Výsledky vyhledávání - "Botnet Detection"

An Ensemble Model for Word-based DGA Botnet Detection Using XGBoost and BERT

Autoři: VU, X. H. HOANG, X. D.

Zdroj: Advances in Electrical and Computer Engineering, Vol 25, Iss 3, Pp 13-20 (2025)

Témata: domain generation algorithm, word-based dga botnet, botnet detection model, word-based botnet detection, Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Computer engineering. Computer hardware, TK7885-7895

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1582-7445; https://doaj.org/toc/1844-7600

Přístupová URL adresa: https://doaj.org/article/d13b435b67ad4e559182a0a1311cc71c

A novel feature selection-driven ensemble learning approach for accurate botnet attack detection

Autoři: Md. Alamgir Hossain Md. Saiful Islam

Zdroj: Alexandria Engineering Journal, Vol 118, Iss, Pp 261-277 (2025)

Témata: Ensemble learning, Anomaly detection, TA1-2040, Mirai and Bashlite botnets, Engineering (General). Civil engineering (General), High-accuracy botnet detection, Machine learning in ioT

Přístupová URL adresa: https://doaj.org/article/8223813031ee467f93cfeb19dde91bd8

SDN-based detection and mitigation of botnet traffic in large-scale networks

Autoři: Shaik, Kamal Mohammed Najeeb

Zdroj: World Journal of Advanced Research and Reviews. 25:2773-2784

Témata: Network Security, Machine Learning, Large-Scale Networks, Botnet Detection, Flow Analysis, Software-Defined Networking (SDN), Traffic Mitigation

Classifying IoT Botnet Attacks With Kolmogorov-Arnold Networks: A Comparative Analysis of Architectural Variations

Autoři: Phuc Hao do Tran Duc Le Truong Duy Dinh a další

Zdroj: IEEE Access, Vol 13, Pp 16072-16093 (2025)

Témata: Cybersecurity, Kolmogorov-Arnold networks, IoT botnet detection, Electrical engineering. Electronics. Nuclear engineering, network intrusion detection, TK1-9971

Přístupová URL adresa: https://doaj.org/article/d4f381cf45014e5eb5f56f1953fcc8da

Ensemble Network Graph-Based Classification for Botnet Detection Using Adaptive Weighting and Feature Extraction

Autoři: Muhammad Aidiel Rachman Putra Tohari Ahmad Dandy Pramana Hostiadi a další

Zdroj: IEEE Access, Vol 13, Pp 31183-31204 (2025)

Témata: machine learning, network infrastructure, information security, network security, Botnet detection, Electrical engineering. Electronics. Nuclear engineering, graph-based representation, TK1-9971

Přístupová URL adresa: https://doaj.org/article/951cec042d224ce08f7f0803aa620852

Hierarchical Clustering Approach With Distribution Similarity Strategy for Multi-Class Botnet Labeling in Real-World Traffic

Autoři: Ta-Chun Lo Che-Hsien Lin Jyh-Biau Chang a další

Zdroj: IEEE Access, Vol 13, Pp 111024-111036 (2025)

Témata: machine learning, NetFlow, network security, deep learning, Botnet detection, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Přístupová URL adresa: https://doaj.org/article/412b4a550acd4b94ace995ab732763e4

A Systematic Literature Review: Classifying IoT Botnet Data Features Based on Its Lifecycle

Autoři: Shihao Liu Fariza Fauzi Ven Jyn Kok

Zdroj: IEEE Access, Vol 13, Pp 65040-65065 (2025)

Témata: systematic literature review (SLR), features, Electrical engineering. Electronics. Nuclear engineering, botnet detection, Internet of Things (IoT), lifecycle, TK1-9971

Přístupová URL adresa: https://doaj.org/article/9c2659fc42714bd3bbbd6128dc27d49c

A novel federated learning approach for IoT botnet intrusion detection using SHAP-based knowledge distillation

Autoři: Md. Alamgir Hossain Sadman Saif Md. Saiful Islam

Zdroj: Complex & Intelligent Systems, Vol 11, Iss 10, Pp 1-23 (2025)

Témata: Federated IoT security, Privacy-preserving intrusion detection, SHAP-based knowledge distillation, Decentralized feature aggregation, Non-IID data handling, Botnet detection in IoT, Electronic computers. Computer science, QA75.5-76.95, Information technology, T58.5-58.64

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2199-4536; https://doaj.org/toc/2198-6053

