Information Sciences最新文献

{"title":"Concept learning for algorithmic reasoning: Insights from SAT-solving GNNs","authors":"Elad Shoham ,&nbsp;Hadar Cohen ,&nbsp;Khalil Wattad ,&nbsp;Havana Rika ,&nbsp;Dan Vilenchik","doi":"10.1016/j.ins.2025.122754","DOIUrl":"10.1016/j.ins.2025.122754","url":null,"abstract":"<div><div>Explainable AI and model transparency methods primarily focus on classification tasks, identifying salient input features or abstract concepts that are directly tied to the data. In contrast, algorithmic problems such as SAT solving present a deeper challenge: here, meaningful concepts depend not only on the input but also on the model’s evolving internal state; hence, such settings remain underexplored. We study concept learning in an existing model named <span>NeuroSAT</span>, a Graph Neural Network (GNN) trained to predict satisfiability, and uncover internal algorithmic structures, most notably the notion of <em>support</em>, that align with classical SAT heuristics. We then construct a significantly simplified GNN trained via a teacher–student approach: instead of learning from SAT/UNSAT labels, the student is trained to mimic <span>NeuroSAT</span>’s latent representations—i.e., the concepts themselves—and achieves comparable performance using 91 % fewer parameters. For this simplified architecture, we provide a rigorous theoretical analysis that demonstrates, under certain assumptions on the input distribution and network weights, the emergence of the concept of support and its governing role in the network’s dynamics. This work bridges explainability and algorithmic reasoning by showing that classical SAT-solving strategies emerge naturally in GNNs—and can be used to simplify, compress, and formally analyze their internal dynamics.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"726 ","pages":"Article 122754"},"PeriodicalIF":6.8,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Parametrically perturbed logistic map - a new approach based on the least significant bits in the state variable’s representation","authors":"Madhu Sharma","doi":"10.1016/j.ins.2025.122737","DOIUrl":"10.1016/j.ins.2025.122737","url":null,"abstract":"<div><div>Cryptography involves controlled randomization and de-randomization of digital data. In the essential cryptographic infrastructure, the role of Pseudo Random Number Generators (PRNGs) becomes significant. The present work focuses on a new method of implementing PRNGs using chaotic maps. Using this approach, the classical chaotic maps, which otherwise are found to be cryptographically inadequate, can be enhanced to meet the necessary statistical requirements. In this new approach, one of the parameters of a chaotic map can be varied using the lower bits of the floating-point representation of the map’s state variable. This methodology is demonstrated using one of the most commonly discussed chaotic maps - the logistic map. The modified logistic map is shown to have excellent chaotic characteristics across the entire range of the only remaining parameter - the map’s initial state. The resulting chaotic map is named ’Parametrically Perturbed Logistic Map (PPLM)’. The PPLM is used to implement a new Pseudo Random Bit Generator (PRBG) - the PPLM-PRBG. An extensive set of simulations is carried out on the PPLM-PRBG. Using a standard set of parametric studies, including the ’NIST test suite’, the new PRBG is found to have excellent statistical and cryptographic properties.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"725 ","pages":"Article 122737"},"PeriodicalIF":6.8,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bi-coalitions analysis in the rough sets conflict model","authors":"Rafał Deja ,&nbsp;Małgorzata Przybyła-Kasperek","doi":"10.1016/j.ins.2025.122746","DOIUrl":"10.1016/j.ins.2025.122746","url":null,"abstract":"<div><div>This paper introduces a novel framework for conflict analysis based on rough set theory, extending Pawlak’s classical model. We introduce the concept of bi-coalitions, defined as groups of agents that fully agree on a subset of issues. Unlike traditional alliance relations, bi-coalitions are constructed without reliance on numerical thresholds, enabling a crisp and interpretable representation of consensus. The paper proposes an algorithm for identifying bi-coalitions using an indiscernibility matrix. To quantify coalition coherence, we introduce two strength measures with optional weighting of issues to reflect domain-specific relevance. Furthermore, we develop a negotiation algorithm guiding the system toward consensus or stable partitions. The proposed model is empirically validated on two real-world conflict scenarios: the 2023 parliamentary elections in Poland and the Middle East geopolitical situation. These case studies demonstrate the model’s ability to uncover interpretable coalition structures and support dynamic consensus-building.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"725 ","pages":"Article 122746"},"PeriodicalIF":6.8,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mitigating malware prevalence in networks with arbitrary topologies: a Flip-It cyber game approach integrated with epidemic modeling","authors":"Mousa Tayseer Jafar ,&nbsp;Lu-Xing Yang ,&nbsp;Gang Li ,&nbsp;Robin Doss ,&nbsp;Kon Mouzakis ,&nbsp;Rajesh Vasa ,&nbsp;Helge Janicke ,&nbsp;Ahmed Ibrahim ,&nbsp;Ahmed Mohsin ,&nbsp;Iqbal H. Sarker ,&nbsp;Kristen Moore ,&nbsp;Seyit Camtepe ,&nbsp;Diksha Goel","doi":"10.1016/j.ins.2025.122753","DOIUrl":"10.1016/j.ins.2025.122753","url":null,"abstract":"<div><div>Cyber threats have evolved in complexity, aiming at a wide range of sectors using advanced methods and tools. This evolving threat landscape challenges existing cybersecurity frameworks, many of which lack the adaptability to counteract the complex tactics of sophisticated adversaries. Developing robust cyber defense strategies requires simulating dynamic interactions between attackers and defenders across high, moderate, and low-impact scenarios. The Flip-It cyber game serves as an intelligent framework for simulating these interactions, enabling the analysis of adaptive strategies in cybersecurity. This paper aims to address the problem of mitigating malware prevalence with full consideration of attack/defense capabilities in arbitrary network topologies. This paper proposes a sophisticated discrete-time epidemic model to characterize security state transitions over time for all three scenarios within the Flip-It game framework. On this basis, the original problem is modeled as a closed-loop control problem to seek the optimal containment strategy. Deep Reinforcement Learning (DRL) is then used to tackle the problem, generating efficient defense strategies that are well-adapted to changing cybersecurity environments.