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IDS Based threat monitoring in Cloud Computing
2022
International Journal of Scientific Research in Computer Science Engineering and Information Technology
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Our solution's goal is to combine information from Intrusion Detection Systems (IDS) implemented in cloud services with risk evaluation data for each attack scenario. ...
Our approach proposes a new qualitative technique for examining each symptom, indication, and risk in order to determine the impact and likelihood of distributed and multi-step attacks against cloud systems ...
Figure 1 Attack Mechanism We developed a new intrusion detection approach based on risk assessment in our prior work [7] , with the goal of introducing the data owner and cloud provider. ...
doi:10.32628/cseit228110
fatcat:on6zp7kjzzae7ljpndsvdj3lf4
Intrusion Detection System – A Study
2015
International Journal of Security Privacy and Trust Management
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Intrusion Detection System (IDS) is meant to be a software application which monitors the network or system activities and finds if any malicious operations occur. ...
This main objective of this paper is to provide a complete study about the definition of intrusion detection, history, life cycle, types of intrusion detection methods, types of attacks, different tools ...
Host based IDS views the sign of intrusion in the local system. For analysis they use host system's logging and other information. Host based handler is referred as sensor. ...
doi:10.5121/ijsptm.2015.4104
fatcat:fdabcimrarbmpfwsifmhdxi2ni
A Design of an Integrated Cloud-based Intrusion Detection System with Third Party Cloud Service
2021
Open Computer Science
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In this paper, the design of a novel integrated Cloud-based Intrusion Detection System (CIDS) is proposed to immunise the cloud against any possible attacks. ...
Moreover, a third-party Cloud-based Intrusion Detection System Service (CIDSS) is also exploited to control the proposed CIDS and provide the reporting service. ...
Conflict of Interests: The authors declare that there is no conflict of interest regarding the publication of this paper. ...
doi:10.1515/comp-2020-0214
fatcat:6irhsmvdp5hzxetwcrt5dorake
INCREMENTAL LEARNING FOR EDGE NETWORK INTRUSION DETECTION
2023
Revue Roumaine des Sciences Techniques - Serie Electrotechnique et Energetique
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The paper presents incremental learning as a solution for adapting intrusion detection systems to the dynamic edge network conditions. ...
A mechanism based on unsupervised learning that triggers retraining of the XGBoost classifier is suggested. ...
ACKNOWLEDGEMENTS The results presented in this article have been funded by the Ministry of Investments and European Projects through the Human Capital Sectoral Operational Program 2014-2020, Contract no ...
doi:10.59277/rrst-ee.2023.3.9
fatcat:ug7teek7s5ae7d5jtqfz7ta3ae
Chaotic Metaheuristics with Multi-Spiking Neural Network Based Cloud Intrusion Detection
2023
Computers Materials & Continua
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Intrusion Detection Systems (IDSs) can be used in a network to manage suspicious activities. ...
In the current study, a Chaotic Metaheuristics with Optimal Multi-Spiking Neural Network-based Intrusion Detection (CMOMSNN-ID) model is proposed to secure the cloud environment. ...
Network traffic analysis in cloud networks is one of the most significant tasks in cloud management. ...
doi:10.32604/cmc.2023.033677
fatcat:bkm4pmysp5bvbatbuuu4hft4qi
CLOUD COMPUTING SECURITY ISSUES AND RESEARCH CHALLENGES FROM DDOS ATTACKS USING INTRUSION DETECTION SYSTEM
2017
Zenodo
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Research on recent DDoS attacks and a comparison of the major cloud-based DDoS defence systems are presented in this article. ...
Nowadays, the Internet community faces a distributed denial of service (DDoS) attack scenario. IDSs have become a critical part of protecting systems and networks from intrusions. ...
Using an Intrusion Detection System (IDS) like SNORT is one of the most effective mechanisms for detecting and preventing DDoS. ...
doi:10.5281/zenodo.6685637
fatcat:eg2jfl2rtfa7lozgoxpvshkdqi
A novel time efficient learning-based approach for smart intrusion detection system
2021
Journal of Big Data
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Background The ever increasing sophistication of intrusion approaches has led to the dire necessity for developing Intrusion Detection Systems with optimal efficacy. ...
An in-depth analysis of network parameters is also performed, which gives a deep insight into the variation of network parameters during the benign and malicious sessions. ...
[22] proposed a real-time intrusion detection system based on a parallel intrusion detection mechanism and LightGBM. ...
doi:10.1186/s40537-021-00498-8
fatcat:n7haycf4izfnlhf3zakiija52u
Anomaly Detection Framework in Fog-to-Things Communication for Industrial Internet of Things
2022
Computers Materials & Continua
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An anomaly-based Intrusion Detection System (IDS) can be an effective security solution for maintaining the confidentiality, integrity, and availability of data transmitted in IIoT environments. ...
