Suchergebnisse - "anomaly-based intrusion detection"

Anomaly-based detection of cyberattacks in smart homes

Autoren: Iturbe Araya, Juan Ignacio

Weitere Verfasser: University/Department: Universitat Oberta de Catalunya. Escola de Doctorat

Thesis Advisors: Rifà-Pous, Helena

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: llars intel·ligents, hogares inteligentes, smart homes, ciberseguretat, ciberseguridad, cybersecurity, detecció d´intrusos basada en anomalies, detección de intrusos basada en anomalías, anomaly-based intrusion detection, aprenentatge no supervisat, aprendizaje no supervisado, unsupervised learning, desbalance de classes, desbalance de clases, class imbalance, optimització d'hiperparàmetres, optimización de hiperparámetros, hyperparameters optimization, métricas de evaluación, mètriques d'avaluació, evaluation metrics, seguretat IoT, seguridad IoT, IoT security, conjunts de dades desbalancejades, conjuntos de datos desbalanceados, imbalanced datasets

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/695557

Anomaly-Based Intrusion Detection for IoMT Networks: Design, Implementation, Dataset Generation, and ML Algorithms Evaluation

Autoren: Georgios Zachos Georgios Mantas Kyriakos Porfyrakis et al.

Quelle: IEEE Access, Vol 13, Pp 41994-42028 (2025)

Schlagwörter: novelty detection algorithms, machine learning algorithms, Anomaly-based intrusion detection, intrusion detection system (IDS), dataset generation, Internet of Medical Things (IoMT), Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Zugangs-URL: https://doaj.org/article/da12a6725acd49a1b67f57d5730a8f7e

SoK of Machine Learning and Deep Learning Based Anomaly Detection Methods for Automatic Dependent Surveillance- Broadcast

Autoren: Nurşah Çevik Sedat Akleylek

Quelle: IEEE Access, Vol 12, Pp 35643-35662 (2024)

Schlagwörter: Aircraft, cyber security, Cyber Security, deep learning, 02 engineering and technology, Surveys, Ids, Anomaly Based Intrusion Detection System, Ads-B, Intrusion Detection, TK1-9971, Machine Learning, Databases, Deep Learning, Anomaly Detection System, anomaly based intrusion detection system, 0202 electrical engineering, electronic engineering, information engineering, Anomaly Detection, Avionics Security, Electrical engineering. Electronics. Nuclear engineering, anomaly detection system, avionics security, Computer Security, ADS-B, Intrusion Detection System

Zugangs-URL: https://doaj.org/article/103d5d9785a64ca5bd9b7738057e313a
https://hdl.handle.net/20.500.12713/5007

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

Autoren: Ziadoon Kamil Maseer Qusay Kanaan Kadhim Baidaa Al‐Bander et al.

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

Schlagwörter: 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)

Zugangs-URL: http://arxiv.org/abs/2308.02805
https://doaj.org/article/fb47601826e4494991980cd451b5df62

Review on Approaches of Federated Modeling in Anomaly-Based Intrusion Detection for IoT Devices

Autoren: Umar Audi Isma’ila Kamaluddeen Usman Danyaro Aminu Aminu Muazu et al.

Quelle: IEEE Access, Vol 12, Pp 30941-30961 (2024)

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, IoT devices, non-IDD data, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, aggregation function, Federated learning modeling, anomaly-based intrusion detection, TK1-9971

Zugangs-URL: https://doaj.org/article/1d62a996f05d41fb90ace1a2f6daa257

Scheduling to the Rescue; Improving ML-Based Intrusion Detection for IoT

Autoren: Mirzai, Aria Coban, Ali Zülfükar Almgren, Magnus et al.

Quelle: EUROSEC '23: Proceedings of the 16th European Workshop on System Security. May, 2023. EUROSEC ’23. :44-50

Schlagwörter: model training, anomaly-based intrusion detection system, user-level scheduling, internet of things

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-64430
https://doi.org/10.1145/3578357.3589460

Implementing Anomaly-Based Intrusion Detection for Resource-Constrained Devices in IoMT Networks

Autoren: Georgios Zachos Georgios Mantas Kyriakos Porfyrakis et al.