</div><div>Numerical simulations based on small-world networks, scale-free networks, and router networks are then carried out to generate corresponding strategies. Additionally, we have evaluated the performance of the proposed method against the State-Of-The-Art (SOTA) in terms of attack/defense objective function, control actions, number of devices under the control of the attacker and defender, stability, execution time, and scalability. This comprehensive approach integrates epidemiological modeling, game theory, and advanced machine learning to effectively tackle the complexities of contemporary cybersecurity threats.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"726 ","pages":"Article 122753"},"PeriodicalIF":6.8,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Four new ordered weighted averaging weights generators for regular increasingly monotonic functions","authors":"LeSheng Jin ,&nbsp;Yi Yang ,&nbsp;Zhen-Song Chen","doi":"10.1016/j.ins.2025.122751","DOIUrl":"10.1016/j.ins.2025.122751","url":null,"abstract":"<div><div>Diverse normalized weight vectors for OWA aggregation can be generated using regular increasing monotonic functions, embodying bipolar optimism–pessimism preferences. Yager’s original approach has been utilized for over three decades. This work, from different perspectives, proposes and analyzes four approaches to generate weight vectors with regularly increasing monotonic functions. We systematically formulate and analyze Yager’s original method and formally define it as a generator. Furthermore, we propose and analyze four distinct generators with different features and characteristics. The first two possess attenuation properties compared to Yager’s generator. The third one offers a significant advantage of full consistency in orness, and the fourth one provides a consistent cognitive mode for the regularly increasing monotonic functions that coincide almost everywhere.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"725 ","pages":"Article 122751"},"PeriodicalIF":6.8,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed output-feedback optimization for uncertain nonlinear multi-agent systems with unknown input delay","authors":"Liujie Du ,&nbsp;Ping Li ,&nbsp;Zhibao Song ,&nbsp;Zhen Wang ,&nbsp;Wenhui Liu","doi":"10.1016/j.ins.2025.122744","DOIUrl":"10.1016/j.ins.2025.122744","url":null,"abstract":"<div><div>This paper presents distributed output-feedback optimization for uncertain high-order nonlinear multi-agent systems (MASs) subject to unknown input delay. First, appropriate auxiliary systems and Lyapunov-Krasovskii functional (LKF) are implemented to counteract the effects of unknown input delay. In addition, to address the challenges posed by nonlinear uncertainties and unmeasurable system states, a neural networks (NNs)-based state observer employing radial basis function (RBF) NNs has been developed. Subsequently, distributed optimal coordinators (DOCs) are employed to reformulate output consensus as tracking problem for MASs. In the context of actor-critic reinforcement learning (RL) architecture, distributed optimal controller is designed using RL algorithm combined with backstepping technique. Leveraging Lyapunov stability theory, it is rigorously demonstrated that the tracking error of the output relative to the optimal solution can be reduced to an arbitrarily small magnitude. Finally, simulation examples are conducted to validate the efficacy of the introduced algorithm.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"725 ","pages":"Article 122744"},"PeriodicalIF":6.8,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145270811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel seasonal grey Euler model with three parameter-interval grey numbers for forecasting power generation","authors":"Feifei Huang ,&nbsp;Xiangyan Zeng ,&nbsp;Shuli Yan","doi":"10.1016/j.ins.2025.122738","DOIUrl":"10.1016/j.ins.2025.122738","url":null,"abstract":"<div><div>Accurate forecasting of power generation helps to assess the stability of the supply of power generation and to better plan the use of electrical energy. China’s power generation exhibits seasonal oscillations, nonlinear growth, and uncertain fluctuations. The interval numbers can reflect the range of uncertainty fluctuations in the data. Therefore, the three-parameter interval grey numbers prediction of China’s power generation is studied. A matrixed Fourier grey Euler Bernoulli model MFGEBM(1,1) for three-parameter interval grey numbers is proposed. First, a seasonal factor is introduced into a new Caputo fractional accumulation generation operator to reduce the seasonal volatility of the sequence. Secondly, the Fourier series and Bernoulli’s equation are introduced into the grey Euler model to further improve the applicability to sequences with seasonal oscillations. Then, based on a new convergence factor and triangular walking strategy, the grey wolf algorithm is improved to optimize the model’s parameters, and its effectiveness is verified with algorithm comparison experiments. In order to test the accuracy of the model proposed in this paper, two cases with different development trends and related to power are studied, and four existing grey models for seasonal oscillation sequences are used as competing models. Finally, the proposed model is used to forecast China ’s power generation.