{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T02:07:27Z","timestamp":1763345247451,"version":"3.45.0"},"reference-count":66,"publisher":"Tech Science Press","issue":"1","license":[{"start":{"date-parts":[[2025,8,31]],"date-time":"2025-08-31T00:00:00Z","timestamp":1756598400000},"content-version":"vor","delay-in-days":242,"URL":"https:\/\/doi.org\/10.32604\/TSP-CROSSMARKPOLICY"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.064777","type":"journal-article","created":{"date-parts":[[2025,8,1]],"date-time":"2025-08-01T07:30:41Z","timestamp":1754033441000},"page":"301-329","update-policy":"https:\/\/doi.org\/10.32604\/tsp-crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["A Comprehensive Survey of Contemporary Anomaly Detection Methods for Securing Smart IoT Systems"],"prefix":"10.32604","volume":"85","author":[{"given":"Chaimae","family":"Hazman","sequence":"first","affiliation":[]},{"given":"Azidine","family":"Guezzaz","sequence":"additional","affiliation":[]},{"given":"Said","family":"Benkirane","sequence":"additional","affiliation":[]},{"given":"Mourade","family":"Azrour","sequence":"additional","affiliation":[]},{"given":"Vinayakumar","family":"Ravi","sequence":"additional","affiliation":[]},{"given":"Abdulatif","family":"Alabdulatif","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","first-page":"4623","article-title":"Securing Internet of Things devices with federated learning: a privacy-preserving approach for distributed intrusion detection","volume":"83","author":"Al Amro","year":"2025","journal-title":"Comput Mater Contin"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"157727","DOI":"10.1109\/ACCESS.2021.3129336","article-title":"A comprehensive systematic literature review on intrusion detection systems","volume":"9","author":"Ozkan-Okay","year":"2021","journal-title":"IEEE Access"},{"key":"ref3","first-page":"e70017","article-title":"Blockchain-based network security analysis framework for telesurgery systems","volume":"6","author":"Alshamrani","year":"2023","journal-title":"Secur Priv"},{"key":"ref4","first-page":"1","article-title":"Analysis of deep learning-based intrusion detection systems in IoT environments","volume":"54","author":"Blali","year":"2025","journal-title":"EDPACS"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/07366981.2025.2478706","article-title":"Enhancing DDoS attack detection in software-defined networking: a comparative study of machine learning algorithms using benchmark datasets","author":"Boukraa","year":"2025","journal-title":"EDPACS"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"58851","DOI":"10.1109\/ACCESS.2024.3389096","article-title":"A comparative study of using deep learning algorithms in network intrusion detection","volume":"12","author":"Elsayed","year":"2024","journal-title":"IEEE Access"},{"key":"ref7","first-page":"1","article-title":"An explainable machine learning-based web attack detection system for industrial IoT web application security","volume":"357","author":"Chakir","year":"2024","journal-title":"Inf Secur J A Glob Perspect"},{"key":"ref8","first-page":"72","author":"Douiba","year":"2025","journal-title":"Recent advances in internet of things security"},{"key":"ref9","first-page":"65","article-title":"Internet of things authentication protocols: comparative study","volume":"79","author":"Dargaoui","year":"2024","journal-title":"Comput Mater Contin"},{"key":"ref10","first-page":"17","article-title":"Secure IoT for healthcare","volume":"1","author":"Panahi","year":"2025","journal-title":"Eur J Innov Stud Sustain"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.3390\/electronics13061031","article-title":"Detection of DoS attacks for IoT in information-centric networks using machine learning: opportunities, challenges, and future research directions","volume":"13","author":"Bukhowah","year":"2024","journal-title":"Electronics"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.jnca.2019.02.026","article-title":"Intrusion detection in smart cities using Restricted Boltzmann Machines","volume":"135","author":"Elsaeidy","year":"2019","journal-title":"J Netw Comput Appl"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"3753","DOI":"10.1007\/s10586-023-04162-z","article-title":"A novel hybrid framework for Cloud Intrusion Detection System using system call sequence analysis","volume":"27","author":"Chaudhari","year":"2024","journal-title":"Clust Comput"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"713","DOI":"10.3390\/s24020713","article-title":"Anomaly detection IDS for detecting DoS attacks in IoT networks based on machine learning algorithms","volume":"24","author":"Altulaihan","year":"2024","journal-title":"Sensors"},{"key":"ref15","series-title":"Proceedings of the 2019 4th MEC International Conference on Big Data and Smart City (ICBDSC)","article-title":"Application of smart