The mLearning Security Rule Base System
with Social Network on eCampus: A Case
Study of North-Chiang Mai University
Sarawut Ramjan
Department of e-Commerce Management, Faculty of Science and Technology,
North-Chiang Mai University, Thailand
sarawutr@northcm.ac.th
Abstract - Private University in Thailand
intends to overcome the education divide
problem by expanding the sub campus to
other area. The mLearning is useable to
content exchange between subs with main
campus
under
social
network
environment.
Unfortunately,
this
technology and social network features
can be bombarded from wireless threat
and problem on vulnerability point;
student, lecturer and network technician.
Therefore, those universities aware to
finding a security solution that is suitable
with each characteristic themselves. Thus,
this paper desire to demonstrated the
security rule base system that can be used
for searching the security control which
appropriate with each operational style of
each university who establish sub campus
which rely on social network over
mLearning infrastructure for link
eClassroom system with main campus.
Moreover, this document exemplifies a
case study of North-Chiang Mai
University for the content reviewing and
supporting the m-Learning security rule
base system with social network model.
Keywords - mLearning and eCampus,
Rule Base, Security, Social network
I. INTRODUCTION
At present, Thai government agency
created new education act regarding to the
university
outside
main
location
establishment [1]. Therefore, private
university in Thailand can grab this
opportunity for overcome the digital divide
problem. They expand sub campus in to area
where underdeveloped concerning to higher
education. In order to construct the education
quality in sub campus equal to main campus,
this intend to employ mLearning on social
network which trendy and cheapness for
drive eClassroom at sub campus to join with
main campus [3] [4]. This activity can
improve the quality level at sub campus as
same as main campus. mLearning on social
network necessary to be provided from
wireless network infrastructure in 3G
environment.
For
concentrated,
this
infrastructure involving with concerning
party; student, lecturer and network
technician at University, internet service
provider and wireless communication
provider that aid working between each other
for operated the social network on mLearning system as show in figure below:
Fig.1 mLearning environment at NCU with Nong
Khai international campus
From figure above, this paper can
discover that they have vulnerability points
which can be attracted from mobility threat
and problem. Accordingly, Thai universities
realize for this problem that they prepare
security solution for a protecting in each
weak point of mLearning infrastructure on
social network channel. For high security,
they must invest on various security controls
for a preventing in each vulnerability point.
Therefore, this document intend to analysis
the m-Learning security rule base system
with social network on eCampus that can be
The Eighth International Conference on eLearning for Knowledge-Based Society, 23-24 February 2012, Thailand
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Sarawut Ramjan
useable to filter the security control which
appropriated with each characteristic of
university and social network. In additional,
this model can be employed for university
considering about mLearning security
investment
under
social
network
environment.
For specification, this paper focuses on
real case study that is North-Chiang Mai
University: NCU where constructed the sub
campus that call Nong Khai International
campus. In order to foundation the element
of education at Nong Khai campus that
strong equal to NCU main campus, NCU
intend to rely mLearning system and several
types of social network mobile application
such as facebook, twitter or google+ that
new release to social network industry [5]
[6]. Unfortunate, NCU also faces with threat
and problem on mLearning and social
network channels both. Thus, they try to
striving from cyber grave by the relying on
technological solution and policy that
according to operational style of NCU which
collaborative with Nong Khai campus.
Hence, this is best real case for bring up to
example for constructing the security rule
base system that help university for analysis
security control which suitable on mobile
social network class room between sub and
main campus.
II. THE M-LEARNING SECURITY
RULE BASE SYSTEM ON SOCIAL
NETWORK
In order to save cost of m-Learning on
social network investment, this section will
be created the rule base system that can be
useable to finding a technological solution
that appropriated with each operational style
of each university. This model employ NIST
800-30 standard that is useable to guide the
university for the evaluated the risk degree of
mLearning system themselves [2]. This risk
analysis model can apply to rule base system
that filters the vulnerability point from
mLearning system and social network
feature characterization. Rule base model
analyzed the security solution that
organization provide for protect on
mLearning
system.
This
standard
recommend concerning to the threat
identification in order to considering the
attack motivation.
From movement above, this model can
analysis the likelihood determination and
impact analysis that compromised analysis to
risk degree which is recommended or
reported connecting with technological
solution and policy that appropriated with
each characteristic of each university who
employ social network feature on mLearning
system for join sub and main campus for one
virtual class room and eCampus. For
efficiency demonstrated the security rule
base model, this paper will guide by NCU
process that set up full mLearning system on
social network feature. Therefore, this figure
is illustrated for a display and focus below:
Special Issue of the International Journal of the Computer, the Internet and Management, Vol. 19 No. SP2, February, 2012
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The mLearning Security Rule Base System with Social Network on eCampus: A Case Study of North-Chiang Mai University
Fig.2 NCU mLearning security rule base system on social network
From illustrated above, this paper
employ NIST standard which is appropriate
with small application similar to social
network system that operated on mobile
device. This guideline is decency to run the
risk level of NCU mLearning security. In
order to concentrated, this section will be
narrated concerning to the rule base model as
step following:
First step, mLearning security rule base
system gathers information from sub and
main campus that integrated for created
virtual class room on mobility device. This
step uses various techniques for the data
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Sarawut Ramjan
colleting which are questionnaire, interview,
experiment and observation that cover on
sub and main campus of NCU in point of
system related information and operational
information of social network mLearning.
