossary for LLM-based legal concept detection 迈向半自动化的欧洲立法协调分析：基于法学硕士的法律概念检测的协调词汇表

IF 3.2 3区社会学 Q1 LAW

Computer Law & Security Review

Pub Date : 2025-08-02 DOI: 10.1016/j.clsr.2025.106171

Davide Audrito , Ivan Spada , Rachele Mignone, Emilio Sulis, Luigi Di Caro

Achieving legislative harmonisation within the European Union (EU) is a multifaceted challenge, hampered by various political, economic, and legal complexities. This article addresses the significant issue of non-compliance by EU member states in transposing EU laws into national frameworks, underscored by numerous infringement procedures. This work introduces a novel methodological framework that combines semantic knowledge modelling and transformer-based language models to address discrepancies in legislative harmonisation. Central to the proposed methodology is the creation of a comprehensive glossary designed to establish correspondences between European legislative concepts and their national counterparts, thus facilitating greater accuracy in legal harmonisation. By deploying Large Language Models (LLMs) for semi-automating concept detection, complemented by legal harmonisation expert’s oversight, this research provides an exhaustive, explainable assessment of legislative approximation within the EU. The findings enrich the academic debate on legal harmonisation offering actionable tools designed to decrease the frequency and gravity of infringement procedures, while promoting a more unified and efficient legal framework across the Union. The complete dataset and resources are available at the following link: GitHub repository.

在欧盟（EU）内部实现立法协调是一项多方面的挑战，受到各种政治、经济和法律复杂性的阻碍。本文解决了欧盟成员国在将欧盟法律转化为国家框架方面不合规的重大问题，强调了许多侵权程序。这项工作引入了一种新的方法框架，该框架结合了语义知识建模和基于转换器的语言模型，以解决立法协调中的差异。拟议方法的核心是创建一个全面的词汇表，旨在建立欧洲立法概念与其国家对应概念之间的对应关系，从而促进法律协调的更大准确性。通过部署用于半自动化概念检测的大型语言模型（llm），辅以法律协调专家的监督，本研究提供了对欧盟立法近似的详尽，可解释的评估。研究结果丰富了关于法律协调的学术辩论，提供了可操作的工具，旨在减少侵权程序的频率和严重性，同时促进整个联盟更统一和有效的法律框架。完整的数据集和资源可从以下链接获得：GitHub存储库。

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引用次数: 0

A game changer or jurisdictional arbitrage? De-risking global capital markets amid cross-border data governance resilience 游戏规则改变者还是管辖权套利？在跨境数据治理弹性背景下，降低全球资本市场风险

IF 3.2 3区社会学 Q1 LAW

Computer Law & Security Review

Pub Date : 2025-08-01 DOI: 10.1016/j.clsr.2025.106175

Dr Qingxiu Bu (Fellow)

The rivalry between the U.S. and China remains intense, driven by their competition for technological dominance and geopolitical influence. Both powers are escalating efforts to secure data, aiming to strengthen domestic control and expand international reach. This creates significant challenges for companies like DiDi and TikTok, which must navigate an increasingly polarised and complex environment. DiDi's delisting from the U.S. underscores how big data has become a critical battleground in this rivalry, with far-reaching implications for the global economy. The ongoing TikTok controversy goes beyond security concerns, framing China’s technological advancement as a direct challenge to U.S. dominance in shaping global discourse and public opinion. This confrontation raises crucial questions: Is the focus on accounting oversight, or do deeper conflicts over sovereignty and ideology drive the tension? Does controlling data flow represent a game changer or merely a tool for regulatory arbitrage? From a game theory perspective, addressing this challenge requires a delicate balance—regulating tech giants, safeguarding data security, and sustaining economic growth.

