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Calibration Factors based intrusion detection (CFID) in Cloud Computing
Ponnuru. Sowjanya1, K. V. N. Sunitha2
1Ponnuru. Sowjanya, Research Scholar, JNTUH, Hyderabad, (Telangana), India.
2K. V. N. Sunitha, BVRIT Hyderabad College of Engineering for Women, Hyderabad, (Telangana), India. 

Manuscript received on February 01, 2019. | Revised Manuscript received on February 14, 2019. | Manuscript published on August 30, 2019. | PP: 3748-3757 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9385088619/19©BEIESP | DOI: 10.35940/ijeat.F9385.088619
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The distributed computing is the buzz in recent past, cloud computing stands first in this category. This is since, the users can adapt anything related to data storage, magnificent computing facilities on a system with less infrastructure from anywhere at any time. On other dimension such public and private cloud computing strategies would also attracts the foul players to perform intrusion practices. This is since, the comfortability that the cloud platform providing to end users intends them to adapt these services in regard to save or compute the sensitive data. The scope of vulnerability to breach the data or services over cloud computing is more frequent and easier, which is since, these services relies on internet protocol. In this regard, the research in intrusion detection defense mechanisms is having prominent scope. This manuscript, projecting a novel intrusion detection mechanism called “calibration factors-based intrusion detection (CFID)” for cloud computing networks. The experimental study portrayed the significant scope of the proposal CFID to detect the intrusion activities listed as remote-to-Local, Port Scanning, and Virtual-Machine-Trapping.
Keywords: Calibration factors-based intrusion detection (CFID), Cloud computing (CC), Cloud services (CS), IDC (International Data Corporation), ANN (artificial neural networks).