Evaluation of EWCDMCC Cloud Worm Detection Classification Based on Statistical Analysis

Kanaker, Hasan; Saudi, Madihah Mohd; Azman, Norhidayah

doi:10.1166/asl.2017.7377

Cited by 3 publications

(5 citation statements)

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“…Worm. A worm is a malicious program that can disrupt systems and applications by morphing their primary codes, causing those systems and applications to disintegrate and become unusable [2], [7]. It can multiply, infect, and spread without being attached to a host [8].…”

Section: Types Of Malwaresmentioning

confidence: 99%

“…As a result, it may occasionally fail to analyze unknown malware signatures that are not in its database. Static analysis is usually based on signatures, which must be updated on a regular basis and requires human expertise to produce new signatures [2], [7]. Due to the above reasons, it is not used in this research.…”

Section: Static Analysismentioning

confidence: 99%

“…VirusShare.com [2], [7], [38], [68] and VirusTotal [38], [69] have been used to obtain cloud trojan horse and benign samples. Virusshare is one of the internet's largest openly distributed virus repositories.…”

Section: Dataset Collectionmentioning

confidence: 99%

“…Furthermore, governments have become concerned about the potential of using cloud computing to decrease IT costs and increase the reachability of their delivered services [5], [6]. The cloud technology consists of a full range of IT infrastructures such as servers, applications, email, file storage, large resources, database and services, an available through a network, usually the Internet [7].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Trojan Horse Infection Detection in Cloud Based Environment Using Machine Learning

Kanaker¹,

Karim

Awwad

et al. 2022

Int. J. Interact. Mob. Technol.

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Cloud computing technology is known as a distributed computing network, which consists of a large number of servers connected via the internet. This technology involves many worthwhile resources, such as applications, services, and large database storage. Users have the ability to access cloud services and resources through web services. Cloud computing provides a considerable number of benefits, such as effective virtualized resources, cost efficiency, self-service access, flexibility, and scalability. However, many security issues are present in cloud computing environment. One of the most common security challenges in the cloud computing environment is the trojan horses. Trojan horses can disrupt cloud computing services and damage the resources, applications, or virtual machines in the cloud structure. Trojan horse attacks are dangerous, complicated and very difficult to be detected. In this research, eight machine learning classifiers for trojan horse detection in a cloud-based environment have been investigated. The accuracy of the cloud trojan horses detection rate has been investigated using dynamic analysis, Cukoo sandbox, and the Weka data mining tool. Based on the conducted experiments, the SMO and Multilayer Perceptron have been found to be the best classifiers for trojan horse detection in a cloud-based environment. Although SMO and Multilayer Perceptron have achieved the highest accuracy rate of 95.86%, Multilayer Perceptron has outperformed SMO in term of Receiver Operating Characteristic (ROC) area.

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Section: Types Of Malwaresmentioning

confidence: 99%

Section: Static Analysismentioning

confidence: 99%

Section: Dataset Collectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Trojan Horse Infection Detection in Cloud Based Environment Using Machine Learning

Kanaker¹,

Karim

Awwad

et al. 2022

Int. J. Interact. Mob. Technol.

View full text Add to dashboard Cite

show abstract

“…2. Worm virus 13 : It attacks the network through the vulnerabilities in the system, with a high degree of harm and high propagation speed. In addition to harming network hosts, it will also encroach on network resources.…”

Section: Abnormal Network Trafficmentioning

confidence: 99%

A study of detection of abnormal network traffic: A comparison of multiple algorithms

2021

Security and Privacy

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The detection of abnormal traffic in networks is of great value for maintaining network security. This article gives a brief introduction of abnormal traffic and compares the performance of three algorithms, the support vector domain description algorithm, the gradient boosting decision tree algorithm, and the extreme learning machine-k-nearest neighbor (ELM-KNN) algorithm. Experiments were carried out on the NSL-KDD dataset. It was found that the accuracies of the three algorithms were 0.8327, 0.8679, and 0.9468, the recall rates were 0.6764, 0.7236, and 0.8997, the F1-scores were 0.7898, 0.8364, and 0.9578, and the false alarm rates were 0.3236, 0.2764, and 0.1003. The running time of the ELM-KNN algorithm was far less than the other two algorithms. The experimental results verify the effectiveness of the ELM-KNN algorithm in abnormal network traffic detection. The ELM-KNN algorithm can be further promoted and applied in practice.

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Cloud Computing as Digital Technology - Definition, Models and Use in Enterprises

Bednarčíková¹

Proceedings of the 16th International Scientific Conference INPROFORUM. DIGITALIZATION.Society and Markets, Business and Publi

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Cloud computing (CC) is a digital technology of Industry 4.0 and, together with digitalization, they digitally transform business entities. CC consists of many physical computers connected via the Internet, or is a distributed computing technology over a network, and enables the provision of information technology resources such as servers, databases, storage, applications, and others. The technological model of CC includes models of providing services over the Internet (Software as a Service, Infrastructure as a Service, and Platform as a Service) and models of various deployment methods (public cloud, private cloud, hybrid cloud, community cloud, distributed cloud, and multicloud). The scientific article contains: a theoretical definition of CC technology and a comparison of its use and adoption in enterprises, pointing out expenses, providers, and advantages of CC.

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Evaluation of EWCDMCC Cloud Worm Detection Classification Based on Statistical Analysis

Cited by 3 publications

References 0 publications

Trojan Horse Infection Detection in Cloud Based Environment Using Machine Learning

Trojan Horse Infection Detection in Cloud Based Environment Using Machine Learning

A study of detection of abnormal network traffic: A comparison of multiple algorithms

Cloud Computing as Digital Technology - Definition, Models and Use in Enterprises

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