由于两国在技术主导地位和地缘政治影响力方面的竞争，美国和中国之间的竞争仍然很激烈。这两个大国都在加大保护数据的力度，旨在加强国内控制，扩大国际影响力。这给滴滴和抖音等公司带来了重大挑战，它们必须应对日益两极分化和复杂的环境。滴滴从美国退市凸显出，大数据已成为这场竞争的关键战场，并对全球经济产生深远影响。正在进行的TikTok争议超越了安全问题，将中国的技术进步视为对美国在塑造全球话语和公众舆论方面的主导地位的直接挑战。这种对抗提出了一个关键问题：是对会计监管的关注，还是对主权和意识形态的更深层次的冲突导致了这种紧张关系？控制数据流是改变游戏规则还是仅仅是监管套利的工具？从博弈论的角度来看，应对这一挑战需要一个微妙的平衡——监管科技巨头、保护数据安全和维持经济增长。

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引用次数: 0

LLMs for legal reasoning: A unified framework and future perspectives 法学硕士的法律推理：一个统一的框架和未来的前景

IF 3.2 3区社会学 Q1 LAW

Computer Law & Security Review

Pub Date : 2025-07-30 DOI: 10.1016/j.clsr.2025.106165

Ha Thanh Nguyen , Wachara Fungwacharakorn , May Myo Zin , Randy Goebel , Francesca Toni , Kostas Stathis , Ken Satoh

Large Language Models (LLMs) have recently demonstrated remarkable ease of application to numerous natural language processing tasks, however the question of how well they perform is in serious question. In the case of their use in application domains where precision and accuracy are paramount (e.g., law, medicine), the assessment of their performance is erratic. In particular, the application of these models to legal reasoning presents both unique challenges and substantial opportunities because of the inherently complex and multi-faceted nature of legal decision-making. To begin to harness the potential of LLMs in legal reasoning, we propose a framework for unified legal reasoning that combines rule-based, abductive, and case-based approaches, and then investigate possible methods for their integration with LLMs. The ultimate goal, which we take steps toward, is to provide comprehensive, accurate, and adaptable legal decision analysis.

We critically examine this combination of reasoning methods, their formalizations, and their relevance to the legal domain, including the consideration of calibration methods to assess their performance. Moreover, we discuss current research and challenges in applying LLMs to legal reasoning tasks, highlight the importance of reconciling different reasoning paradigms, analyze cultural notions of justice, and address issues of uncertainty, vagueness, and ambiguity. Our study offers insights into the benefits and complexities of integrating LLMs within a proposed unified reasoning framework, with the hope of addressing some of the diverse legal challenges, and to advance the capabilities of AI-driven legal analysis.

大型语言模型（llm）最近在许多自然语言处理任务中表现出了非凡的易用性，然而，它们的表现如何是一个严重的问题。在精度和准确性至关重要的应用领域（例如，法律，医学）中使用它们的情况下，对它们的性能的评估是不稳定的。特别是，由于法律决策固有的复杂性和多面性，这些模型在法律推理中的应用既提出了独特的挑战，也带来了大量的机会。为了开始利用法学硕士在法律推理中的潜力，我们提出了一个统一的法律推理框架，该框架结合了基于规则的、溯因的和基于案例的方法，然后研究将它们与法学硕士集成的可能方法。我们采取措施的最终目标是提供全面、准确和适应性强的法律决策分析。我们严格检查推理方法的组合，它们的形式化，以及它们与法律领域的相关性，包括考虑校准方法来评估它们的性能。此外，我们还讨论了将法学硕士应用于法律推理任务的当前研究和挑战，强调了调和不同推理范式的重要性，分析了正义的文化概念，并解决了不确定性，模糊性和模糊性的问题。我们的研究提供了将法学硕士整合到拟议的统一推理框架中的好处和复杂性的见解，希望解决一些不同的法律挑战，并提高人工智能驱动的法律分析的能力。

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引用次数: 0

Enhancing charge prediction through the collaboration of large and small models 通过大型和小型模型的协作增强电荷预测