Quelle: Sensors ; Volume 25 ; Issue 4 ; Pages: 1216

Schlagwörter: anomaly-based intrusion detection, dataset generation, Internet of Medical Things (IoMT), intrusion detection system (IDS), machine learning algorithms, novelty detection algorithms, outlier detection algorithms

Dateibeschreibung: application/pdf

Relation: Sensor Networks; https://dx.doi.org/10.3390/s25041216

Verfügbarkeit: https://doi.org/10.3390/s25041216

A novel bi-anomaly-based intrusion detection system approach for industry 4.0

Autoren: Salwa Alem David Espes Laurent Nana et al.

Weitere Verfasser: Salwa Alem David Espes Laurent Nana et al.

Quelle: Future Generation Computer Systems. 145:267-283

Schlagwörter: [INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR], Cyber physical system (CPS), ISA-95 industrial standard, 0202 electrical engineering, electronic engineering, information engineering, Neural networks (NN), [INFO]Computer Science [cs], 02 engineering and technology, Anomaly-based intrusion detection system, Manufacturing executive system (MES)

Design of Anomaly Based Intrusion Detection System Using Support Vector Machine and Grasshopper Optimization Algorithm in IoT

Autoren: Sepehr Sharifi Soulmaz Gheisari

Quelle: مهندسی مخابرات جنوب, Vol 12, Iss 46, Pp 43-58 (2024)

Schlagwörter: grasshopper optimization algorithm, iot, support vector machine, anomaly-based intrusion detection, Telecommunication, TK5101-6720

Dateibeschreibung: electronic resource

Relation: https://sanad.iau.ir/journal/jce/Article/869978; https://doaj.org/toc/2980-9231

Zugangs-URL: https://doaj.org/article/680ff2357704492492bc02bd0b5e14d4

E2IDS: An Enhanced Intelligent Intrusion Detection System Based On Decision Tree Algorithm

Autoren: Mohamed Aly Bouke Azizol Abdullah Sameer Hamoud ALshatebi et al.

Quelle: Journal of Applied Artificial Intelligence. 3:1-16

Schlagwörter: Artificial intelligence, IoT Security, Computer Networks and Communications, Volume (thermodynamics), 02 engineering and technology, Quantum mechanics, Mathematical analysis, Anomaly Detection in High-Dimensional Data, Characterization and Detection of Android Malware, Artificial Intelligence, Machine learning, Decision tree, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Anomaly-based intrusion detection system, Data mining, Computational intelligence, Geography, Intrusion detection system, Physics, Computer science, Intrusion Detection, Process (computing), Algorithm, Detection, Operating system, Computer Science, Physical Sciences, Signal Processing, Feature selection, Computation, Tree (set theory), Network Intrusion Detection and Defense Mechanisms, Security Analysis, Botnet Detection, Benchmark (surveying), Geodesy, Mathematics

Cyber-Physical Cloud Security: Protecting Cloud-Connected Smart Infrastructure

Autoren: Satheesh Reddy Gopireddy

Schlagwörter: Smart Infrastructure Security, Anomaly-Based Intrusion Detection, Cloud-Connected Systems, Cyber-Physical Systems (CPS), Access Control Mechanisms

Defending the Digital Frontier: IDPS and the Battle Against Cyber Threat

Autoren: Hamza Azam Mohammad Irfan Dulloo Muhammad Hassan Majeed et al.