structural system for smart sustainable cities","author":"Farag","year":"2019 Jan 15\u201316"},{"key":"ref16","first-page":"2607","article-title":"A fused machine learning approach for intrusion detection system","volume":"74","author":"Sajid Farooq","year":"2023","journal-title":"Comput Mater Contin"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"3511","DOI":"10.1109\/JSEN.2013.2259691","article-title":"IPv6 addressing strategies for IoT","volume":"13","author":"Savolainen","year":"2013","journal-title":"IEEE Sens J"},{"key":"ref18","first-page":"467","author":"Hande","year":"2020","journal-title":"Research anthology on artificial intelligence applications in security"},{"key":"ref19","first-page":"1227","article-title":"Toward intrusion detection of industrial cyber-physical system: a hybrid approach based on system state and network traffic abnormality monitoring","volume":"84","author":"He","year":"2025","journal-title":"Comput Mater Contin"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"4069","DOI":"10.1007\/s10586-022-03810-0","article-title":"lIDS-SIoEL: intrusion detection framework for IoT-based smart environments security using ensemble learning","volume":"26","author":"Hazman","year":"2023","journal-title":"Cluster Comput"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"929","DOI":"10.26599\/TST.2023.9010033","article-title":"Enhanced IDS with deep learning for IoT-based smart cities security","volume":"29","author":"Hazman","year":"2024","journal-title":"Tsinghua Sci Technol"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1007\/s10586-024-04780-1","article-title":"A smart model integrating LSTM and XGBoost for improving IoT-enabled smart cities security","volume":"28","author":"Hazman","year":"2024","journal-title":"Clust Comput"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"62159","DOI":"10.1007\/s11042-023-16436-0","article-title":"Toward an intrusion detection model for IoT-based smart environments","volume":"83","author":"Hazman","year":"2024","journal-title":"Multimed Tools Appl"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"102002","DOI":"10.1016\/j.inffus.2023.102002","article-title":"Fed-inforce-fusion: a federated reinforcement-based fusion model for security and privacy protection of IoMT networks against cyber-attacks","volume":"101","author":"Khan","year":"2024","journal-title":"Inf Fusion"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.pisc.2016.04.005","article-title":"Computational neural network regression model for host based intrusion detection system","volume":"8","author":"Gautam","year":"2016","journal-title":"Perspect Sci"},{"article-title":"Improving intrusion detection by utilizing adaptive boosting based ensemble classifier","series-title":"Proceedings of the First International Conference on Data Science & Exploration in Artificial Intelligence (CODE-AI 2024); 2024 Jul 3\u20134","author":"Kumar","key":"ref26"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.jpdc.2022.03.003","article-title":"FELIDS: federated learning-based intrusion detection system for agricultural Internet of Things","volume":"165","author":"Friha","year":"2022","journal-title":"J Parallel Distrib Comput"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"103540","DOI":"10.1016\/j.adhoc.2024.103540","article-title":"A federated learning-based zero trust intrusion detection system for Internet of Things","volume":"162","author":"Javeed","year":"2024","journal-title":"Ad Hoc Netw"},{"key":"ref29","first-page":"27","article-title":"Emerging threats in Internet-of-Things (IoT) hardware security","volume":"25","author":"Elshafie","year":"2025","journal-title":"Int J Comput Sci Netw Secur"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"3179","DOI":"10.1007\/s13042-020-01241-0","article-title":"Ensemble machine learning approach for classification of IoT devices in smart home","volume":"12","author":"Cviti\u0107","year":"2021","journal-title":"Int J Mach Learn Cybern"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"1169","DOI":"10.1007\/s13132-021-00767-0","article-title":"Towards high impact smart cities: a universal architecture based on connected intelligence spaces","volume":"13","author":"Komninos","year":"2022","journal-title":"J Knowl Econ"},{"key":"ref32","doi-asserted-by":"crossref","first-page":"4330","DOI":"10.3390\/en14144330","article-title":"Analysis of the social aspect of smart cities development for the example of smart sustainable buildings","volume":"14","author":"Radziejowska","year":"2021","journal-title":"Energies"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"4083","DOI":"10.12694\/scpe.v25i5.3005","article-title":"Research and analysis of smart city landscape design and planning based on the Internet of Things","volume":"25","author":"Kang","year":"2024","journal-title":"Scalable Comput Pract