Second step, there are three activities
including with security providing, the
attacker’s motivation from first step and
system characterization from first step. In
security providing, rule base system will
consider about the level acceptance from
concerning party on the providing of
mLearning security which run on social
network channel. Then, if concerning party
can accept the security solution providing,
this model will transfer the solution to
assessment for vulnerability point analysis
and keep in database. In contrast, if
concerning party reject this checking, rule
base system will create mLearning security
requirement that necessary with m-Learning
system on social network for input to
vulnerability point database.
In this real case study, vulnerability
points including with lecturer, student and
network technician of NCU including with
concerning party that are ISP, wireless
communication provider and social network
provider. The weak points are concerning
parties that are stake holder who operated the
data exchange between sub and main campus
via mobile social network. In second
component, concerning party is collected
about attack motivation that bombard in each
characteristic of NCU mLearning system on
social network. Therefore, concerning party
must inform the characteristic of mLearning
system that rely on social network in order to
identify attack motivation which will be
transformed to threat identification database.
From second step that is run three
activity on parallel operation, the forth step
make rule base system for solution analysis
which pull solution data from security
solution store and vulnerability point that
rely on security solution. Then this section
will sent the analysis result into likelihood
determination process that survey the
solution with vulnerability point and threat in
order to analysis likelihood determination to
likelihood level which is transfer to impact
analysis step. Yet, the impact analysis not
require only the likelihood level, it is also
require the system characteristic for analysis
the impact level.
Next step, impact level will be used for
identify the risk level that deploy the security
recommendation which appropriate with
NCU mLearning on social network channel.
Moreover, this process will transform the
recommendation into the security solution
and policy report that display to IT manager
at NCU. In additional, this detail can keep in
solution store in order to employ in risk
analysis again.
Therefore, this mLearning security rule
base system on social network that make
NCU model to case study can be employ for
guide other university who tries to expand
the sub campus to other area and intend to
setup the m-Learning on social network
channel. They can use this model for
decency to construct the security system that
suitable
with
system
characteristic
themselves.
III. CONCLUSION
There are many respects regarding to the
rule base security model that is employs for
the finding the security control which
appropriate with each characteristic of
university where rely mobility device for
operated virtual class room on social
network in order to combination between sub
and main campus. For concentrated in real
case study, this review focuses on NorthChiang Mai University that useful on social
network on m-Learning system for make
high standard of education at Nong Khai
international campus that equal to main
campus at Chiang Mai province. The
similarly to other universities, NCU faces
with threat and problem on various social
network types. Therefore, this paper intend
to consider connecting with social network
including with facebook, google+ and twitter
that set up on smart phone device in order to
comparative
the
features
that
are
vulnerability point of mLearning system.
Moreover, this document apply the NIST
Special Issue of the International Journal of the Computer, the Internet and Management, Vol. 19 No. SP2, February, 2012
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The mLearning Security Rule Base System with Social Network on eCampus: A Case Study of North-Chiang Mai University
standard 800-30 that is employ for construct
the security rule base system under risk
management concept. This model operated
by filtering vulnerability point, threat and
problem, attack motivation, likelihood level,
level of impact and control analysis on
mobility system for analysis the risk level.
This level can be useable to identify the
security solution and policy that suitable
with university who make eClassroom which
join between sub and main campus under
mobility environment including with social
network feature. This rule base model can be
employed for drive the security system on mLearning that encompass with social network
application. In additional, this guideline can
ease up to other analysis model later.
REFERENCES
[1] Law of educational ministry. “Education
management outside main campus of private
university 2008” Office of the higher education
commission, 2008.
[2] Gary Stoneburner, Alice Goguen and Alexis
Feringa.
“Risk
management
guide
for
information technology system” National
institute of standard and technology, Technology
administration, US. Department of commerce,
2002.
[3] Marsella Yeanette Hatane and Henny Putri
Saking Wijaya. “The Impacts and Efficacy of
Social Networks as Part of eLearning in English
Department, Petra Christian University”. The
Seventh International Conference on eLearning
for Knowledge-Based Society, 2010.
[4] Ion MIERLUS – MAZILU. “mLearning
objective” The Sixth International Conference on
eLearning for Knowledge-Based Society, 2009.
[5] Aaron Beach, Mike Gartrell, and Richard Han.
“Solutions to Security and Privacy Issues in
Mobile Social Networking” International
Conference on Computational Science and
Engineering, 2009.
[6] Endarnoto, S.K.; Pradipta, S.; Nugroho, A.S.;
Purnama, J. “Traffic Condition Information
Extraction & Visualization from Social Media
Twitter for Android Mobile Application”.
International
Conference
on
Electrical
Engineering and Informatics (ICEEI), 2011.
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