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arXiv 2025年

作者： D’Acunto, Gabriele Zennaro, Fabio Massimo Felekis, Yorgos Di Lorenzo, Paolo Department of Information Engineering Electronics and Telecommunications Sapienza University Rome Italy Department of Informatics University of Bergen Bergen Norway Department of Computer Science University of Warwick Coventry United Kingdom

Structural causal models (SCMs) allow us to investigate complex systems at multiple levels of resolution. The causal abstraction (CA) framework formalizes the mapping between high- and low-level SCMs. We address CA learning in a challenging and realistic setting, where SCMs are inaccessible, interventional data is unavailable, and sample data is misaligned. A key principle of our framework is semantic embedding, formalized as the high-level distribution lying on a subspace of the low-level one. This principle naturally links linear CA to the geometry of the Stiefel manifold. We present a category-theoretic approach to SCMs that enables the learning of a CA by finding a morphism between the low- and high-level probability measures, adhering to the semantic embedding principle. Consequently, we formulate a general CA learning problem. As an application, we solve the latter problem for linear CA;considering Gaussian measures and the Kullback-Leibler divergence as an objective. Given the nonconvexity of the learning task, we develop three algorithms building upon existing paradigms for Riemannian optimization. We demonstrate that the proposed methods succeed on both synthetic and real-world brain data with different degrees of prior information about the structure of CA. Copyright © 2025, The Authors. All rights reserved.

关键词： Embeddings

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Designing Quantum-Safe Lattice-Based Multi-Authority CP-ABE Scheme for Blockchain-Enabled IoT-Based Consumer Healthcare Electronics

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IEEE Transactions on Consumer Electronics 2025年

作者： Bagchi, Prithwi Bisht, Abhishek Das, Ashok Kumar Saxena, Neetesh Hossain, M. Shamim International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Department of Computer Science and Engineering College of Informatics Korea University 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of Cardiff University School of Computer Science and Informatics CardiffCF24 4AG United Kingdom King Saud University College of Computer and Information Sciences Department of Software Engineering Riyadh13273 Saudi Arabia

Despite edge computing reducing communication delays associated with cloud computing, privacy concerns remain a significant challenge when sharing data from edge-based consumer electronics (CE) or Internet-of-Things (IoT) devices. Ciphertext policy attribute-based encryption (CP-ABE) is a cryptographic tool that facilitates intricate and refined access control. It can deliver more flexible, secure, compact, and effective access control policies for the cloud data. In the case of a conventional CP-ABE scheme, the keys can only be issued and disseminated by a trusted central authority (CA). However, if the CA is compromised, the entire system becomes more susceptible to assaults or failures, which leads to a single-point failure. In this article, we propose a Ring-Learning with Errors (Ring-LWE)-based MA-CP-ABE scheme that is effectively resolved by the multi-authority CP-ABE (MA-CP-ABE), and it ensures the security against quantum attacks. The threshold secret sharing by Shamir and the Lagrange interpolation formula are applied in the key-generation and decryption procedures of the proposed scheme, which make it easier to segment and restore the private keys. The proposed scheme is implemented in the CE-enabled IoT-based smart healthcare applications using the blockchain technology as a secure storage. A detailed comparative study, security analysis and experimental results with the existing relevant schemes shows that the proposed scheme exhibits superior security and better efficiency as compared to other schemes, demonstrating its feasibility in practical IoT-based healthcare applications. © 2025 IEEE.

关键词： Quantum cryptography

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Generative AI in Academic Writing: A Comparison of DeepSeek, Qwen, ChatGPT, Gemini, Llama, Mistral, and Gemma

arXiv

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arXiv 2025年

作者： Aydın, Ömer Karaarslan, Enis Erenay, Fatih Safa Džakula, Nebojša Bačanin Manisa Celal Bayar University Faculty of Engineering and Natural Sciences Department of Computer Sciences Manisa Turkey University of Waterloo Faculty of Engineering Management Science and Engineering Ontario Canada Mugla Sitki Kocman University Faculty of Engineering Department of Computer Engineering Mugla Turkey Singidunum University Faculty of Informatics and Computing Belgrade Serbia

