Design of Optimal Acceptance Sampling Plan for Network Intrusion Detection
C. MadhusudhanaRao
Dr. C.MadhusudhanaRao, Professor of CSSE, Centre for Computer Networks and Cyber Security, Sree Vidyanikethan Engineering, Tirupati, India
Manuscript received on October 14, 2019. | Revised Manuscript received on 23 October, 2019. | Manuscript published on November 10, 2019. | PP: 4379-4383 | Volume-9 Issue-1, November 2019. | Retrieval Number: A5064119119/2019©BEIESP | DOI: 10.35940/ijitee.A5064.119119
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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: Network Intrusion Detection Systems (NIDS) protects networks connected to the internet from malicious attacks by monitoring network flows predominantly at fragment level in network layer. Inspecting every fragment of a network flow is computationally prohibitive. The Acceptance Sampling for Network Intrusion Detection (ASNID) method avoids hundred percent inspections of fragments to detect anomalous flows. This study proposes a model to determine optimal acceptance sample size. Further, this study also proposes a model for estimating the cost of computational effort.
Keywords: Acceptance Sampling, Expected Total Cost, Expected Computational Effort, Geometric Mean Accuracy Index, Network Intrusion Detection.
Scope of the Article: Optimal Design of Structures