Quantifying Security Threats for E-learning Systems

Abstract

As the reach of the internet expands to cover ever broader aspects of our economic and social welfare, cyber security is emerging as a major concern for researchers and practitioners, dealing as it does with privacy, confidentiality, user authentication, etc. E-learning systems epitomize computing systems and networks of the internet generation, since they involve multiple stakeholders, geographically distributed resources and data, and special requirements for confidentiality, authentication, and privacy. In this paper, we discuss the application of a cyber security metric to E-learning systems, in light of their standard architecture, their well-defined classes of stakeholders, and their specific security requirements. I. SECURITY ISSUES IN E-LEARNING : A LITTERATURE REVIEW E-learning concept is the use of technology to deliver information for training. This modern education is useful and interesting as it creates interactions between learners and instructors, or learners and learners regardless of time and space [2]. Also, it is an educational system where the instructor and the learner are at distance, collaborate and communicate using the technology. E-learning is the delivery of a learning, training or education program by electronic means as it involves the use of a computer or electronic device in some way to provide training, educational or learning material [3]. Nowadays, E-learning has become a popular way of learning for schools and businesses, it has increased exponentially in recent years [4]. The E-learning has gone through a spectacular development during the past years. In today's internet age, education requires the share and the distribution of information. We need a system or a platform, and then we call this an E-learning system or distance learning system or the E-learning platform which supports the online and / or the live and / or the blended learning processes. When they support only live learning process they can be an electronic support for course.

Full text

Quantifying Security Threats for E-learning Systems
Latifa Ben Arfa Rabai, Neila Rjaibi
Department of computer science
ISG
Tunis, Tunisia
latifa.rabai@gmail.com, rjaibi_neila@yahoo.fr
Anis Ben Aissa
Department of computer science
ENIT
Tunis, Tunisia
anis_enit@yahoo.fr
Abstract—As the reach of the internet expands to cover ever
broader aspects of our economic and social welfare, cyber
security is emerging as a major concern for researchers and
practitioners, dealing as it does with privacy, confidentiality, user
authentication, etc. E-learning systems epitomize computing
systems and networks of the internet generation, since they
involve multiple stakeholders, geographically distributed
resources and data, and special requirements for confidentiality,
authentication, and privacy. In this paper, we discuss the
application of a cyber security metric to E-learning systems, in
light of their standard architecture, their well-defined classes of
stakeholders, and their specific security requirements.
Keywords- Risk management; information security; e-
learning; threats analysis; mean failure cost; quantification.
I. SECURITY ISSUES IN E-LEARNING : A LITTERATURE
REVIEW
E-learning concept is the use of technology to deliver
information for training. This modern education is useful and
interesting as it creates interactions between learners and
instructors, or learners and learners regardless of time and
space [2]. Also, it is an educational system where the instructor
and the learner are at distance, collaborate and communicate
using the technology. E-learning is the delivery of a learning,
training or education program by electronic means as it
involves the use of a computer or electronic device in some
way to provide training, educational or learning material [3].
Nowadays, E-learning has become a popular way of learning
for schools and businesses, it has increased exponentially in
recent years [4].
The E-learning has gone through a spectacular development
during the past years. In today's internet age, education requires
the share and the distribution of information. We need a system
or a platform, and then we call this an E-learning system or
distance learning system or the E-learning platform which
supports the online and / or the live and / or the blended
learning processes. When they support only live learning
process they can be an electronic support for course.
A variety of E-learning systems are widespread, the number
of commercial E-learning is more than 250 sources and 45 of
them are Open Source Software (OSS) [5].These standard
systems support either a partially or completely the on line
education. We cite WebCT (1997) [6], Ilias (1997), Blackboard
(1997) [7], Claroline (2000), Moodle (2002) [5, 8] and SAKAI
(2004) as the most used E-learning systems [5, 6, 9 and 10].
Moodle is popular and recommended among the variety of
open source free product of the market, the teacher can produce
high quality on-line courses and he/she is well assisted by its
rich documentation and support.
E-learning system is complex as it guarantees the
satisfaction of the learner and the good image of the learning
process. Fundamental assessment dimensions are discussed,
they form the content, the human resources and the learning
platform which covers network equipments and security. Other
external dimensions cover financial, culture, policy and
standards. This aspect is essential to make E-learning system
successful. By the openness, the heterogeneity and the
widespread of an E-learning system, dangerous threats increase
and security issues become an important challenge to guarantee
a safe environment. It is of our interest to focus on the security
of E-learning platform in order to study its integrity,
confidentiality and availability. In consequence having a stable
platform without technical problems leads to have a learning
process with higher quality [11, 22], an important increase in
adequate cash, profitability and commercial image.
E-learning systems are large, dynamic with a variety of
users and resources. The top three types of security attacks
according to a security survey are: insider abuses of network
access, viruses and laptop/mobile device theft [12]. The focus
reclines on vulnerabilities and risks specific to e-learning, all
the components of E-learning system such as web services,
server computer systems, client computer systems, database
systems can be threatened. Possible vulnerabilities that may
affect the security of the online teaching learning system are
summarized as follows [13]:
• DDOS (Distributed Denial of Service): the attacker
tries to lock the server using a high-speed connection,
it jams the network card, or blocks the legit traffic.
• Search-SPAM: similar to the DDOS attack, a
hacker may submit a lot of “dummy” searches
using our internal search engine, using two or three
letter words with high frequency (such as
“of”,”for”,”and”,”in” etc) The result pages being a
lot, these searches consume the most CPU time, both
by Apache web service, PHP page generator and the
MySQL database server .
• Key loggers may be installed by students who can steal
teachers’ passwords and modify their own grades.
978-1-4673-2225-6/12/$31.00 ©2012 IEEE
2012 International Conference on Education and e-Learning Innovations