IF 3.2 3区社会学 Q1 LAW

Computer Law & Security Review

Pub Date : 2025-07-29 DOI: 10.1016/j.clsr.2025.106168

Bin Wei , Yaoyao Yu , Jiawen Zhang , Yiquan Wu

Charge prediction is a fundamental task in AI&Law, where the goal is to predict charges based on fact descriptions. Although various methods have been introduced to enhance performance, challenges remain. Specifically, small models (SMs)-based methods such as BERT struggle with hard cases involving low-frequency or confusing charges due to their limited capacity, whereas large language models (LLMs)-based approaches like GPT-4 exhibit difficulties in handling diverse charges owing to insufficient legal knowledge. To overcome these limitations, we propose a hybrid framework that collaborates both large and small models to improve charge prediction performance, based on the idea that combining the strengths of each can overcome their limitations. Initially, SMs provide an initial prediction along with a predicted probability distribution. If the maximum predicted probability falls below a threshold, LLMs step in to reflect and re-predict as needed. Additionally, we construct a confusing charges dictionary and design a two-stage legal inference prompt, which helps LLMs make the secondary prediction for the hard cases. Extensive experiments on two datasets from China and Italy demonstrate the effectiveness of this approach, yielding average F1 improvements of 7.94% and 11.46% respectively. Moreover, a fine-grained analysis demonstrates that our proposed framework is effective in identifying low-frequency and confusing charges.

电荷预测是人工智能法中的一项基本任务，其目标是根据事实描述预测电荷。尽管已经引入了各种方法来提高性能，但挑战仍然存在。具体来说，基于小模型（SMs）的方法，如BERT，由于其有限的容量，难以处理涉及低频或混淆收费的疑难案件，而基于大型语言模型（LLMs）的方法，如GPT-4，由于缺乏法律知识，在处理各种收费方面表现出困难。为了克服这些限制，我们提出了一个混合框架，结合大型和小型模型来提高电荷预测性能，基于结合每个模型的优势可以克服它们的局限性的想法。最初，SMs提供了一个初始预测以及预测的概率分布。如果最大预测概率低于阈值，llm会介入以反映并根据需要重新预测。此外，我们构建了一个混淆收费词典，并设计了一个两阶段的法律推理提示，这有助于法学硕士对困难案例进行二次预测。在中国和意大利的两个数据集上进行的大量实验证明了该方法的有效性，平均F1分别提高了7.94%和11.46%。此外，细粒度分析表明，我们提出的框架是有效的识别低频和混淆收费。

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引用次数: 0

Personal data controllers and device producers: Mind the gap 个人数据控制者和设备生产商：注意差距

IF 3.3 3区社会学 Q1 LAW

Computer Law & Security Review

Pub Date : 2025-07-25 DOI: 10.1016/j.clsr.2025.106172

Efstratios Koulierakis

It seemed well established that producing a smart device could not, by itself, render someone a personal data controller in the absence of subsequent influence over the processing operations (the influence thesis). In contrast, legal scholars have introduced a new interpretation of European data protection law that seeks to apply the General Data Protection Regulation (GDPR) to the processing operations of smart devices even if no entity influences the processing remotely after the release of the product. This approach classifies producers as personal data controllers for device-based processing (producer-controller thesis). The proponents of the producer-controller thesis highlight the increasing importance of smart devices that store data locally and the need for protecting consumers’ rights in that context. However, as this paper claims, the GDPR is not the proper legal instrument for addressing the safety standards of smart products that process data locally. These considerations relate to legislative texts that prescribe product requirements, such as the AI Act and the Cyber Resilience Act. On those grounds, the present work criticises the producer-controller thesis. As this paper concludes, expanding the concept of ‘controller’ to encompass producers of smart devices does not enhance the protection of the data subjects and does not fit within the current data protection framework of the European Union.

似乎已经确定的是，在没有对处理操作产生后续影响的情况下，生产智能设备本身不能使某人成为个人数据控制者（影响论点）。相比之下，法律学者对欧洲数据保护法提出了一种新的解释，试图将《通用数据保护条例》（GDPR）适用于智能设备的处理操作，即使产品发布后没有实体远程影响处理。这种方法将生产者分类为基于设备的处理的个人数据控制器（生产者-控制器论文）。生产者-控制者理论的支持者强调了在本地存储数据的智能设备的日益重要性，以及在这种情况下保护消费者权利的必要性。然而，正如本文所述，GDPR并不是解决本地处理数据的智能产品安全标准的适当法律工具。这些考虑与规定产品要求的立法文本有关，例如《人工智能法案》和《网络弹性法案》。基于这些理由，本文对生产者-控制者理论提出了批评。正如本文所总结的那样，将“控制者”的概念扩展到智能设备的生产者并不能增强对数据主体的保护，也不适合欧盟当前的数据保护框架。

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引用次数: 0

A Comparative review of Symbolism and Connectionism in AI&Law: Tracing evolution and exploring integration 《人工智能与法律》中的象征主义与联结主义比较：追溯演变，探索融合

