{"title":"A conceptual framework to mitigate ransomware attacks on IoMT devices using threat intelligence: a systematic literature review","authors":"Kalaivani Selvaraj, Manmeet Mahinderjit Singh, Zarul Fitri Zaaba","doi":"10.1016/j.cosrev.2025.100801","DOIUrl":"10.1016/j.cosrev.2025.100801","url":null,"abstract":"<div><div>Internet of Medical Things (IoMT) device usage increases due to the development of low-power embedded devices and internet technologies. IoMT devices store medical data on internal devices such as Secure Digital (SD) card, Read Only Memory (ROM), and external devices such as private, public, and hybrid cloud server. IoMT devices, web and application services, and medical data are prone to cyberattacks. However, Ransomware attack on IoMT devices, such as physical and storage devices are increased due to increase usage of home diagnostic devices. Existing cyberattack frameworks, methods, algorithms, and cyber resilience fail to detect, prevent, and mitigate novel ransomware variants. The ransomware variant based attacks on IoMT devices rapidly increases on daily basis. Ransomware variant detection is challenging in IoMT devices due to acquisition of different types and structure of medical data. This Systematic Literature Review (SLR) reviews the existing methods and framework for detection of different ransomware variant attacks. In this SLR, 154 published research articles were analyzed from 2014 to 2025 on ransomware attack detection and prevention methods. The above articles are Scopus indexed and Science Citation Indexed (SCI). This SLR explore towards cyberattack variant detection methods. From this review analysis, a conceptual Robust Reliable Adaptable and comprehensive (RRAC) framework is proposed for the identified research gap, i.e., ransomware variant detection in IoMT devices. The proposed RRAC framework is based on Situational Awareness Reference Model (SARM) and MITRE ATT&CK and uses Fuzzy Rough Set Theory, Graph Theory, GenAI, and Threat Intelligence for ransomware variant detection in IoMT devices.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100801"},"PeriodicalIF":12.7,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144827342","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}
Mehdi Hosseinzadeh , Jawad Tanveer , Amir Masoud Rahmani , Farhad Soleimanian Gharehchopogh , Ramin Abbaszadi , Sang-Woong Lee , Jan Lansky
{"title":"Sand cat swarm optimization: A comprehensive review of algorithmic advances, structural enhancements, and engineering applications","authors":"Mehdi Hosseinzadeh , Jawad Tanveer , Amir Masoud Rahmani , Farhad Soleimanian Gharehchopogh , Ramin Abbaszadi , Sang-Woong Lee , Jan Lansky","doi":"10.1016/j.cosrev.2025.100805","DOIUrl":"10.1016/j.cosrev.2025.100805","url":null,"abstract":"<div><div>Metaheuristic algorithms, as powerful computational tools, play a significant role in solving complex optimization problems in the field of engineering. Among these algorithms, the Sand Cat Swarm Optimization (SCSO) algorithm, inspired by the hunting behaviour of sand cats, has shown considerable potential in addressing combinatorial problems and real-world applications. In this survey paper, a systematic and comprehensive review of the basic structure and extended versions of the SCSO has been conducted. Papers related to SCSO have been collected from 5 major databases (Elsevier, Springer, IEEE, MDPI, and Wiley). Elsevier and Springer contain the largest share of articles, with 32% and 26%, respectively. In this paper, binary, multi-objective, and hybrid versions have been thoroughly reviewed. Also, the application of the SCSO in various engineering fields, including structural engineering, energy systems, biomedical computing, and control systems, has been fully investigated. The field of engineering problems and Electronics-Power include the highest percentage of SCSO usage, with 20% and 24%, respectively. The results of statistical analyses show that the improved versions of SCSO outperform the basic metaheuristic algorithms in stability of results, convergence speed, and final quality of answers.