Deepseek and Qwen LLMs became popular at the beginning of 2025 with their low-cost and open-access LLM solutions. A company based in Hangzhou, Zhejiang, China, announced its new LLM, DeepSeek v3, in December 2024. Then, Alibaba released its AI model, Qwen 2.5 Max, on January 29, 2025. These tools, which are free and open-source have made a significant impact on the world. Deepseek and Qwen also have the potential to be used by many researchers and individuals around the world in academic writing and content creation. Therefore, it is important to determine the capacity of these new LLMs to generate high-quality academic content. This study aims to evaluate the academic writing performance of both Qwen 2.5 Max and DeepSeek v3 by comparing these models with popular systems such as ChatGPT, Gemini, Llama, Mistral, and Gemma. In this research, 40 articles on the topics of Digital Twin and Healthcare were used. The method of this study involves using generative AI tools to generate texts based on posed questions and paraphrased abstracts of these 40 articles. Then, the generated texts were evaluated through the plagiarism tool, AI detection tools, word count comparisons, semantic similarity tools and readability assessments. It was observed that plagiarism test result rates were generally higher for the paraphrased abstract texts and lower for the answers generated to the questions, but both were above acceptable levels. In the evaluations made with the AI detection tool, it was determined with high accuracy that all the generated texts were detected as AI-generated. In terms of the generated word count comparison, it was evaluated that all chatbots generated satisfactory amount of content. Semantic similarity tests show that the generated texts have high semantic overlap with the original texts. The readability tests indicated that the generated texts were not sufficiently readable. © 2025, CC BY.

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Design oligoporous-core based multimode fiber for mode division multiplexing applications

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Optical and Quantum Electronics 2025年第5期57卷 1-24页

作者： Mitu, Sumaiya Akhtar Abdulrazak, Lway Faisal Ibrahim, Sobhy M. Tahhan, Shaymaa R. Hossain, Md Bellal Ahmed, Kawsar Bui, Francis M. Chen, Li Department of Computer Science and Engineering University of Asia Pacific Dhaka Bangladesh Department of Information and Communication Technology Group of Bio-photomatiχ Mawlana Bhashani Science and Technology University Santosh Tangail Bangladesh Department of Computer Science Cihan University Sulaimaniya Sulaimaniya Kurdistan Region Iraq Department of Biochemistry College of Science King Saud University Riyadh Saudi Arabia Department of Laser and Optoelectronics Engineering College of Engineering Al-Nahrain University Jadriya Baghdad Iraq School of Electrical and Information Engineering The University of Sydney Sydney Australia Department of Electrical and Computer Engineering University of Saskatchewan Saskatoon Canada Health Informatics Research Lab Department of Computer Science and Engineering Daffodil International University Daffodil Smart City Birulia Dhaka Bangladesh

A polarization-maintaining oligoporous-core-based multi-mode fiber is proposed. By tuning the air hole, as well as the core number, shape, size, and position up to 28 distinct linearly polarized (LP) modes are obtained. The Finite Element Method (FEM) is used to perform the numerical investigations. In addition, various materials combinations are used as a doping with silica which is highly helpful to increase or decrease the refractive index of the core material. The multimode fiber is identified by the normalized frequency or V parameter. Besides, the high birefringence value, low loss value, minimum crosstalk with high sensitivity response of $$1.46\times {10}^{-2}$$ , $$2\times {10}^{-11}$$ dB/m, 41.80 dB and 88,280.46 nm/RIU, respectively, are achieved from the numerical investigations over the wavelength range from 1.55 µm to1.65 µm for the different LP modes. Moreover, good responses also obtain for the numerical aperture, V number, coupling length and other parameters. In the end, every value reveals both an easy-to-fabricate structure design as well as adequate performance analysis. The suggested fiber structure can support many modes and might be applicable in the field of optical communications and spatial multiplexing based on the user demand.

