Cloud Network Anomaly Detection Using Machine and Deep Learning Techniques-Recent Research Advancements

A Abdallah, A Alkaabi, G Alameri, SH Rafique… - IEEE …, 2024 - ieeexplore.ieee.org
In the rapidly evolving landscape of computing and networking, the concepts of cloud
networks have gained significant prominence. Although the cloud network offers on-demand …

A better and fast cloud intrusion detection system using improved squirrel search algorithm and modified deep belief network

N Sarkar, PK Keserwani, MC Govil - Cluster Computing, 2024 - Springer
Utilizing the cloud environment is one of the most preferable option in every information
technology (IT) organization for running its business due to its flexible nature of services for …

Secure deep learning framework for cloud to protect the virtual machine from malicious events

V Kumar, Shaheen, D Rajani… - Wireless Personal …, 2023 - Springer
In recent decades, user communication has been digitalized with some advanced
applications. However, securing the digital cloud system is complicated because of the …

A consistent augmented stacking polynomial optimized tool (ASPOT) for improving security of cloud-IoT systems

D Ramachandran, R Chithambaramani… - … in Applied Sciences …, 2024 - semarakilmu.com.my
The cloud computing transforms information technology by offering end users simulated,
flexible resources on demand that require fewer resources and facilities giving them greater …

A bizarre synthesized cascaded optimized predictor (BizSCOP) model for enhancing security in cloud systems

RJ Menezes, PJ Jayarin, AC Sekar - Journal of Cloud Computing, 2024 - Springer
Due to growing network data dissemination in cloud, the elasticity, pay as you go options,
globally accessible facilities, and security of networks have become increasingly important …

Adaptive cloud intrusion detection system based on pruned exact linear time technique

W Elbakri, MM Siraj, BAS Al-rimy, SN Qasem… - Computers, Materials …, 2024 - irep.ntu.ac.uk
Cloud computing environments, characterized by dynamic scaling, distributed architectures,
and complex workloads, are increasingly targeted by malicious actors. These threats …

SAutoIDS: A semantic autonomous intrusion detection system based on cellular deep learning and ontology for malware detection in cloud computing

ARG Nazoksara, NS Etminan, R Hosseinzadeh - 2024 - researchsquare.com
Cloud computing (CC) is an online technology that has attracted the attention of many users
and organizations today. Users send their requests through mobile to CC to perform a …

Stacking Ensemble-Based Approach for Malware Detection

S Das, A Garg, S Kumar - SN Computer Science, 2024 - Springer
The rapid growth of Internet connectivity has resulted in a significant increase in digital
attack events, many of which have devastating and severe consequences. Malware is one …

Multi-Fractal Trusted Gradient Regressive Deep Multilayer Perceptron Classifier for Intrusion Detection in Cloud

S Priya, RS Ponmagal - 2023 Third International Conference on …, 2023 - ieeexplore.ieee.org
Cloud Computing is an optimistic model which comprises several classes of unlimited
computing services in isolated users in the Internet. Owing the dispersed scenery of CC …

FLOLSTM: Fuzzy logic‐driven optimized LSTM for improved malicious traffic detection in hypervisor environments

ANS Kumar, RK Yadav, NS Raghava - Concurrency and Computation … - Wiley Online Library
In the ever‐evolving realm of cloud computing, the challenge of intrusion detection has
grown increasingly intricate and vital. With the proliferation of cyber‐attacks and the …