Intrusion Detection and Prevention Systems as a Service in Could-based Environment

Abstract

Intrusion Detection and Prevention Systems (IDPSs) are standalone complex hardware, expensive to purchase, change and manage. The emergence of Network Function Virtualization (NFV) and Software Defined Networking (SDN) mitigates these challenges and delivers middlebox functions as virtual instances. Moreover, cloud computing has become a very cost-effective model for sharing large-scale services in recent years. Features such as portability, isolation, live migration, and customizabil-ity of virtual machines for high-performance computing have attracted enterprise customers to move their in-house IT data center to the cloud. In this paper, we formulate the placement of Intrusion Detection and Prevention Systems (IDPS) and introduce a model called Incremental Mobile Facility Location Problem (IMFLP) to study the IDPP problem. Moreover, we propose a novel and efficient solution called Adaptive Facility Location (AFL) to efficiently solve the optimization problem introduced in the IMFLP model. The effectiveness of our solution is evaluated through realistic simulation studies compared with other popular online facility location algorithms.

Authors and Affiliations

Khalid Alsubhi, Hani Moaiteq AlJahdali

Keywords

Related Articles

Improvement of the Frequency Characteristics for RFID Patch Antenna based on C-Shaped Split Ring Resonator

In this paper, we present a new technique for improving frequency characteristics and miniaturizing the geometric dimension of the RFID patch antenna that operates in the SHF band. This technique consists in implementing...

MOMEE: Manifold Optimized Modeling of Energy Efficiency in Wireless Sensor Network

Although adoption pace of wireless sensor network has increased in recent times in many advance technologies of ubiquitous-ness, but still there are various open-end challenges associated with energy efficiencies among t...

Long-Term Weather Elements Prediction in Jordan using Adaptive Neuro-Fuzzy Inference System (ANFIS) with GIS Techniques

Weather elements are the most important parameters in metrological and hydrological studies especially in semi-arid regions, like Jordan. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is used here to predict the mini...

Firefly Algorithm for Adaptive Emergency Evacuation Center Management

Flood disaster is among the most devastating natural disasters in the world, claiming more lives and causing property damage. The pattern of floods across all continents has been changing, becoming more frequent, intense...

Constraints in the IoT: The World in 2020 and Beyond

The Internet of Things (IoT), often referred as the future Internet; is a collection of interconnected devices integrated into the world-wide network that covers almost everything and could be available anywhere. IoT is...

Download PDF file
  • EP ID EP358603
  • DOI 10.14569/IJACSA.2018.090738
  • Views 86
  • Downloads 0

How To Cite

Khalid Alsubhi, Hani Moaiteq AlJahdali (2018). Intrusion Detection and Prevention Systems as a Service in Could-based Environment. International Journal of Advanced Computer Science & Applications, 9(7), 271-280. https://europub.co.uk/articles/-A-358603