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A survey of Community Detection algorithms and its comparative performance analysis 社区检测算法综述及其性能比较分析
IF 12.7 1区 计算机科学
Computer Science Review Pub Date : 2025-08-05 DOI: 10.1016/j.cosrev.2025.100799
Dipika Singh , Rakhi Garg
{"title":"A survey of Community Detection algorithms and its comparative performance analysis","authors":"Dipika Singh ,&nbsp;Rakhi Garg","doi":"10.1016/j.cosrev.2025.100799","DOIUrl":"10.1016/j.cosrev.2025.100799","url":null,"abstract":"<div><div>Community Detection is an important area of research. It finds a variety of applications in Social, Biological networks. Many Community Detection algorithms have been proposed over the years. And many surveys have also been conducted on different approaches of Community Detection. But as more and more algorithms have been proposed over the years, a more updated and complete review is required in this area. In this paper we have tried to accumulate important research in the area of Community Detection from the year 2002 to 2024. We have also discussed important algorithms that have been modified and re-implemented by different authors along with its merits and demerits. Moreover, different metrics for the evaluation of Community Detection algorithms and datasets used are also elaborated. This paper will be beneficial for researchers working in this area to get a latest collection of different Community Detection algorithms along with the approaches used in them.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100799"},"PeriodicalIF":12.7,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144773097","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}
引用次数: 0
Revolutionizing textual data insights: A comprehensive review of the dual relationship between transformers and clustering in textual data analysis 革命性的文本数据洞察:文本数据分析中变形和聚类之间的双重关系的全面回顾
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-07-19 DOI: 10.1016/j.cosrev.2025.100792
Nazila Pourhaji Aghayengejeh , M.A. Balafar , Narjes Nikzad Khasmakhi
{"title":"Revolutionizing textual data insights: A comprehensive review of the dual relationship between transformers and clustering in textual data analysis","authors":"Nazila Pourhaji Aghayengejeh ,&nbsp;M.A. Balafar ,&nbsp;Narjes Nikzad Khasmakhi","doi":"10.1016/j.cosrev.2025.100792","DOIUrl":"10.1016/j.cosrev.2025.100792","url":null,"abstract":"<div><div>In recent years, the integration of transformer models and clustering techniques has gained significant attention in the research community. Transformers excel at feature extraction, representation learning, and understanding data, which helps improve the accuracy and efficiency of clustering tasks. Conversely, clustering methods play a critical role in managing data distribution, enhancing interpretability, and improving the training of transformer models. This review looks at the dual relationship between these two domains: how transformers can advance clustering methodologies and how clustering techniques can optimize transformer performance. By examining this interaction, the paper highlights promising directions for future research.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100792"},"PeriodicalIF":13.3,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144662455","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}
引用次数: 0
Maximal cliques summarization: Principles, problem classification, and algorithmic approaches 最大团总结:原理、问题分类和算法方法
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-07-18 DOI: 10.1016/j.cosrev.2025.100784
Marco D’Elia , Irene Finocchi , Maurizio Patrignani
{"title":"Maximal cliques summarization: Principles, problem classification, and algorithmic approaches","authors":"Marco D’Elia ,&nbsp;Irene Finocchi ,&nbsp;Maurizio Patrignani","doi":"10.1016/j.cosrev.2025.100784","DOIUrl":"10.1016/j.cosrev.2025.100784","url":null,"abstract":"<div><div>Several algorithms are available for computing all the maximal cliques of real-world graphs, both in centralized and distributed settings. However, in many application contexts, the sheer number of maximal cliques and their significant overlap call for strategies to reduce their quantity, maintaining only the most “meaningful” ones. In this survey we introduce a novel taxonomic framework that classifies summarization problems along two key dimensions: summarization principles and problem classes. Our framework provides a unified perspective on seemingly unrelated problems, organizing systematically the highly scattered literature on this topic, revealing underlying connections that were not previously well understood, and identifying several open problems in this field.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100784"},"PeriodicalIF":13.3,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144654536","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}
引用次数: 0
A comprehensive review on machine learning-based VPN detection: Scenarios, methods, and open challenges 基于机器学习的VPN检测:场景、方法和开放挑战的综合综述
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-07-17 DOI: 10.1016/j.cosrev.2025.100781
