A Cloud Intrusion Detection System Using Novel PRFCM Clustering and KNN Based Dempster-Shafer Rule

2016 ◽  
Vol 6 (4) ◽  
pp. 18-35 ◽  
Author(s):  
Partha Ghosh ◽  
Shivam Shakti ◽  
Santanu Phadikar
Keyword(s):  
Cloud Computing ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Clustering Algorithm ◽  
Detection System ◽  
Cloud Environment ◽  
Dempster Shafer Theory ◽  
Computing Paradigm ◽  
Rule Set ◽  
Shafer Theory

Cloud computing has established a new horizon in the field of Information Technology. Due to the large number of users and extensive utilization, the Cloud computing paradigm attracts intruders who exploit its vulnerabilities. To secure the Cloud environment from such intruders an Intrusion Detection System (IDS) is required. In this paper the authors have proposed an anomaly based IDS which classifies an incoming connection by taking the deviation of it from the normal behaviors. The proposed method uses a novel Penalty Reward based Fuzzy C-Means (PRFCM) clustering algorithm to generate a rule set and the best rule set is extracted from it using a modified approach for KNN algorithm. This best rule set is used in evidential reasoning of Dempster Shafer Theory for classification. The IDS has been trained and tested with NSL-KDD dataset for performance evaluation. The results prove the proposed IDS to be highly efficient and reliable.

scholarly journals Proposed Network Intrusion Detection System ‎In Cloud Environment Based on Back ‎Propagation Neural Network

2017 ◽  
Vol 26 (1) ◽  
pp. 29-40 ◽  
Author(s):  
Shawq Malik Mehibs ◽  
Soukaena Hassan Hashim
Keyword(s):  
Neural Network ◽  
Cloud Computing ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Back Propagation ◽  
Network Intrusion Detection ◽  
Cloud Environment ◽  
High Detection Rate ◽  
Network Intrusion

Cloud computing is distributed architecture, providing computing facilities and storage resource as a service over the internet. This low-cost service fulfills the basic requirements of users. Because of the open nature and services introduced by cloud computing intruders impersonate legitimate users and misuse cloud resource and services. To detect intruders and suspicious activities in and around the cloud computing environment, intrusion detection system used to discover the illegitimate users and suspicious action by monitors different user activities on the network .this work proposed based back propagation artificial neural network to construct t network intrusion detection in the cloud environment. The proposed module evaluated with kdd99 dataset the experimental results shows promising approach to detect attack with high detection rate and low false alarm rate

scholarly journals A Design of an Integrated Cloud-based Intrusion Detection System with Third Party Cloud Service

2021 ◽  
Vol 11 (1) ◽  
pp. 365-379
Author(s):  
Wisam Elmasry ◽  
Akhan Akbulut ◽  
Abdul Halim Zaim
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Cloud Service ◽  
Third Party ◽  
Traffic Flows ◽  
Cloud Environment ◽  
System Service ◽  
Reporting Service ◽  
Bagging Ensemble

Abstract Although cloud computing is considered the most widespread technology nowadays, it still suffers from many challenges, especially related to its security. Due to the open and distributed nature of the cloud environment, this makes the cloud itself vulnerable to various attacks. 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. The proposed CIDS consists of five main modules to do the following actions: monitoring the network, capturing the traffic flows, extracting features, analyzing the flows, detecting intrusions, taking a reaction, and logging all activities. Furthermore an enhanced bagging ensemble system of three deep learning models is utilized to predict intrusions effectively. Moreover, a third-party Cloud-based Intrusion Detection System Service (CIDSS) is also exploited to control the proposed CIDS and provide the reporting service. Finally, it has been shown that the proposed approach overcomes all problems associated with attacks on the cloud raised in the literature.

scholarly journals Effective Intrusion Detection System by using LOS Classifier

2019 ◽  
Vol 9 (2) ◽  
pp. 2961-2966
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Intrusion Detection ◽  
Social Networking ◽  
Intrusion Detection System ◽  
Detection System ◽  
Learning Approaches ◽  
Area Unit ◽  
Hybrid Development

With winning advances like catch of Things, Cloud Computing and Social Networking, mammoth proportions of framework traffic associated information area unit made Intrusion Detection System for sort out security suggests the strategy to look at partner unapproved access on framework traffic. For Intrusion Detection System we are going to call attention to with respect to Machine Learning Approaches. it's accomplice rising field of enrolling which can explicitly act with a decent arrangement of less human affiliation. System gains from the data intentionally affirmation and makes perfect objectives. all through this paper we keep an eye on zone unit going to separated styles of Machine Learning pulls in near and had done relative examination in it. inside the last we keep an eye on territory unit going to foreseen the idea of hybrid development, that might be a blend of host principally and framework based for the most part Intrusion Detection System.

scholarly journals An Efficient Hybrid Multilevel Intrusion Detection System in Cloud Environment

2014 ◽  
Vol 16 (4) ◽  
pp. 16-26 ◽  
Author(s):  
Partha Ghosh ◽  
◽  
Chameli Debnath ◽  
Dipjyoti Metia ◽  
Dr. Ruma Dutta
Keyword(s):  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Cloud Environment
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