Exp"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"1716396","DOI":"10.1155\/2021\/1716396","article-title":"Construction of smart city street landscape big data-driven intelligent system based on industry 4.0","volume":"2021","author":"Li","year":"2021","journal-title":"Comput Intell Neurosci"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"117362","DOI":"10.1016\/j.eswa.2022.117362","article-title":"Mobile and wearable sensors for data-driven health monitoring system: state-of-the-art and future prospect","volume":"202","author":"Virginia Anikwe","year":"2022","journal-title":"Expert Syst Appl"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"105899","DOI":"10.1016\/j.engappai.2023.105899","article-title":"Smart farming using artificial intelligence: a review","volume":"120","author":"Akkem","year":"2023","journal-title":"Eng Appl Artif Intell"},{"key":"ref37","doi-asserted-by":"crossref","first-page":"6978","DOI":"10.3390\/s21216978","article-title":"A comprehensive review on smart grids: challenges and opportunities","volume":"21","author":"Moreno Escobar","year":"2021","journal-title":"Sensors"},{"key":"ref38","doi-asserted-by":"crossref","first-page":"122380","DOI":"10.1016\/j.eswa.2023.122380","article-title":"Experts and intelligent systems for smart homes\u2019 transformation to sustainable smart cities: a comprehensive review","volume":"238","author":"Huda","year":"2024","journal-title":"Expert Syst Appl"},{"key":"ref39","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1016\/j.jiph.2024.01.013","article-title":"Multirole of the Internet of medical things (IoMT) in biomedical systems for managing smart healthcare systems: an overview of current and future innovative trends","volume":"17","author":"Mathkor","year":"2024","journal-title":"J Infect Public Health"},{"key":"ref40","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1007\/s10462-024-10712-7","article-title":"Artificial intelligence and multimodal data fusion for smart healthcare: topic modeling and bibliometrics","volume":"57","author":"Chen","year":"2024","journal-title":"Artif Intell Rev"},{"key":"ref41","doi-asserted-by":"crossref","first-page":"141","DOI":"10.3390\/knowledge4020008","article-title":"Evaluation of the omni-secure firewall system in a private cloud environment","volume":"4","author":"Mahmood","year":"2024","journal-title":"Knowledge"},{"key":"ref42","doi-asserted-by":"crossref","first-page":"1554","DOI":"10.1038\/s41598-025-85248-z","article-title":"An optimized LSTM-based deep learning model for anomaly network intrusion detection","volume":"15","author":"Dash","year":"2025","journal-title":"Sci Rep"},{"key":"ref43","first-page":"1659","article-title":"TIDS: tensor based intrusion detection system (IDS) and its application in large scale DDoS attack detection","volume":"84","author":"Sun","year":"2025","journal-title":"Comput Mater Contin"},{"key":"ref44","doi-asserted-by":"crossref","first-page":"102406","DOI":"10.1016\/j.phycom.2024.102406","article-title":"Abnormal traffic detection for Internet of Things based on an improved residual network","volume":"66","author":"Wang","year":"2024","journal-title":"Phys Commun"},{"key":"ref45","first-page":"44","author":"Roy","year":"2017","journal-title":"Mathematics and computing"},{"key":"ref46","doi-asserted-by":"crossref","first-page":"158","DOI":"10.3390\/network3010008","article-title":"A federated learning-based approach for improving intrusion detection in industrial Internet of Things networks","volume":"3","author":"Rashid","year":"2023","journal-title":"Network"},{"key":"ref47","doi-asserted-by":"crossref","first-page":"12218","DOI":"10.1007\/s11227-024-05895-3","article-title":"DL-HIDS: deep learning-based host intrusion detection system using system calls-to-image for containerized cloud environment","volume":"80","author":"Joraviya","year":"2024","journal-title":"J Supercomput"},{"key":"ref48","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1007\/s11276-023-03495-2","article-title":"Retraction note: towards an efficient model for network intrusion detection system (IDS): systematic literature review","volume":"30","author":"Abdulganiyu","year":"2025","journal-title":"Wirel Netw"},{"key":"ref49","doi-asserted-by":"crossref","first-page":"57542","DOI":"10.1109\/ACCESS.2021.3071263","article-title":"A review of rule learning-based intrusion detection systems and their prospects in smart grids","volume":"9","author":"Liu","year":"2021","journal-title":"IEEE Access"},{"key":"ref50","doi-asserted-by":"crossref","first-page":"4372","DOI":"10.3390\/s20164372","article-title":"Machine learning-based IoT-botnet attack detection with sequential architecture","volume":"20","author":"Soe","year":"2020","journal-title":"Sensors"},{"key":"ref51","doi-asserted-by":"crossref","first-page":"41525","DOI":"10.1109\/ACCESS.2019.2895334","article-title":"Deep