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The mLearning Security Rule Base System with Social Network on eCampus: A Case Study of North-Chiang Mai University. Sarawut Ramjan, North-Chiang Mai University. Introduction. Government agency created new act for overcome education divide in Thailand

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Sarawut ramjan north chiang mai university

The mLearning Security Rule Base System with Social Network on eCampus: A Case Study of North-Chiang Mai University

Sarawut Ramjan, North-Chiang Mai University


Introduction
Introduction

  • Government agency created new act for overcome education divide in Thailand

  • Private university in Thailand expand sub campus to other area-NCU

  • They intend to set up a virtual class room for the driving an education standard equal to main campus

  • Social network on mLearning system is trendy solution


Introduction1
Introduction

  • Unfortunately, they face with mobile threat and problem on vulnerability points; student, lecturer and network technician on mobility environment

  • They have a high investment for protect system themselves

    • They lack skill for finding security solution

    • They have new characteristic ; joining between sub and main campus with social network on mobility system

    • They have various social network type that difference feature style such as mobile facebook, mobile twitter and new release ; mobile google+


The security model risk management in ncu
The security model-Risk management in NCU

  • NIST standard-free guideline

  • System characterization

    • ISP

    • Social network

    • Wireless communication provider

    • Student, lecturer, technician

  • Threat identification

  • Vulnerability identification


The security model risk management in ncu1
The security model-Risk management in NCU

  • Likelihood level = vulnerable point + threat

    • Low

    • Medium

    • High

  • Impact level = Confidentiality+ Availability +Integrity

    • Low

    • Medium

    • High


The security model risk management in ncu2
The security model-Risk management in NCU

  • Risk level = likelihood level + impact level

  • Control recommendation