IF 3.3 3区社会学 Q1 LAW

Computer Law & Security Review

Pub Date : 2025-07-24 DOI: 10.1016/j.clsr.2025.106166

Bin Wei

AI&Law explores computational methods for automating legal reasoning and prediction, evolving in parallel with AI research and developing along two primary paths: symbolic and connectionist approaches. Symbolic AI&Law centers on the formal representation of legal concepts and performing reasoning based on statutes and case law. These methods have led to the development of rule-based and case-based reasoning systems, successfully implemented in legal expert systems. The primary advantage of symbolic approaches is their inherent explainability, although they face limitations due to the knowledge acquisition bottleneck. Connectionist AI&Law encourages legal professionals to adopt inductive inference and use “bottom-up” learning models to extract hidden features from large datasets. This paradigm incorporates machine learning and natural language processing (NLP) techniques to address legal information extraction, retrieval, text classification, summarization, and legal prediction tasks. The advent of large language models (LLMs) has further expanded the capabilities of connectionist models, enabling more sophisticated legal text analysis and predictive accuracy, though issues of model transparency and hallucination remain active areas of research. The interaction between symbolic and connectionist approaches can complement each other. Symbolic models can enhance the transparency and explainability of connectionist systems, while connectionist techniques can optimize the scalability and efficiency of symbolic reasoning processes. These two paradigms exhibit strong potential for collaboration, particularly in the domains of explainable dialogue systems, neuro-symbolic systems, legal knowledge embedding and legal argumentation mining, etc.

AI Law探索自动化法律推理和预测的计算方法，与AI研究并行发展，并沿着两条主要路径发展：符号和连接主义方法。符号法以法律概念的形式表现和基于成文法和判例法的推理为中心。这些方法导致了基于规则和基于案例的推理系统的发展，并成功地在法律专家系统中实施。符号方法的主要优点是其固有的可解释性，尽管它们面临着知识获取瓶颈的限制。Connectionist ai Law鼓励法律专业人士采用归纳推理，并使用“自下而上”的学习模型从大型数据集中提取隐藏特征。该范式结合了机器学习和自然语言处理（NLP）技术来解决法律信息提取、检索、文本分类、摘要和法律预测任务。大型语言模型（llm）的出现进一步扩展了连接主义模型的能力，使更复杂的法律文本分析和预测准确性成为可能，尽管模型透明度和幻觉问题仍然是研究的活跃领域。符号主义和联结主义研究方法之间的相互作用可以相互补充。符号模型可以增强连接主义系统的透明性和可解释性，而连接主义技术可以优化符号推理过程的可扩展性和效率。这两种范式在可解释对话系统、神经符号系统、法律知识嵌入和法律论证挖掘等领域表现出强大的合作潜力。

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引用次数: 0

The algorithmic muse and the public domain: Why copyright’s legal philosophy precludes protection for generative AI outputs 算法缪斯和公共领域：为什么版权的法律哲学排除了对生成人工智能输出的保护

IF 3.3 3区社会学 Q1 LAW

Computer Law & Security Review

Pub Date : 2025-07-22 DOI: 10.1016/j.clsr.2025.106170

Ezieddin Elmahjub

Generative AI (GenAI) outputs are not copyrightable. This article argues why. We bypass conventional doctrinal analysis that focuses on black letter law notions of originality and authorship to re-evaluate copyright's foundational philosophy. GenAI fundamentally severs the direct human creative link to expressive form. Traditional theories utilitarian incentive, labor desert and personality fail to provide coherent justification for protection. The public domain constitutes the default baseline for intellectual creations. Those seeking copyright coverage for GenAI outputs bear the burden of proof. Granting copyright to raw GenAI outputs would not only be philosophically unsound but would also trigger an unprecedented enclosure of the digital commons, creating a legal quagmire and stifling future innovation. The paper advocates for a clear distinction: human creative contributions to AI-generated works may warrant protection, but the raw algorithmic output should remain in the public domain.