关键词： Fiber to the x

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Parameterized Saga of First-Fit and Last-Fit Coloring 42

Parameterized Saga of First-Fit and Last-Fit Coloring

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42nd International Symposium on Theoretical Aspects of computer Science, STACS 2025

作者： Agrawal, Akanksha Lokshtanov, Daniel Panolan, Fahad Saurabh, Saket Verma, Shaily Indian Institute of Technology Madras India University of California Santa BarbaraCA United States School of Computer Science University of Leeds United Kingdom The Institute of Mathematical Sciences HBNI Chennai India Department of Informatics University of Bergen Norway Algorithm Engineering Group Hasso Plattner Institute Potsdam Germany

ISBN: (纸本)9783959773652

The classic greedy coloring algorithm considers the vertices of an input graph G in a given order and assigns the first available color to each vertex v in G. In the Grundy Coloring problem, the task is to find an ordering of the vertices that will force the greedy algorithm to use as many colors as possible. In the Partial Grundy Coloring, the task is also to color the graph using as many colors as possible. This time, however, we may select both the ordering in which the vertices are considered and which color to assign the vertex. The only constraint is that the color assigned to a vertex v is a color previously used for another vertex if such a color is available. Whether Grundy Coloring and Partial Grundy Coloring admit fixed-parameter tractable (FPT) algorithms, algorithms with running time f(k)nO(1), where k is the number of colors, was posed as an open problem by Zaker and by Effantin et al., respectively. Recently, Aboulker et al. (STACS 2020 and Algorithmica 2022) resolved the question for Grundy Coloring in the negative by showing that the problem is W[1]-hard. For Partial Grundy Coloring, they obtain an FPT algorithm on graphs that do not contain Ki,j as a subgraph (a.k.a. Ki,j-free graphs). Aboulker et al. re-iterate the question of whether there exists an FPT algorithm for Partial Grundy Coloring on general graphs and also asks whether Grundy Coloring admits an FPT algorithm on Ki,j-free graphs. We give FPT algorithms for Partial Grundy Coloring on general graphs and for Grundy Coloring on Ki,j-free graphs, resolving both the questions in the affirmative. We believe that our new structural theorems for partial Grundy coloring and "representative-family" like sets for Ki,j-free graphs that we use in obtaining our results may have wider algorithmic applications. © Akanksha Agrawal, Daniel Lokshtanov, Fahad Panolan, Saket Saurabh, and Shaily Verma.

关键词： Graph algorithms

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Imitation Game for Adversarial Disillusion with Multimodal Generative Chain-of-Thought Role-Play

arXiv

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arXiv 2025年

作者： Chang, Ching-Chun Chen, Fan-Yun Gu, Shih-Hong Gao, Kai Wang, Hanrui Echizen, Isao Information and Society Research Division National Institute of Informatics Tokyo Japan Department of Information Engineering and Computer Science Feng Chia University Taichung Taiwan

As the cornerstone of artificial intelligence, machine perception confronts a fundamental threat posed by adversarial illusions. These adversarial attacks manifest in two primary forms: deductive illusion, where specific stimuli are crafted based on the victim model’s general decision logic, and inductive illusion, where the victim model’s general decision logic is shaped by specific stimuli. The former exploits the model’s decision boundaries to create a stimulus that, when applied, interferes with its decision-making process. The latter reinforces a conditioned reflex in the model, embedding a backdoor during its learning phase that, when triggered by a stimulus, causes aberrant behaviours. The multifaceted nature of adversarial illusions calls for a unified defence framework, addressing vulnerabilities across various forms of attack. In this study, we propose a disillusion paradigm based on the concept of an imitation game. At the heart of the imitation game lies a multimodal generative agent, steered by chain-of-thought reasoning, which observes, internalises and reconstructs the semantic essence of a sample, liberated from the classic pursuit of reversing the sample to its original state. As a proof of concept, we conduct experimental simulations using a multimodal generative dialogue agent and evaluates the methodology under a variety of attack scenarios. © 2025, CC BY.