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"726 ","pages":"Article 122738"},"PeriodicalIF":6.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-triggered secure bipartite formation for MASs against byzantine attacks: A distributed unknown input observer approach","authors":"Younan Zhao ,&nbsp;Fanglai Zhu ,&nbsp;Xufeng Ling","doi":"10.1016/j.ins.2025.122752","DOIUrl":"10.1016/j.ins.2025.122752","url":null,"abstract":"<div><div>The present paper studies the self-triggered secure bipartite formation for MASs against Byzantine adversaries, where an asymptotic stabilization control protocol is designed. Compared with the existing work, a more practical situation is considered where the state of each subsystem is unmeasurable and the system output is transmitted to its neighbor agents instead of the state. First of all, a distributed bipartite formation variable (DBFV) is introduced and the bipartite formation control objective turns out to be a convergence problem of the DBFV. Then, the dynamic system of the DBFV is set up where a multiple disturbance (MD) is involved. Next, the algebraic relation between the MD and the DBFV is defined, based on which a distributed unknown input observer (DUIO) is designed such that the asymptotic convergence estimates of the DBFV and the MD are obtained. Further, a DUIO-based controller is established to realize the asymptotic stabilization of the DBFV dynamic system. Finally, a Byzantine detection and defense strategy is designed based on the self-triggered mechanism with discontinuous updates of the communication topology, where nonsmooth dynamics theory is introduced into the stability analysis of the DBFV system. The proposed strategy and controller are validated by a simulation example.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"726 ","pages":"Article 122752"},"PeriodicalIF":6.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-granularity spectral graph coarsening","authors":"Jinyuan Ni ,&nbsp;Long Chen ,&nbsp;Ning Yu","doi":"10.1016/j.ins.2025.122748","DOIUrl":"10.1016/j.ins.2025.122748","url":null,"abstract":"<div><div>Graph coarsening is the process of simplifying large-scale graph representations while preserving essential structural characteristics to improve computational efficiency in graph processing. Conventional techniques primarily reduce graph size through node and edge merging but often inadequately preserve both global spectral properties and local structural details. Real-world graphs exhibit inherent hierarchical complexity comprising critical global topological patterns and local structural features necessary for accurate analysis. To address these limitations, we present a Multi-Granularity Spectral Graph Coarsening (MGSGC) framework that systematically integrates spectral graph analysis with local structural preservation through multi-granularity operations. Our approach initiates with hierarchical graph decomposition, where node merging generates structurally homogeneous subgraphs. Spectral analysis of normalized Laplacian matrices guides iterative coarsening optimization, using spectral distance metrics to identify subgraphs requiring refinement. A dual-resolution mechanism preserves global spectral signatures and local connectivity patterns simultaneously, ensuring retention of both macroscopic and microscopic structural information. Comprehensive experiments across multiple benchmark datasets demonstrate that MGSGC outperforms recent methods, achieving higher accuracy, superior structural preservation, and strong resilience to label noise, ensuring robust performance in real-world scenarios. Code is available at <span><span>https://anonymous.4open.science/r/MGSGC/</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"726 ","pages":"Article 122748"},"PeriodicalIF":6.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145247909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Behavioral pattern clustering for thematic user segmentation in web interaction environments","authors":"Suma Srinath,&nbsp;Nagaraju Baydeti","doi":"10.1016/j.ins.2025.122745","DOIUrl":"10.1016/j.ins.2025.122745","url":null,"abstract":"<div><div>Clustering users based on their interest is a critical component in personalized content delivery. This paper proposes a novel multi modal framework that integrates semantic video classification, contextualized caption generation, and user behavior patterns. The system combines visual and audio features which are computed using convolutional and transformer based encoders to robustly capture the complex contents of video description. User browsing profile is modelled using probabilistic distributions to reflect realistic browsing behavior across six interest categories. These profiles are then clustered using KMeans, DBSCAN, and Agglomerative clustering to identify the various user groups. The quality of clustering is evaluated using Silhouttee Score, Davies-Bouldin Index, and Calinski-Harabasz Index, with PCA and t-SNE applied for visual validation of coherence of clusters. The simulation framework addresses the issues concerning data privacy and the scarcity of real world data by producing controllable and realistic user behavior traces. Experimental results demonstrate that KMeans provides the optimal trade-off between quality of clustering solution and computational cost. These integrated efforts bring personalized content delivery to a new perspective, i.e., fine-grained user segmentation and precise video understanding, respectively. The future work will focus on adopting real-time adaptive learning and integrating with more data types, and will further deploy on large-scale multimedia applications.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"724 ","pages":"Article 122745"},"PeriodicalIF":6.8,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}