Alejandro Guerra-Manzanares , Maurantonio Caprolu , Roberto Di Pietro
{"title":"A comprehensive review on machine learning-based VPN detection: Scenarios, methods, and open challenges","authors":"Alejandro Guerra-Manzanares ,&nbsp;Maurantonio Caprolu ,&nbsp;Roberto Di Pietro","doi":"10.1016/j.cosrev.2025.100781","DOIUrl":"10.1016/j.cosrev.2025.100781","url":null,"abstract":"<div><div>Virtual Private Networks (VPNs) are an essential tool to protect user privacy and enforce secure communications over the Internet. However, they can also be misused to bypass legit network security mechanisms and hence access otherwise restricted content. These reasons, combined with the fact that VPN supporting technology has continuously evolved—reaching quite a relevant level of sophistication—make detecting VPN traffic a vested research issue for both academia and industry. In this paper, we provide a comprehensive review of machine learning-based (ML) solutions for VPN traffic detection. In particular, we start with framing the problem and identifying the main scenarios and related adversary models. Then, we provide a thorough analysis of the related literature and state-of-the-art in ML methodologies for VPN detection, identifying research gaps and unresolved challenges. In particular, we show that the vast majority of the current solutions rely on a specific dataset that suffers from a few severe limitations, hence questioning the validity of reported results when applied to real use case scenarios. Finally, we summarize existing knowledge highlighting common mistakes and providing guidelines as well as future research directions. To the best of our knowledge, this is the first paper that provides a deep dive into ML methodologies for VPN detection, showing current pitfalls, providing actionable recommendations, as well as suggesting research directions.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100781"},"PeriodicalIF":13.3,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144654535","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}
引用次数: 0
Integration of SDN into UAV, edge computing, & Blockchain: A review, challenges, & future directions SDN与无人机、边缘计算、区块链的融合:回顾、挑战与未来方向
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-07-17 DOI: 10.1016/j.cosrev.2025.100790
Tejas M. Modi , Kuna Venkateswararao , Pravati Swain
{"title":"Integration of SDN into UAV, edge computing, & Blockchain: A review, challenges, & future directions","authors":"Tejas M. Modi ,&nbsp;Kuna Venkateswararao ,&nbsp;Pravati Swain","doi":"10.1016/j.cosrev.2025.100790","DOIUrl":"10.1016/j.cosrev.2025.100790","url":null,"abstract":"<div><div>Software Defined Network(SDN) is an advanced architecture that enhances the centralized access of the network topology through a central controller. Emerging networking mechanisms provide novel advanced architectures that enhance the application usage scenarios. Emerging networking mechanisms, i.e., Edge computing, Unmanned Aerial Vehicle (UAV) systems, and Blockchain, are new techniques that generate various communication models to provide secure and virtual access to the network entities. However, the UAV and edge computing systems cannot handle the high traffic congestion in the network. The system must offload the data computation to other devices in these scenarios. The offloading process requires a central authority to manage task computation and available resources in the system. Thus, SDN can provide a central controller to handle the resources in the UAV and edge computing system.</div><div>Meanwhile, SDN lacks security, and Blockchain needs to manage the trusted third-party entities in the system. For these problems, the SDN and Blockchain provide resilience to each other in architectural advancements. This proposed survey presents state-of-the-art fusion systems where SDN is integrated into emerging networking mechanisms. The main objective is to represent the integration of SDN into UAV, Edge Computing, and Blockchain systems for different domains, i.e., routing, resource management, task offloading, network management, and security. Moreover, the survey represents the various simulation tools and performance parameters of fusion architectures. Furthermore, the survey illustrates challenges, open issues, and future directions in the next generation of networking systems.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100790"},"PeriodicalIF":13.3,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144654469","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}
引用次数: 0
Deep anomaly detection for time series: A survey 时间序列深度异常检测:综述
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-07-11 DOI: 10.1016/j.cosrev.2025.100787
Xudong Jia, Peng Xun, Wei Peng, Baokang Zhao, Haojie Li, Chiran Shen