Mohd Alwi et al.[14] present issues related to the security
of E-learning environment which are legal and ethical issues,
piracy and the accessibility, security with the learning
platforms and technologies, authentication of students and
copyright and ownership of institution material
Organizations are exponentially threatened; security is a
current issue for them. Some statistics show that organizations
are currently investing on security resources. Through 2005,
the total global revenue for security products and service
vendors amounted to $21.1 billion, from 1999 to 2000, the
number of organizations spending more than $1 million
annually on security nearly doubled, it represents 12% of all
organizations in 1999 to 23% in 2000 [15]. Organizations are
obliged to put emphasis on security risk management in order
to measure and assess security risk and provide a good plan for
risk mitigation.
One very important question that may be asked in security
management is: why should we quantify security threats? It is
clear that by quantifying variables, meaningful indication about
risk assessment and good business decision makers are
provided. Furthermore Mohd Alwi et al. [16] also suggest that
security information management is useful in increasing
competition, adequate cash, profitability and commercial
image. Results of analysis security threats may also be useful in
a practical plan to provide us pertinent information in order to
implement a secure environment.
This paper is organized as follows. In section 2, we review
related research on security risk management approaches in
order to give a proper context to our work. In section 3, we
present the metric for cyber security. In sections 4 and 5 we
discuss how this metric can be specialized to E-learning
systems in light of specific attributes of such systems, such as:
their standard architecture, their standard deployment over the
internet infrastructure, their typical stakeholders, and their
specific security requirements. Finally, in section 6 we
conclude by summarizing our results, highlighting strength of
the cyber security measure and sketching directions of further
research.
II. E-LEARNING SECURITY RISK MANAGEMENT
E-learning shares similar characteristics with other e-
services according to Mohd Alwi et al. [16], there are three
main characteristics which are: the accessibility of service via
internet, the consumption of service by a person via internet
and the payment of a service by the consumer. Therefore,
management security approaches to quantify security threats in
E-learning are common with other e-services. However, some
particularities are noted according to Nickolova et al. [17], we
found in E-learning system:
• A variety of users, multiple applications and
information to download and upload.
• An important communication between the computer
users and E-learning portal
• A dynamic nature of the E-learning system
• A complex architecture.
In the first step it is necessary to define the terms ‘risk’ and
‘threat’ in order to emphasize on their different features.
According to Bruce Schneier [18] a threat is defined as: “a
potential way an attacker can attack a system”. Commonly
known, threats for computers are viruses, network penetrations,
theft and unauthorized modification of data, eavesdropping,
and non-availability of servers. A threat is also defined as a
category of object, person or other entities that present a danger
like spam, Trojan horse and fishing [19, 20].
A risk is the product of the probability that a particular
threat will occur and the expected loss. According to Bruce
Schneier [18], when we talk about risk, it is the likelihood of
the threat and the seriousness of its successful attack. For
example a threat is more serious because it is more likely to
occur. The risk of security threat as a quantitative measure is a
suitable input to decision making [21]. Therefore, the purpose
of considering risk as a financial measure leads to making
decision from business perspective. For example, the return on
security investment: ROI measure [22, 23] and the mean failure
cost (MFC) measure presented in [22, 24].
It is of our need to adopt a security risk management
process to determine the worthiest attack and the ignored one,
it is one way to focus on the serious attacks, to better manage
the budget and find the best way to use it [18, 21]. In a
quantitative security risk management there are two input
variables that needed to be fixed but they are difficult in the
priori phase: the probability that a threat may occur and the loss
suffered from a successful attack [22].
E-learning security management is a hot topic which
coincides with the development and the use of E-learning by
schools and businesses throughout the world. Much research
has been conducted in this perspective but we noted a lack in
quantitative approaches. Recently, the strength of Mohd Alwi
et al. model resides in presenting a full recent qualitative model
depending on vulnerabilities categories, threats, the 22 system
applications, whereas the second which is Nickolova et al.
qualitative model only depends on threats [17, 16].
III. MEAN FAILURE COST: A MEASURE OF CYBER-
SECURITY
In [1], Ben Aissa et al. introduce the concept of Mean
Failure cost as a measure of dependability in general, and a
measure of cyber security in particular. To compute the values
of the mean failure cost for each stakeholder, we need to fill 3
matrixes and a vector as follow:
A. Stakes Matrix (ST)
We consider a system S and we let H1, H2, H3,…Hk, be
stakeholders of the system, i.e. parties that have a stake in its
operation. We let R1, R2, R3,…Rn, be security requirements
that we wish to impose on the system, and we let STi,j, for
1≤i≤k and 1≤j≤n be the stake that stakeholder Hi has in
meeting security requirement Rj.