Quelle: International Journal of Emerging Multidisciplinaries: Computer Science & Artificial Intelligence. 2

Schlagwörter: Artificial intelligence, IoT Security, Computer Networks and Communications, Intrusion detection system, Rootkit, Anomaly detection, Network security, Computer science, Malware, Interdiction, Intrusion Detection, Anomaly Detection in High-Dimensional Data, Detection, Characterization and Detection of Android Malware, Engineering, Aerospace engineering, Artificial Intelligence, Computer security, Honeypot, Computer Science, Physical Sciences, Signal Processing, Network Intrusion Detection and Defense Mechanisms, Security Analysis, Anomaly-based intrusion detection system

Robust genetic machine learning ensemble model for intrusion detection in network traffic

Autoren: M. A. Akhtar Syed Muhammad Owais Qadri Maria Andleeb Siddiqui et al.

Quelle: Sci Rep
Scientific Reports, Vol 13, Iss 1, Pp 1-22 (2023)

Schlagwörter: Artificial intelligence, Data pre-processing, Computer Networks and Communications, Science, Article, Anomaly Detection in High-Dimensional Data, Characterization and Detection of Android Malware, Artificial Intelligence, Computer security, Ensemble learning, Machine learning, Anomaly-based intrusion detection system, Data mining, Constant false alarm rate, Preprocessor, Intrusion detection system, Network security, Computer science, Intrusion Detection, Network Security, Detection, Computer Science, Physical Sciences, Signal Processing, Network Intrusion Detection and Defense Mechanisms, Medicine, Security Analysis, Botnet Detection, Classifier (UML), Random forest

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/37821521
https://doaj.org/article/a0d4497a6acc4d82a7bbd8269bf31d7e

How Much Training Data is Enough? A Case Study for HTTP Anomaly-Based Intrusion Detection

Autoren: Rafael Estepa Jesus E. Diaz-Verdejo Antonio Estepa et al.

Weitere Verfasser: Rafael Estepa Jesus E. Diaz-Verdejo Antonio Estepa et al.

Quelle: idUS. Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
idUS: Depósito de Investigación de la Universidad de Sevilla
instname
Digibug. Repositorio Institucional de la Universidad de Granada
Universidad de Granada (UGR)
IEEE Access, Vol 8, Pp 44410-44425 (2020)

Schlagwörter: training, Anomaly-based intrusion detection, 0202 electrical engineering, electronic engineering, information engineering, Training, dataset assessment, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, Dataset assessment, TK1-9971, anomaly-based intrusion detection

Dateibeschreibung: application/pdf

Zugangs-URL: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09019687.pdf
https://hdl.handle.net/11441/107307
https://idus.us.es/handle//11441/107307
https://doaj.org/article/2f7d913325d544fb875361ead8d9d839
https://idus.us.es/handle/11441/107307
https://ieeexplore.ieee.org/document/9019687/
https://dblp.uni-trier.de/db/journals/access/access8.html#EstepaDEM20
http://hdl.handle.net/10481/61835
https://hdl.handle.net/10481/96323

A methodology for conducting efficient sanitization of HTTP training datasets

Autoren: Rafael Estepa Germán Madinabeitia Jesús E. Díaz-Verdejo et al.

Weitere Verfasser: Rafael Estepa Germán Madinabeitia Jesús E. Díaz-Verdejo et al.

Quelle: idUS. Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, Data acquisition, 02 engineering and technology, Anomaly based intrusion detection, Training datasets

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/11441/168066
https://www.sciencedirect.com/science/article/pii/S0167739X19322629
https://dblp.uni-trier.de/db/journals/fgcs/fgcs109.html#Diaz-VerdejoEEM20

Towards a better similarity algorithm for host-based intrusion detection system

Autoren: Ouarda Lounis Malika Bourenane Brahim Bouderah

Quelle: Journal of Intelligent Systems, Vol 32, Iss 1, Pp 55595-605 (2023)

Schlagwörter: Artificial intelligence, Outlier Detection, Computer Networks and Communications, Science, 68m25, system call sequences, Misuse detection, Pattern recognition (psychology), Anomaly Detection in High-Dimensional Data, Characterization and Detection of Android Malware, bsa-hids, Artificial Intelligence, Machine learning, jaro–winkler, Anomaly-based intrusion detection system, similarity, Constant false alarm rate, Data mining, Biology, adfa-ld, Ecology, Host (biology), Intrusion detection system, QA75.5-76.95, Computer science, levenshtein, zero-day attack, Intrusion Detection, Programming language, Algorithm, Detection, Electronic computers. Computer science, FOS: Biological sciences, Computer Science, Physical Sciences, Signal Processing, Network Intrusion Detection and Defense Mechanisms, Security Analysis, System call, Jaccard index, Botnet Detection