生成AI （GenAI）输出不受版权保护。这篇文章探讨了其中的原因。我们绕过传统的理论分析，重点放在黑体字法的原创性和作者的概念，重新评估版权的基本哲学。GenAI从根本上切断了人类创造性与表达形式的直接联系。传统的功利主义激励理论、劳动报酬理论和人格理论未能为保护提供连贯的理由。公共领域构成了智力创造的默认基线。那些为GenAI的产出寻求版权保护的人承担举证责任。将GenAI的原始成果授予版权不仅在哲学上是不合理的，而且还会引发对数字公地前所未有的封闭，造成法律困境，扼杀未来的创新。这篇论文主张明确区分：人类对人工智能作品的创造性贡献可能需要保护，但原始算法输出应留在公共领域。

引用次数: 0

A systematic literature review on dark patterns for the legal community: definitional clarity-and a legal classification based on the Unfair Commercial Practices Directive 法律界对黑暗模式的系统文献回顾：定义的清晰度-以及基于不公平商业惯例指令的法律分类

IF 3.3 3区社会学 Q1 LAW

Computer Law & Security Review

Pub Date : 2025-07-21 DOI: 10.1016/j.clsr.2025.106169

Cecilia Isola , Fabrizio Esposito

This article offers a clear definition of dark patterns and a comprehensive classification thereof using the framework provided by Directive 2005/29 on unfair commercial practices. The analysis builds on a systematic literature review that analyses how dark patterns are defined and the types of dark patterns discussed in 116 articles, conference papers and regulatory documents. Accordingly, 'dark pattern' can be defined as 'the design of a digital choice environment that is capable of distorting user behaviour'. We point out that the following elements should not be included in the definition of dark pattern: intentionality of the designer and exploitation of heuristics or cognitive bias. We identify 42 types of dark patterns. All of them can be classified as: misleading omission; misleading action; harassment; undue influence; coercion. This classification is based on legal categories and helps bridge the gap between research and legal practice, thereby increasing the expected social impact of research on dark patterns.

这篇文章提供了一个明确的黑暗模式的定义，并使用指令2005/29关于不公平的商业行为提供的框架进行了全面的分类。该分析基于系统的文献综述，分析了黑暗模式的定义，以及116篇文章、会议论文和监管文件中讨论的黑暗模式的类型。因此，“暗模式”可以定义为“能够扭曲用户行为的数字选择环境的设计”。我们指出，以下因素不应包括在暗模式的定义中：设计者的意向性和启发式或认知偏见的利用。我们确定了42种黑色图案。所有这些都可以归类为：误导性遗漏；误导行动;骚扰;不正当影响;强制转换。这种分类以法律类别为基础，有助于弥合研究与法律实践之间的差距，从而增加对黑暗模式研究的预期社会影响。

引用次数: 0

Exploring the use of LLMs in the Italian legal domain: A survey on recent applications 探索法学硕士在意大利法律领域的使用：对最近的应用调查

IF 3.3 3区社会学 Q1 LAW

Computer Law & Security Review

Pub Date : 2025-07-10 DOI: 10.1016/j.clsr.2025.106164

Marco Siino

This article delves into recent applications of Transformers (also, Large Language Models or LLMs) in the context of the Italian legal language. The impressive speed at which the literature in this domain has recently grown (i.e., in 2022 and 2023) is proved by the number of related works that we collected in this study. The focus of this work is on exploring how LLMs are being utilized within the framework of Italian law. In detail, we first introduce the tasks that have been addressed in the Italian legal domain. When introducing the tasks, to motivate and to provide the most relevant works, we reference worldwide literature. After introducing the tasks, we report and discuss all the existent applications to these tasks, specifically in the Italian legal domain. Through this work, we intend to deliver the state of the art in LLM applications in the Italian legal domain to researchers as well as practising attorneys.

本文深入研究了transformer（也称为大型语言模型或llm）在意大利法律语言上下文中的最新应用。我们在本研究中收集的相关作品的数量证明了该领域的文献最近（即2022年和2023年）增长的惊人速度。这项工作的重点是探索法学硕士如何在意大利法律的框架内被利用。详细地说，我们首先介绍在意大利法律领域所处理的任务。在介绍任务时，为了激励和提供最相关的作品，我们参考了世界各地的文献。在介绍了这些任务之后，我们报告并讨论了这些任务的所有现有申请，特别是在意大利法律领域。通过这项工作，我们打算为研究人员和执业律师提供意大利法律领域法学硕士应用的最新技术。

引用次数: 0