learning approach for intelligent intrusion detection system","volume":"7","author":"Vinayakumar","year":"2019","journal-title":"IEEE Access"},{"key":"ref52","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1016\/j.procs.2017.12.091","article-title":"Statistical analysis of CIDDS-001 dataset for network intrusion detection systems using distance-based machine learning","volume":"125","author":"Verma","year":"2018","journal-title":"Procedia Comput Sci"},{"key":"ref53","doi-asserted-by":"crossref","first-page":"48697","DOI":"10.1109\/ACCESS.2018.2867564","article-title":"An intrusion detection system using a deep neural network with gated recurrent units","volume":"6","author":"Xu","year":"2018","journal-title":"IEEE Access"},{"key":"ref54","first-page":"1731","article-title":"DEMGAN: a machine learning-based intrusion detection system evasion scheme","volume":"84","author":"Xu","year":"2025","journal-title":"Comput Mater Contin"},{"key":"ref55","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1109\/COMST.2021.3139052","article-title":"Surveying trust-based collaborative intrusion detection: state-of-the-art, challenges and future directions","volume":"24","author":"Li","year":"2022","journal-title":"IEEE Commun Surv Tut"},{"key":"ref56","first-page":"4389","article-title":"Diff-IDS: a network intrusion detection model based on diffusion model for imbalanced data samples","volume":"82","author":"Yang","year":"2025","journal-title":"Comput Mater Contin"},{"key":"ref57","first-page":"639","article-title":"Intrusion detection in NSL-KDD dataset using hybrid self-organizing map model","volume":"143","author":"Iftikhar","year":"2025","journal-title":"Comput Model Eng Sci"},{"key":"ref58","doi-asserted-by":"crossref","first-page":"2227","DOI":"10.1016\/j.procs.2024.04.211","article-title":"Network anomaly detection and performance evaluation of Convolutional Neural Networks on UNSW-NB15 dataset","volume":"235","author":"Vibhute","year":"2024","journal-title":"Procedia Comput Sci"},{"article-title":"Statistical analysis of honeypot data and building of Kyoto 2006+ dataset for NIDS evaluation","series-title":"Proceedings of the First Workshop on Building Analysis Datasets and Gathering Experience Returns for Security; 2011 Apr 10","author":"Song","key":"ref59"},{"article-title":"A review and analysis of the bot-IoT dataset","series-title":"Proceedings of the 2021 IEEE International Conference on Service-Oriented System Engineering (SOSE); 2021 Aug 23\u201326","author":"Peterson","key":"ref60"},{"key":"ref61","doi-asserted-by":"crossref","first-page":"6430","DOI":"10.1109\/ACCESS.2021.3140015","article-title":"Generative deep learning to detect cyberattacks for the IoT-23 dataset","volume":"10","author":"Abdalgawad","year":"2021","journal-title":"IEEE Access"},{"key":"ref62","doi-asserted-by":"crossref","first-page":"9572","DOI":"10.3390\/app12199572","article-title":"Analysis of ToN-IoT, UNW-NB15, and edge-IIoT datasets using DL in cybersecurity for IoT","volume":"12","author":"Tareq","year":"2022","journal-title":"Appl Sci"},{"key":"ref63","first-page":"3725","article-title":"Adaptive cloud intrusion detection system based on pruned exact linear time technique","volume":"79","author":"Elbakri","year":"2024","journal-title":"Comput Mater Contin"},{"key":"ref64","doi-asserted-by":"crossref","first-page":"863","DOI":"10.1613\/jair.1.11192","article-title":"SMOTE for learning from imbalanced data: progress and challenges, marking the 15-year anniversary","volume":"61","author":"Fernandez","year":"2018","journal-title":"J Artif Intell Res"},{"article-title":"Data and model centric approaches for card fraud detection","series-title":"Proceedings of the 2023 International Conference on Computer and Applications (ICCA); 2023 Nov 28\u201330","author":"Farag","key":"ref65"},{"key":"ref66","first-page":"801","article-title":"Intrusion detection based on bidirectional long short-term memory with attention mechanism","volume":"74","author":"Yang","year":"2023","journal-title":"Comput Mater Contin"}],"container-title":["Computers, Materials &amp; Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-85-1\/TSP_CMC_64777\/TSP_CMC_64777.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T02:03:22Z","timestamp":1763345002000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v85n1\/63513"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":66,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.064777","relation":{},"ISSN":["1546-2226"],"issn-type":[{"type":"electronic","value":"1546-2226"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"2025-02-24","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-22","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-08-29","order":2,"name":"published","label":"Published Online","group":{"name":"publication_history","label":"Publication History"}}]}}