Zugangs-URL: https://doaj.org/article/180f54a9cfc1437faf5dc632ccbd8912

Anomaly-Based Intrusion Detection System To Detect Advanced Persistent Threats: Environmental Sustainability

Autoren: Oughannou Zahra El Rhadiouini Zakaria Chaoui Habiba et al.

Quelle: E3S Web of Conferences, Vol 412, p 01106 (2023)

Schlagwörter: apt, ids, anomaly-based intrusion detection, deep learning, environmental sustainability, sustainable cybersecurity practices, Environmental sciences, GE1-350

Relation: https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/49/e3sconf_icies2023_01106.pdf; https://doaj.org/toc/2267-1242; https://doaj.org/article/625f6b9bbfa64ff5b28e201db08d6ad6

Verfügbarkeit: https://doi.org/10.1051/e3sconf/202341201106
https://doaj.org/article/625f6b9bbfa64ff5b28e201db08d6ad6

Influence of pre-processing on anomaly-based intrusion detection / Роль предварительного процессирования при обнаружении атак, основанных на аномалиях / Uticaj preprocesuiranja na detekciju napada zasnovanih na anomalijama

Autoren: Danijela D. Protić

Quelle: Vojnotehnički Glasnik, Vol 68, Iss 3, Pp 598-611 (2020)

Schlagwörter: anomaly-based intrusion detection, machine learning, kyoto 2006+, обнаружение аномалий, машинное обучение, detekcija anomalija, mašinsko učenje, Military Science, Engineering (General). Civil engineering (General), TA1-2040

Dateibeschreibung: electronic resource

Relation: http://scindeks-clanci.ceon.rs/data/pdf/0042-8469/2020/0042-84692003598P.pdf; https://doaj.org/toc/0042-8469; https://doaj.org/toc/2217-4753

Zugangs-URL: https://doaj.org/article/672b050147b347168e87c134b38a7ebf

ENHANCING NETWORK SECURITY IN ANOMALY-BASED INTRUSION DETECTION SYSTEMS THROUGH ADAPTIVE NEURAL NETWORKS

Autoren: HASHIM MUZE ABDELA

Schlagwörter: Anomaly-based intrusion detection, Adaptive neural networks, Feature selection, Ensemble methods, Cybersecurity, Hyperparameter tuning, Network security.cre

A novel approach to intrusion detection using zero-shot learning hybrid partial labels

Autoren: Syed Atir Raza Shirazi Mehwish Shaikh Raybal Akhtar et al.

Quelle: Mehran University Research Journal of Engineering and Technology, Vol 43, Iss 1, Pp 182-191 (2024)

Schlagwörter: Exploit, Technology, Artificial intelligence, Outlier Detection, Computer Networks and Communications, Science, Feature (linguistics), 0211 other engineering and technologies, 02 engineering and technology, 7. Clean energy, Anomaly Detection in High-Dimensional Data, Characterization and Detection of Android Malware, Artificial Intelligence, Computer security, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Anomaly-based intrusion detection system, Data mining, Intrusion, Intrusion detection system, Linguistics, Geology, Network security, FOS: Earth and related environmental sciences, 15. Life on land, Engineering (General). Civil engineering (General), Computer science, Intrusion Detection, FOS: Philosophy, ethics and religion, 3. Good health, Detection, Philosophy, Geochemistry, Computer Science, Physical Sciences, Signal Processing, Network Intrusion Detection and Defense Mechanisms, FOS: Languages and literature, Security Analysis, TA1-2040, Botnet Detection

Zugangs-URL: https://doaj.org/article/091848848b8d4adaad0dbef1522045a5