Přístupová URL adresa: https://doaj.org/article/c2d81e61611f483fbc86b53f872563cd

Securing RPL-Based Networks Against Version Number and Rank Attacks

Autoři: Alaa Eddine Khalfoune Rachid Beghdad

Zdroj: Acta Informatica Pragensia, Vol 13, Iss 3, Pp 340-358 (2024)

Témata: Computer Networks and Communications, routing protocol for low power and lossy networks, security, 7. Clean energy, Characterization and Detection of Android Malware, Artificial Intelligence, Computer security, blocking techniques, Side-Channel Attacks, FOS: Mathematics, Cache Attacks, Language-based Information Flow Security, DDoS Attacks, lln, QA75.5-76.95, internet of things, Computer science, Network Security, Rank (graph theory), Combinatorics, Electronic computers. Computer science, Signal Processing, Computer Science, Physical Sciences, Network Intrusion Detection and Defense Mechanisms, Botnet Detection, Mathematics

Přístupová URL adresa: https://doaj.org/article/75ddb5b014fa43ba9d1e92c3478364d2

Hateful Sentiment Detection in Real-Time Tweets: An LSTM-Based Comparative Approach

Autoři: Sanjiban Sekhar Roy Abhijit Guha Roy Pijush Samui a další

Zdroj: IEEE Transactions on Computational Social Systems. 11:5028-5037

Témata: Artificial neural network, Artificial intelligence, Support vector machine, Naive Bayes classifier, Computer Networks and Communications, Offensive Language, Natural language processing, 4. Education, 16. Peace & justice, Computer science, 3. Good health, Detection, Artificial Intelligence, Machine Learning for Internet Traffic Classification, Computer Science, Physical Sciences, Machine learning, 8. Economic growth, Automated Detection of Hate Speech and Offensive Language, Network Intrusion Detection and Defense Mechanisms, Hate Speech, Botnet Detection, 10. No inequality, Natural Language Processing, Random forest

FortisEDoS: A Deep Transfer Learning-Empowered Economical Denial of Sustainability Detection Framework for Cloud-Native Network Slicing

Autoři: Chafika Benzaïd Tarik Taleb Ashkan Sami a další

Zdroj: IEEE Transactions on Dependable and Secure Computing

Témata: Artificial intelligence, Denial-of-service attack, Computer Networks and Communications, 7. Clean energy, 12. Responsible consumption, Anomaly Detection in High-Dimensional Data, Transfer of learning, Characterization and Detection of Android Malware, Deep Learning, Artificial Intelligence, Computer security, 11. Sustainability, Cloud computing, 14. Life underwater, DDoS Attacks, Deep learning, 15. Life on land, Computer science, Intrusion Detection, World Wide Web, Detection, Operating system, 13. Climate action, Computer Science, Physical Sciences, Signal Processing, Network Intrusion Detection and Defense Mechanisms, Botnet Detection, The Internet

Special Characters in Domain's Name as Possible Indication of Compromitation Status

Autoři: Tepeš Golubić, Lidija Cafuta, Davor Dodig, Ivica a další

Zdroj: 2024 23rd International Symposium INFOTEH-JAHORINA (INFOTEH). :1-6

Témata: Botnet detection, forensic linguistic

Přístupová URL adresa: https://ieeexplore.ieee.org/document/10495994
https://doi.org/10.1109/INFOTEH60418.2024.10495994

Explainable artificial intelligence for botnet detection in internet of things

Autoři: Mohamed Saied Shawkat Guirguis

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-17 (2025)

Témata: Internet of things, Machine learning, Cyber security, Botnet detection, Explainable artificial intelligence, Medicine, Science

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2045-2322

Přístupová URL adresa: https://doaj.org/article/dcbe437980f14853bd5b5a2968a4044f

Meta‐analysis and systematic review for anomaly network intrusion detection systems: Detection methods, dataset, validation methodology, and challenges

Autoři: Ziadoon Kamil Maseer Qusay Kanaan Kadhim Baidaa Al‐Bander a další

Zdroj: IET Networks, Vol 13, Iss 5-6, Pp 339-376 (2024)

Témata: FOS: Computer and information sciences, Artificial intelligence, Computer Science - Cryptography and Security, Outlier Detection, Computer Networks and Communications, TK5101-6720, Systems and Control (eess.SY), Anomaly detection, Electrical Engineering and Systems Science - Systems and Control, Anomaly Detection in High-Dimensional Data, Traffic Analysis, Artificial Intelligence, computer network security, FOS: Electrical engineering, electronic engineering, information engineering, Anomaly-based intrusion detection system, Data mining, Intrusion detection system, Computer science, Intrusion Detection, Machine Learning for Internet Traffic Classification, Computer Science, Physical Sciences, Telecommunication, Network Intrusion Detection and Defense Mechanisms, Anomaly Detection, computer networks, Botnet Detection, Cryptography and Security (cs.CR)