{"title":"Deep anomaly detection for time series: A survey","authors":"Xudong Jia,&nbsp;Peng Xun,&nbsp;Wei Peng,&nbsp;Baokang Zhao,&nbsp;Haojie Li,&nbsp;Chiran Shen","doi":"10.1016/j.cosrev.2025.100787","DOIUrl":"10.1016/j.cosrev.2025.100787","url":null,"abstract":"<div><div>The cyberspace environment has evolved into a complex ecosystem, generating vast amounts of diverse time series data from various devices, systems, and software. Detecting anomalies in these massive, multi-source datasets is critical for ensuring system reliability and security. This paper provides a comprehensive review of deep learning approaches for time series anomaly detection. We systematically classify existing methods into six categories based on their objective functions: forecasting models, reconstruction models, generative models, density models, contrastive models, and hybrid models. For each category, we analyze their advantages, disadvantages, and architectural variations to guide researchers in selecting appropriate approaches for specific problems. We further summarize applications across multiple domains including network services, cyber–physical systems, smart grids, smart cities, and healthcare, providing valuable insights into practical implementations. The paper also organizes commonly used public datasets with their key characteristics and examines evaluation metrics ranging from traditional point-level assessments to advanced sequence-adaptive frameworks. Finally, we discuss emerging challenges and promising research directions, including data augmentation strategies, model robustness improvements, generalization capabilities, applications of foundation models and large language models, autoML frameworks, and lightweight model designs. This survey offers a systematic framework for understanding the current landscape of deep time series anomaly detection and provides clear pathways for advancing the field to address real-world challenges.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100787"},"PeriodicalIF":13.3,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144596820","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}
引用次数: 0
The computing continuum: Past, present, and future 计算连续体:过去、现在和未来
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-07-10 DOI: 10.1016/j.cosrev.2025.100782
Luiz F. Bittencourt , Roberto Rodrigues-Filho , Josef Spillner , Filip De Turck , José Santos , Nelson L.S. da Fonseca , Omer Rana , Manish Parashar , Ian Foster
{"title":"The computing continuum: Past, present, and future","authors":"Luiz F. Bittencourt ,&nbsp;Roberto Rodrigues-Filho ,&nbsp;Josef Spillner ,&nbsp;Filip De Turck ,&nbsp;José Santos ,&nbsp;Nelson L.S. da Fonseca ,&nbsp;Omer Rana ,&nbsp;Manish Parashar ,&nbsp;Ian Foster","doi":"10.1016/j.cosrev.2025.100782","DOIUrl":"10.1016/j.cosrev.2025.100782","url":null,"abstract":"<div><div>The development of network-connected computing resources has led to various computing paradigms over the years, each bringing its own set of challenges for creating efficient distributed systems. Currently, there is an increasing need to integrate the evolving Internet of Things (IoT) with the established Cloud infrastructure. This integration often requires adding intermediate layers to address Cloud limitations such as latency, bandwidth, security, cost, and control. This configuration, known as the computing continuum, involves a diverse array of distributed devices with unique characteristics working together to meet the demands of both current and emerging applications. This paper explores the path that has led to the development of the computing continuum, offering a technology-agnostic definition from a historical perspective. It also examines applications that can benefit from the computing continuum and identifies research challenges that need to be addressed to fully realize its potential.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100782"},"PeriodicalIF":13.3,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144588383","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}
引用次数: 0
Autoscaling techniques in cloud-native computing: A comprehensive survey 云原生计算中的自动缩放技术:全面调查
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-07-09 DOI: 10.1016/j.cosrev.2025.100791
Byeonghui Jeong, Young-Sik Jeong
{"title":"Autoscaling techniques in cloud-native computing: A comprehensive survey","authors":"Byeonghui Jeong,&nbsp;Young-Sik Jeong","doi":"10.1016/j.cosrev.2025.100791","DOIUrl":"10.1016/j.cosrev.2025.100791","url":null,"abstract":"<div><div>Autoscaling, the core technology of cloud-native computing, dynamically adjusts computing resources as per application load fluctuations in order to improve scalability, cost efficiency, and performance continuity. By doing so, autoscaling enables widespread adoption of cloud-native computing across various industries; consequently, autoscaling techniques are critical for supporting the cloud-native paradigm. This study aims to provide a comprehensive survey of cloud-native autoscaling techniques, offering a unified understanding of current approaches and identifying unresolved issues. First, autoscaling algorithms and mechanisms are each classified into three types. Through this classification framework, a wide range of scaling algorithms, from threshold-based reactive policies to artificial intelligence (AI)-based proactive policies, are examined, and their respective advantages and limitations are analyzed. Next, the study comprehensively investigates and summarizes the experimental environments, datasets, and performance metrics used for evaluating autoscaling techniques. Furthermore, it systematically discusses key considerations for optimizing autoscaling techniques across the lifecycle of cloud-native applications by dividing the process into three distinct stages. In addition, this study provides a comprehensive review of cyberattacks that exploit autoscaling and the corresponding mitigation strategies. Finally, it discusses open issues, future directions, and research opportunities related to autoscaling in cloud-native computing.