Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

5.8K
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
5.8K
Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

4.8K
An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
4.8K
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

152
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
152
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

711
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
711
Types of Errors: Detection and Minimization01:12

Types of Errors: Detection and Minimization

2.3K
Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...
2.3K
What is Climate?01:16

What is Climate?

18.8K
Climate refers to the prevailing weather conditions in a specific area over an extended period. As the saying goes, “Climate is what you expect. Weather is what you get.” Climate is influenced by geographic factors, such as latitude, terrain, and proximity to bodies of water.
18.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Developing sustainable system based on transformers algorithms to predict the Dubas insects diseases in palm leaves.

Frontiers in plant science·2025
Same author

Enhancing cybersecurity through autonomous knowledge graph construction by integrating heterogeneous data sources.

PeerJ. Computer science·2025
Same author

Computational Intelligence Based Recurrent Neural Network for Identification Deceptive Review in the E-Commerce Domain.

Computational intelligence and neuroscience·2022
Same author

Deep Learning Model for the Detection of Real Time Breast Cancer Images Using Improved Dilation-Based Method.

Diagnostics (Basel, Switzerland)·2022
Same author

Detecting and Analyzing Suicidal Ideation on Social Media Using Deep Learning and Machine Learning Models.

International journal of environmental research and public health·2022
Same author

Multi-Class Skin Lesion Classification Using a Lightweight Dynamic Kernel Deep-Learning-Based Convolutional Neural Network.

Diagnostics (Basel, Switzerland)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Sep 5, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

654

Artificial Intelligence Algorithm-Based Economic Denial of Sustainability Attack Detection Systems: Cloud Computing

Theyazn H H Aldhyani1, Hasan Alkahtani2

  • 1Applied College in Abqaiq, King Faisal University, P.O. Box 400, Al-Ahsa 31982, Saudi Arabia.

Sensors (Basel, Switzerland)
|July 9, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces artificial intelligence methods to detect and mitigate economic denial of sustainability (EdoS) attacks in cloud computing. The random forest algorithm achieved 98% accuracy, outperforming existing systems.

Keywords:
cloud computingdeep learning approacheseconomic denial of sustainability attackintrusion detection systemmachine learning approaches

More Related Videos

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.1K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.8K

Related Experiment Videos

Last Updated: Sep 5, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

654
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.1K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.8K

Area of Science:

  • Cloud Computing Security
  • Cybersecurity
  • Artificial Intelligence in IT

Background:

  • Cloud computing offers cost-effective IT services but is vulnerable to new threats.
  • Economic Denial of Sustainability (EdoS) attacks exploit the pay-per-use model, causing unexpected charges for cloud customers.
  • Existing detection methods for distributed attacks on cloud grids are being enhanced.

Purpose of the Study:

  • To present an effective approach for mitigating EdoS attacks in cloud computing environments.
  • To evaluate the performance of various machine and deep learning algorithms for EdoS attack detection.
  • To improve the security systems of cloud computing service providers against EdoS threats.

Main Methods:

  • Implemented and tested several machine learning and deep learning algorithms: Support Vector Machine (SVM), K-nearest Neighbors (KNN), Random Forest (RF), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM).
  • Utilized a dataset of nine injection attacks from the University of New South Wales (UNSW) Cyber Range Lab.
  • Conducted experiments using binary classification (normal vs. attack) and multi-classification (nine attack types) with statistical analyses including Mean Square Error (MSE), Pearson Correlation Coefficient (R), and Root Mean Square Error (RMSE).

Main Results:

  • The Random Forest (RF) algorithm achieved 98% accuracy in binary classification and an R-squared value of 92.02%.
  • The Support Vector Machine (SVM) model demonstrated 97.54% accuracy in multi-classification.
  • The RF algorithm showed a low prediction error (MSE = 0.01465) and outperformed existing EdoS detection systems.

Conclusions:

  • Artificial intelligence-based algorithms are effective in detecting and mitigating EdoS attacks in cloud computing.
  • The proposed RF and SVM models offer high accuracy and low false alarm rates, enhancing cloud security.
  • This research provides a robust framework for identifying and neutralizing EdoS threats, ensuring service sustainability.