Enhancing intrusion detection: a hybrid machine and deep learning approach

Journal of Cloud Computing Advances Systems and Applications, Год журнала: 2024, Номер 13(1)

Опубликована: Июль 17, 2024

Abstract The volume of data transferred across communication infrastructures has recently increased due to technological advancements in cloud computing, the Internet Things (IoT), and automobile networks. network systems transmit diverse heterogeneous dispersed environments as technology develops. communications using these networks daily interactions depend on security provide secure reliable information. On other hand, attackers have their efforts render susceptible. An efficient intrusion detection system is essential since embark new kinds attacks limitations. This paper implements a hybrid model for Intrusion Detection (ID) with Machine Learning (ML) Deep (DL) techniques tackle proposed makes use Extreme Gradient Boosting (XGBoost) convolutional neural (CNN) feature extraction then combines each long short-term memory (LSTM) classification. Four benchmark datasets CIC IDS 2017, UNSW NB15, NSL KDD, WSN DS were used train binary multi-class With increase dimensions, current trouble identifying threats low test accuracy scores. To narrow down dataset’s space, XGBoost, CNN selection algorithms are this work separate model. experimental findings demonstrate high rate good relatively False Acceptance Rate (FAR) prove usefulness

Язык: Английский

Opti-FOG: Optimizing Resource Allocation With Anti-Inspired FOG Node Selection

IEEE Access, Год журнала: 2024, Номер 12, С. 85355 - 85375

Опубликована: Янв. 1, 2024

Язык: Английский

Internet of things based smart framework for the safe driving experience of two wheelers

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Сен. 18, 2024

Язык: Английский