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المؤلفChkirbene, Zina
المؤلفHamila, Ridha
المؤلفErbad, Aiman
المؤلفKiranyaz, Serkan
المؤلفAl-Emadi, Nasser
المؤلفHamdi, Mounir
تاريخ الإتاحة2023-04-04T09:09:07Z
تاريخ النشر2021
اسم المنشور2021 International Wireless Communications and Mobile Computing, IWCMC 2021
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/IWCMC51323.2021.9498809
معرّف المصادر الموحدhttp://hdl.handle.net/10576/41620
الملخصCloud computing is attracting a lot of attention in the past few years. Although, even with its wide acceptance, cloud security is still one of the most essential concerns of cloud computing. Many systems have been proposed to protect the cloud from attacks using attack signatures. Most of them may seem effective and efficient; however, there are many drawbacks such as the attack detection performance and the system maintenance. Recently, learning-based methods for security applications have been proposed for cloud anomaly detection especially with the advents of machine learning techniques. However, most researchers do not consider the attack classification which is an important parameter for proposing an appropriate countermeasure for each attack type. In this paper, we propose a new firewall model called Secure Packet Classifier (SPC) for cloud anomalies detection and classification. The proposed model is constructed based on collaborative filtering using two machine learning algorithms to gain the advantages of both learning schemes. This strategy increases the learning performance and the system's accuracy. To generate our results, a publicly available dataset is used for training and testing the performance of the proposed SPC. Our results show that the accuracy of the SPC model increases the detection accuracy by 20% compared to the existing machine learning algorithms while keeping a high attack detection rate. 2021 IEEE
راعي المشروعACKNOWLEDGMENT This work was supported by Qatar University Internal Grant IRCC-2020-001. The statements made herein are solely the responsibility of the author[s].
اللغةen
الناشرIEEE
الموضوعCloud security
Firewalls
Intrusion detection systems
Machine learning techniques
Secure packet classifier
العنوانCooperative Machine Learning Techniques for Cloud Intrusion Detection
النوعConference Paper
الصفحات837-842


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