Přístupová URL adresa: http://arxiv.org/abs/2308.02805
https://doaj.org/article/fb47601826e4494991980cd451b5df62

A Comprehensive Review of Machine Learning Approaches for Detecting Malicious Software

Autoři: Liu Yuanming Rodziah Latih

Zdroj: International Journal on Advanced Science, Engineering and Information Technology. 14:826-834

Témata: FOS: Computer and information sciences, Artificial intelligence, Computer Networks and Communications, Feature engineering, Variety (cybernetics), Malware, Leverage (statistics), Identification (biology), Characterization and Detection of Android Malware, Memory Analysis, Computer security, Machine learning, Digital Forensics Research and Challenges, Data mining, Biology, Botany, Deep learning, Computer science, Intrusion Detection, Process (computing), Programming language, 3. Good health, Detection, Operating system, Signal Processing, Computer Science, Physical Sciences, Network Intrusion Detection and Defense Mechanisms, Security Analysis, Botnet Detection, Software, Information Systems

A privacy-enhanced framework with deep learning for botnet detection

Autoři: Guangli Wu Xingyue Wang

Zdroj: Cybersecurity, Vol 8, Iss 1, Pp 1-14 (2025)

Témata: Botnet detection, Deep learning, Privacy enhancement, Federated learning, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2523-3246

Přístupová URL adresa: https://doaj.org/article/f07404329a6f4dd89af8486e259ba00f

Improving spam botnet detection through convolutional model and geolocation feature enhancement in a novel three-class classification task

Autoři: Florentino Benedictus Muhammad Aidiel Rachman Putra Tohari Ahmad a další

Zdroj: International Journal of Intelligent Networks, Vol 6, Iss , Pp 185-203 (2025)

Témata: Botnet detection, Convolutional neural network, Geolocation country mapping, Network infrastructure, Network security, Spam botnet, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2666603025000144; https://doaj.org/toc/2666-6030

Přístupová URL adresa: https://doaj.org/article/536468c4176d4ca6aad757a112df849d

SB-Net: A Novel Spam Botnet Detection Scheme With Two-Stage Cascade Learner and Ensemble Feature Selection

Autoři: Irsyad Fikriansyah Ramadhan Muhammad Aidiel Rachman Putra Ntivuguruzwa Jean De La Croix a další

Zdroj: IEEE Open Journal of the Communications Society, Vol 6, Pp 7237-7255 (2025)

Témata: Botnet detection, botnet spam, cyber security, machine learning classification, network security, network infrastructure, Telecommunication, TK5101-6720, Transportation and communications, HE1-9990

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/11142818/; https://doaj.org/toc/2644-125X

Přístupová URL adresa: https://doaj.org/article/c46fdc4c06014d1db099b5aaef0b7cf4

MLSTL-WSN: machine learning-based intrusion detection using SMOTETomek in WSNs

Autoři: Md. Alamin Talukder Selina Sharmin Md. Ashraf Uddin a další

Zdroj: International Journal of Information Security. 23:2139-2158

Témata: Computer Science - Machine Learning, Wireless Home Automation Systems, Artificial intelligence, Computer Science - Cryptography and Security, Computer Networks and Communications, 02 engineering and technology, Engineering, Computer security, 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Embedded system, Computer network, Sensors, Intrusion, Intrusion detection system, Geology, FOS: Earth and related environmental sciences, Security Challenges in Smart Grid Systems, Computer science, Intrusion Detection, Geochemistry, Control and Systems Engineering, Attack Detection, Computer Science, Physical Sciences, Network Intrusion Detection and Defense Mechanisms, Cryptography, Botnet Detection, Wireless sensor network

Přístupová URL adresa: http://arxiv.org/abs/2402.13277

MalBoT-DRL: Malware Botnet Detection Using Deep Reinforcement Learning in IoT Networks

Autoři: Mohammad Al-Fawa’reh Jumana Abu-Khalaf Patryk Szewczyk a další

Zdroj: IEEE Internet of Things Journal. 11:9610-9629

Témata: network traffic analysis, IoT botnet, bashlite, reinforcement learning, Computer Sciences, intrusion detection, Information Security, Mirai, Botnet detection, 02 engineering and technology, Torii, incremental statistics, Physical Sciences and Mathematics, 0202 electrical engineering, electronic engineering, information engineering, MalBoTDRL

Popis souboru: application/pdf