Designing an efficient security framework for detecting intrusions in virtual network of cloud computing
Cloud computing has grown for various IT capabilities such as IoTs, Mobile Computing,
Smart IT, etc. However, due to the dynamic and distributed nature of cloud and …
Smart IT, etc. However, due to the dynamic and distributed nature of cloud and …
An improved design for a cloud intrusion detection system using hybrid features selection approach with ML classifier
The focus of cloud computing nowadays has been reshaping the digital epoch, in which
clients now face serious concerns about the security and privacy of their data hosted in the …
clients now face serious concerns about the security and privacy of their data hosted in the …
A comprehensive intrusion detection framework using boosting algorithms
Abstract Intrusion Detection Systems are one of the most effective technologies that protect
systems against cyber-attacks. In this study, a new Comprehensive Cyber Security Intrusion …
systems against cyber-attacks. In this study, a new Comprehensive Cyber Security Intrusion …
Data mining with big data in intrusion detection systems: A systematic literature review
Cloud computing has become a powerful and indispensable technology for complex, high
performance and scalable computation. The exponential expansion in the deployment of …
performance and scalable computation. The exponential expansion in the deployment of …
Building a cloud-IDS by hybrid bio-inspired feature selection algorithms along with random forest model
The adoption of cloud computing has become increasingly widespread across various
domains. However, the inherent security vulnerabilities of cloud computing pose significant …
domains. However, the inherent security vulnerabilities of cloud computing pose significant …
Analysis of Simple K-Mean and Parallel K-Mean Clustering for Software Products and Organizational Performance Using Education Sector Dataset
Context. Educational Data Mining (EDM) is a new and emerging research area. Data mining
techniques are used in the educational field in order to extract useful information on …
techniques are used in the educational field in order to extract useful information on …
Software Defect Prediction and Analysis Using Enhanced Random Forest (extRF) Technique: A Business Process Management and Improvement Concept in IOT …
FH Alshammari - Mobile Information Systems, 2022 - Wiley Online Library
Software defect prediction is a thriving study area in the realm of software engineering and
processing in the IOT‐based environment. Defect prediction creates a list of defective source …
processing in the IOT‐based environment. Defect prediction creates a list of defective source …
Establishment and mapping of heterogeneous anomalies in network intrusion datasets
L Riddell, M Ahmed, P Haskell-Dowland - Connection Science, 2022 - Taylor & Francis
Anomaly detection in the scope of network security aims to identify network instances for the
unexpected and unique, with various security operations employing such techniques to …
unexpected and unique, with various security operations employing such techniques to …
Ensemble classifier design tuned to dataset characteristics for network intrusion detection
Machine Learning-based supervised approaches require highly customized and fine-tuned
methodologies to deliver outstanding performance. This paper presents a dataset-driven …
methodologies to deliver outstanding performance. This paper presents a dataset-driven …
Towards Efficient Intrusion Detection Using Hybrid Data Mining Techniques
F Salo - 2019 - search.proquest.com
The enormous development in the connectivity among different type of networks poses
significant concerns in terms of privacy and security. As such, the exponential expansion in …
significant concerns in terms of privacy and security. As such, the exponential expansion in …