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100805"},"PeriodicalIF":12.7,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810203","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":"The Lonely Runner Conjecture turns 60","authors":"Guillem Perarnau, Oriol Serra","doi":"10.1016/j.cosrev.2025.100798","DOIUrl":"https://doi.org/10.1016/j.cosrev.2025.100798","url":null,"abstract":"The Lonely Runner Conjecture originated in Diophantine approximation is turning 60. Even if the conjecture is still widely open, the flow of partial results, innovative tools and connections to different problems and applications has been steady on its long life. This survey attempts to give a panoramic view of the status of the problem, trying to highlight the contributions of the many papers that it has originated.","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"14 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144898566","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 survey on Hedetniemi’s conjecture","authors":"Xuding Zhu","doi":"10.1016/j.cosrev.2025.100794","DOIUrl":"https://doi.org/10.1016/j.cosrev.2025.100794","url":null,"abstract":"In 1966, Hedetniemi conjectured that for any positive integer <mml:math altimg=\"si928.svg\" display=\"inline\"><mml:mi>n</mml:mi></mml:math> and graphs <mml:math altimg=\"si2.svg\" display=\"inline\"><mml:mi>G</mml:mi></mml:math> and <mml:math altimg=\"si929.svg\" display=\"inline\"><mml:mi>H</mml:mi></mml:math>, if neither <mml:math altimg=\"si2.svg\" display=\"inline\"><mml:mi>G</mml:mi></mml:math> nor <mml:math altimg=\"si929.svg\" display=\"inline\"><mml:mi>H</mml:mi></mml:math> is <mml:math altimg=\"si928.svg\" display=\"inline\"><mml:mi>n</mml:mi></mml:math>-colourable, then <mml:math altimg=\"si7.svg\" display=\"inline\"><mml:mrow><mml:mi>G</mml:mi><mml:mo linebreak=\"goodbreak\" linebreakstyle=\"after\">×</mml:mo><mml:mi>H</mml:mi></mml:mrow></mml:math> is not <mml:math altimg=\"si928.svg\" display=\"inline\"><mml:mi>n</mml:mi></mml:math>-colourable. This conjecture has received significant attention over the past half century, and was disproved by Shitov in 2019. Shitov’s proof shows that Hedetniemi’s conjecture fails for sufficiently large <mml:math altimg=\"si928.svg\" display=\"inline\"><mml:mi>n</mml:mi></mml:math>. Shortly after Shitov’s result, smaller counterexamples were found in a series of papers, and it is now known that Hedetniemi’s conjecture fails for all <mml:math altimg=\"si10.svg\" display=\"inline\"><mml:mrow><mml:mi>n</mml:mi><mml:mo linebreak=\"goodbreak\" linebreakstyle=\"after\">≥</mml:mo><mml:mn>4</mml:mn></mml:mrow></mml:math>, and holds for <mml:math altimg=\"si11.svg\" display=\"inline\"><mml:mrow><mml:mi>n</mml:mi><mml:mo linebreak=\"goodbreak\" linebreakstyle=\"after\">≤</mml:mo><mml:mn>3</mml:mn></mml:mrow></mml:math>. Hedetniemi’s conjecture has inspired extensive research, and many related problems remain open. This paper surveys the results and problems associated with the conjecture, and explains the ideas used in finding counterexamples.","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"14 1","pages":""},"PeriodicalIF":12.9,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144898576","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 survey on graph problems parameterized above and below guaranteed values","authors":"Gregory Gutin, Matthias Mnich","doi":"10.1016/j.cosrev.2025.100795","DOIUrl":"https://doi.org/10.1016/j.cosrev.2025.100795","url":null,"abstract":"We survey the field of algorithms and complexity for graph problems parameterized above or below guaranteed values. Those problems seek, for a given graph <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:mi>G</mml:mi></mml:math>, a solution whose value is at least <mml:math altimg=\"si2.svg\" display=\"inline\"><mml:mrow><mml:mi>g</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>G</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mo linebreak=\"goodbreak\" linebreakstyle=\"after\">+</mml:mo><mml:mi>k</mml:mi></mml:mrow></mml:math> or at most <mml:math altimg=\"si3.svg\" display=\"inline\"><mml:mrow><mml:mi>g</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>G</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mo linebreak=\"goodbreak\" linebreakstyle=\"after\">−</mml:mo><mml:mi>k</mml:mi></mml:mrow></mml:math>, where <mml:math altimg=\"si4.svg\" display=\"inline\"><mml:mrow><mml:mi>g</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>G</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math> is a guarantee on the value that <ce:italic>any</ce:italic> solution