In this paper, we propose an intelligent anomalybased IDS framework in the context of fog-to-things communications to decentralize the cloud-based security solution into a distributed architecture (fog ...
The anomaly detection system at the fog layer will alert any detected anomalies and pass the traffic to the cloud for further security analysis. ...
doi:10.32604/cmc.2022.029283
fatcat:3cejvnpssjgrlpkdmol6bxyg7y
A Consistent Augmented Stacking Polynomial Optimized Tool (ASPOT) for Improving Security of Cloud-IoT Systems
2024
Journal of Advanced Research in Applied Sciences and Engineering Technology
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processing costs, and system load. ...
Hence, the proposed work aims to develop an innovative and lightweight Augmented Stacking Polynomial Optimized Tool (ASPOT) for strengthening the cloud-IoT system security against modern cyberattacks with ...
Journal of Advanced Research in Applied Sciences and Engineering Technology Volume 37, Issue 1 (2024) ...
doi:10.37934/araset.37.1.1636
fatcat:mcyuiigqgja33nl5fdh4g5fvb4
An efficient intrusion detection mechanism based on particle swarm optimization and KNN
2020
ACCENTS Transactions on Information Security
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In this paper an efficient intrusion detection mechanism based on particle swarm optimization and KNN has been presented. ...
In our approach experimentation has been performed for the intrusion detection considering NSL-KDD dataset. ...
Conflicts of interest The authors have no conflicts of interest to declare. ...
doi:10.19101/tis.2020.517003
fatcat:ibnw5qeb2rehrepshjlgtd76na
SIMAD: Secure Intelligent Method for IoT-Fog Environments Attacks Detection
2022
Computers Materials & Continua
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In addition, the ever-evolving hacking techniques and methods and the expanded risks surfaces have demonstrated the importance of attacks detection systems. ...
We evaluated the performance of our distributed approach with the application of certain machine learning mechanisms. ...
Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study. ...
doi:10.32604/cmc.2022.020141
fatcat:syrdpfxvzjdwlkiiay2cm6qpce
Securing Fog-to-Things Environment Using Intrusion Detection System Based On Ensemble Learning
[article]
2019
arXiv
pre-print
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In this vein, the Intrusion detection systems (IDS) have emerged as a viable solution for the detection and prevention of malicious activities. ...
Unlike the signature-based detection approaches, machine learning-based solutions are a promising means for detecting unknown attacks. ...
Our deployment architecture is illustrated in Fig. 5 . This architecture provides a faster intrusion detection system with attack classification for efficient prevention mechanisms. ...
arXiv:1901.10933v1
fatcat:uxpqfkthozfs5mlswomgdmij4u
Cyberattacks Detection in IoT-Based Smart City Applications Using Machine Learning Techniques
2020
International Journal of Environmental Research and Public Health
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Contrary to existing works that have focused on single classifiers, we also explore ensemble methods such as bagging, boosting and stacking to enhance the performance of the detection system. ...
In this paper, we explore an attack and anomaly detection technique based on machine learning algorithms (LR, SVM, DT, RF, ANN and KNN) to defend against and mitigate IoT cybersecurity threats in a smart ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/ijerph17249347
pmid:33327468
pmcid:PMC7764956
fatcat:syieikibrvfexjbpg7u5nzf5hm
Multi-layer Cooperative Intrusion Detection System for Cloud Environment
2017
Proceedings of the 14th International Joint Conference on e-Business and Telecommunications
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After discussing existing Intrusion Detection Systems, deployed for Cloud Computing, we propose, in this paper, an approach that is based on cooperative and distributed intrusion detection, where a Cooperative ...
In recent years, Cloud Computing had met a rapid development and an increasing popularity that have boosted the rate of its adoption. ...
To enhance the way of detecting intrusions in the cloud networks, we propose a cooperative intrusion detection approach using agents deployed in each layer of the cloud network. ...
doi:10.5220/0006427100360044
dblp:conf/winsys/GhribiMZ17
fatcat:3hjskr2m3vc7zls6xsyulqa6ri
Cloud Computing And Its Security Measures
2020
International journal of electronics engineering and application
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In this paper we have made a detail study of the security measures required for the cloud service provider as well as the cloud client. ...
In today's world, Cloud Computing is essentially one of the most well -known and on-demand technologies offered by the IT sectors. ...
The various intrusion detection methodologies used by the Intrusion detection system are: • Signature-based intrusion detection • Anomalies based intrusion detection • Stateful protocol analysis Cloud ...
doi:10.30696/ijeea.viii.i.2020.10-19
fatcat:bre3ndirvzal5m3r5schywp65y
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