关键词： Adversarial machine learning

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Special Issue Editorial: Deterministic, Reliable, Resilient, and Programmable Networks for 6G

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IEEE Network 2025年第3期39卷 72-74页

作者： Papagianni, Chrysa Cavalcanti, Dave Verdi, Fabio Luciano Chieng, David Bernardos, Carlos J. Informatics Institute University of Amsterdam Amsterdam 1012 WX Netherlands Intel Corporation Hillsboro 97124 OR United States Universidade Federal de São Carlos Computer Science Department São Carlos 13565-905 Brazil University of Nottingham Ningbo China Department of Electrical and Electronic Engineering Ningbo 315100 China Universidad Carlos III de Madrid Telematics Department Madrid 28911 Spain

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AI-Powered Behaviour Analysis in Financial Services

AI-Powered Behaviour Analysis in Financial Services

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Data Science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： R. Thalapathi Rajasekaran Muthu Selvam Department of Computer Science and Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu India College of Computing and Informatics University of North Carolina at Charlotte Charlotte North Carolina USA

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

This research investigates the application of state-of-the-art machine learning strategies, including deep learning, clustering, and reinforcement learning, to better understand user behavior in the banking sector. This strategy enriches personalisation, boosts customer engagement, and enhances operational efficiencies. Advanced neural network designs, including Recurrent Neural Networks (RNNs) and transformer architectures, are deployed to interpret transactional and communicative data. Various clustering methods, such as K-Means, DBSCAN, and Hierarchical Clustering, are utilised to classify users by their behavioral characteristics. Moreover, techniques like Deep Q-learning and multi-agent reinforcement learning are employed to adapt dynamically to user actions, thereby maximizing satisfaction. The research further highlights essential ethical issues concerning bias minimization, privacy protection, and the interpretability of models, ensuring the ethical deployment of machine learning practices. Through empirical validation, the suggested framework shows notable improvements in predicting defaults, refining marketing approaches, and increasing adoption rates. These findings underscore the revolutionary influence of machine learning in profiling user behavior, hinting at future developments in federated learning and quantum computing.

关键词： Industries Deep learning Ethics Adaptation models Q-learning Recurrent neural networks Computational modeling Refining Banking Transformers

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Structural Properties of Non-Linear Cellular Automata: Permutivity, Surjectivity and Reversibility

arXiv

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arXiv 2025年

作者： Ramdhane, Firas Ben Dennunzio, Alberto Margara, Luciano Menara, Giuliamaria Department of Informatics Systems and Communications University of Milano-Bicocca Italy Department of Computer Science and Engineering University of Bologna Cesena Italy University of Sfax Faculty of Sciences of Sfax Tunisia

This paper explores the algebraic conditions under which a cellular automaton with a non-linear local rule exhibits surjectivity and reversibility. We also analyze the role of permutivity as a key factor influencing these properties and provide conditions that determine whether a non-linear CA is (bi)permutive. Through theoretical results and illustrative examples, we characterize the relationships between these fundamental properties, offering new insights into the dynamical behavior of non-linear CA. Copyright © 2025, The Authors. All rights reserved.

关键词： Linear algebra

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Enhancing User Interaction in Digital Financial Systems Using AI-Driven Front-End Technologies: A Personalised Response Approach

Enhancing User Interaction in Digital Financial Systems Usin...

引用

Data Science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

This study highlights the rapid advancements in artificial intelligence (AI) and machine learning (ML), which have transformed the financial sector by enhancing personalised user interactions and customer engagement. An innovative AI-driven framework was proposed to deliver real-time, context-aware, and highly personalised responses for Digital Banking users. The system architecture employs advanced ML models, natural language processing (NLP) techniques, and modern front-end technologies such as React and GraphQL to address the challenges related to data silos, computational demand, and data privacy. ML models such as user segmentation, recommendation, and NLP models work together to analyse user behaviour, predict needs, and generate human-like responses. Utilising React, GraphQL subscriptions, and Edge AI, the front-end layer ensures a seamless and responsive user experience. The experimental results showed a 120% increase in click-through rates, a 180% increase in follow-up actions, and a 70% reduction in average response time, demonstrating significant improvements in user engagement. User satisfaction, measured by the Net Promoter Score, was significantly higher for the personalised system (8.5) than for the traditional system (5.2). The proposed methodology lays the foundation for an agile trust-based financial environment. Future enhancements will focus on explainable AI, multimodal interactions, and blockchain integration to boost transparency, engagement, and data privacy.

关键词： Data privacy Analytical models Computational modeling Systems architecture Banking Predictive models Natural language processing Real-time systems User experience Time factors

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