on <mml:math altimg=\"si1.svg\" display=\"inline\"><mml:mi>G</mml:mi></mml:math> takes. The goal is to design algorithms which find such solution in time whose complexity in <mml:math altimg=\"si6.svg\" display=\"inline\"><mml:mi>k</mml:mi></mml:math> is decoupled from that in the guarantee, or to rule out the existence of such algorithms by means of intractability results. We discuss a large number of algorithms and intractability results, and complement them by several open problems.","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"24 1","pages":"100795"},"PeriodicalIF":12.9,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144898575","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}
Tanzila Kehkashan, Raja Adil Riaz, Ahmad Sami Al-Shamayleh, Adnan Akhunzada, Noman Ali, Muhammad Hamza, Faheem Akbar
{"title":"AI-generated text detection: A comprehensive review of methods, datasets, and applications","authors":"Tanzila Kehkashan, Raja Adil Riaz, Ahmad Sami Al-Shamayleh, Adnan Akhunzada, Noman Ali, Muhammad Hamza, Faheem Akbar","doi":"10.1016/j.cosrev.2025.100793","DOIUrl":"https://doi.org/10.1016/j.cosrev.2025.100793","url":null,"abstract":"This review examines the rapidly evolving field of AI-generated text detection, which has gained critical importance following the widespread deployment of advanced large language models like ChatGPT. We analyze the technical foundations, methodological approaches, evaluation frameworks, and practical applications of detection technologies designed to distinguish between human and machine-authored content. The paper synthesizes current knowledge across key dimensions: detection techniques ranging from statistical approaches to neural architectures, datasets and their limitations, performance metrics and evaluation challenges, real-world implementations across educational, publishing, and legal domains, and emerging research directions. Our analysis reveals significant challenges, including the inherent adversarial nature of detection, cross-domain generalization difficulties, and fairness concerns regarding certain writer populations. We identify promising trends toward multi-scale analysis, human-AI collaborative frameworks, and complementary provenance-based approaches. The review concludes that effective detection remains feasible but requires combining multiple approaches, domain-specific customization, and attention to ethical implications. This comprehensive examination serves as a resource for researchers, practitioners, and policymakers navigating the complex technical and societal dimensions of AI text detection in an era of increasingly sophisticated generative AI systems.","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"33 1","pages":"100793"},"PeriodicalIF":12.9,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144898577","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":"Parameterized algorithms on geometric intersection graphs","authors":"Jie Xue , Meirav Zehavi","doi":"10.1016/j.cosrev.2025.100796","DOIUrl":"10.1016/j.cosrev.2025.100796","url":null,"abstract":"<div><div>We survey results on the parameterized complexity of various problems on geometric intersection graphs, particularly (unit) disk graphs. Specifically, we consider: (i) vertex-deletion, packing and pattern detection problems; (ii) <span>Independent Set</span> and <span>Dominating Set</span>; (iii) cut and connectivity problems; (iv) obstacle-removal problems. The discussions include introductions of some of the proof ideas and directions for future research.</div></div>","PeriodicalId":48633,"journal":{"name":"Computer Science Review","volume":"58 ","pages":"Article 100796"},"PeriodicalIF":12.7,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779484","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 survey of Community Detection algorithms and its comparative performance analysis","authors":"Dipika Singh , 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}
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 , M.A. Balafar , 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}
Marco D’Elia , Irene Finocchi , Maurizio Patrignani
{"title":"Maximal cliques summarization: Principles, problem classification, and algorithmic approaches","authors":"Marco D’Elia , Irene Finocchi , 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}