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100791"},"PeriodicalIF":13.3,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144588382","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}
引用次数: 0
A comprehensive review of cybersecurity vulnerabilities, threats, and solutions for the Internet of Things at the network-cum-application layer 全面回顾了网络和应用层的物联网网络安全漏洞、威胁和解决方案
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-07-03 DOI: 10.1016/j.cosrev.2025.100789
Abdul Razaque , Salim Hariri , Abrar M. Alajlan , Joon Yoo
{"title":"A comprehensive review of cybersecurity vulnerabilities, threats, and solutions for the Internet of Things at the network-cum-application layer","authors":"Abdul Razaque ,&nbsp;Salim Hariri ,&nbsp;Abrar M. Alajlan ,&nbsp;Joon Yoo","doi":"10.1016/j.cosrev.2025.100789","DOIUrl":"10.1016/j.cosrev.2025.100789","url":null,"abstract":"<div><div>The proliferation of smart homes, smart logistics, and other technologies has expedited the expansion of Internet-of-Things (IoT) devices. This expansion has heightened the complexity of associated security challenges. Despite extensive research on IoT security, several studies fail to provide a comprehensive examination of both the network and application layers. This is particularly applicable to real-time and mission-critical settings. This review addresses that deficiency by offering a systematic review of IoT across five tiers. It concentrates on the application layer, categorizing it into three domains: real-time control systems, scientific decision-making systems, and query/scan search systems. The study examines vulnerabilities, attack vectors, and security measures in real-time control and query/scan systems. It examines how emerging technologies such as artificial intelligence (AI), Software Defined Networking (SDN), and fog/edge computing can enhance security via improved context awareness and access management. The study ultimately presents recommendations and suggests enhancements to foster trust, scalability, and enhanced security in contemporary IoT systems.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100789"},"PeriodicalIF":13.3,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536154","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}
引用次数: 0
Facial privacy in the digital era: A comprehensive survey on methods, evaluation, and future directions 数字时代的面部隐私:方法、评估和未来方向的综合调查
IF 13.3 1区 计算机科学
Computer Science Review Pub Date : 2025-07-01 DOI: 10.1016/j.cosrev.2025.100785
Miaomiao Wang , Sheng Li , Xinpeng Zhang , Guorui Feng
{"title":"Facial privacy in the digital era: A comprehensive survey on methods, evaluation, and future directions","authors":"Miaomiao Wang ,&nbsp;Sheng Li ,&nbsp;Xinpeng Zhang ,&nbsp;Guorui Feng","doi":"10.1016/j.cosrev.2025.100785","DOIUrl":"10.1016/j.cosrev.2025.100785","url":null,"abstract":"<div><div>With the advancement of computer vision technology and smart devices, images and videos containing facial information are increasingly shared on social media, making it easier for facial data to be collected and misused. As sensitive biometric data, once facial information is leaked, it may cause irreversible damage to personal privacy. Ensuring the security of facial information while benefiting from technological conveniences has become a critical research area. Many surveys have summarized existing protection measures, which often focus on specific issues or are oriented toward particular technologies, so existing methods have not been comprehensively summarized. In this paper, we categorize facial privacy-preserving methods into four paradigms: appearance-guided, identity-guided, reversible, and privacy-preserving for facial recognition systems. We offer an in-depth review of the most representative methods, emphasizing their advantages and functional characteristics. Additionally, we present commonly used datasets and evaluation metrics and analyze the performance of current methods. Finally, we discuss the challenges and opportunities for practical applications in facial privacy protection, offering insights for future research.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100785"},"PeriodicalIF":13.3,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144518885","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}
引用次数: 0
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