B. Dependency Matrix (DP)
We consider the architecture of system S, and let C1, C2,
C3,…Ch, be the components of system S. Whether a particular
security requirement is met or not may conceivably depend on
which component of the system architecture is operational. If
we assume that no more than one component of the
architecture may fail at any time, and define the following
events:
• Ei, 1≤i≤h, is the event: the operation of component Ci
is affected due to a security breakdown.
• Em+1: No component is affected.
Given a set of complementary events E1, E2, E3,… Eh, Eh+1,
we know that the probability of an event F can be written in
terms of conditional probabilities as:
1
1
() ( | ) ( ).
h
kk
k
P
FPFEPE
+
=
=×
∑ (1)
We instantiate this formula with F being the event: the
system fails with respect to some security requirement. To this
effect, we let Fj denote the event that the system fails with
respect to requirement Rj and we write (given that the
probability of failure with respect to Rj is denoted by PRj:
1
1
(|) ().
m
jjkk
k
P
RPFEPE
+
=
=×
∑
(2)
C. Impact Matrix (IM)
Components of the architecture may fails to operate
properly as a result of security breakdowns brought about by
malicious activity. In order to continue the analysis, we must
specify the catalog of threats that we are dealing with, in the
same way that analysts of a system’s reliability define a fault
model. To this effect, we catalog the set of security threats that
we are facing, and we let T1, T2, T3, … Tp, represent the
event that a cataloged threat has materialized, and we let Tp+1,
be the event that no threat has materialized. Also, we let PT
be the vector of size p+1 such that:
• PTq, for 1≤q≤p, is the probability that threat Tq has
materialized during a unitary period of operation (say,
1 hour).
• PTp+1 is the probability that no threat has materialized
during a unitary period of operation time.
1
!
(|)
p
kkqq
q
P
EPETPT
+
=
=×
∑(3)
• We introduce the Impact (IM) matrix, which has h + 1
rows and p + 1 columns, and where the entry at row k
and column q is the probability that component Ck fails
given that threat q has materialized (or, for q = p + 1,
that no threat has materialized),
• We introduce vector PT of size p + 1, such that PTq is
the probability of event Tq, then we can write :
P
EIMPT=D (4)
Matrix IM can be derived by analyzing which threats affect
which components, and assessing the likelihood of success of
each threat, in light of perpetrator behavior and possible
counter-measures. Vector PT can be derived from known
perpetrator behavior, perpetrator models, known system
vulnerabilities, etc. We refer to this vector as the Threat
Configuration Vector or simply as the Threat Vector.
D. Summary of MFC formula
Given the stakes matrix ST, the dependency matrix DP, the
impact matrix IM and the threat vector PT, we can derive the
vector of mean failure costs (one entry per stakeholder) by the
following formula: MFC = ST ◦ DP ◦ IM ◦ PT (5)
Where matrix ST is derived collectively by the
stakeholders, matrix DP is derived by the systems architect,
matrix IM is derived by the security analyst from architectural
information, and vector PT is derived by the security analyst
from perpetrator models.
IV. ILLUSTRATION: AN E-LEARNING APPLICATION
A. List of stakeholders
E-learning system as a popular online learning environment
adapts a variety of stakeholders. The list of the needed actors
includes the system administrator, the teacher, the student and
the technician [10, 11, 25 and 26].
B. E learning system architecture
The Online environment involves several dimensions in
their architecture in order to support the various needs of
stakeholders. The architecture is the integration of several
technological components. According to [10] they are not a
unique architecture for E-learning system. Consequently, there
is no independent architecture, but we recognize for MOODLE
and WebCT the two popular and well known E-learning
systems that actors are common like teacher, student,
knowledge manager and administrator. Also, architectural
components are common like browser, database server and
web server.
Based on the architecture diagram presented by Selvi et al.
[27], we recognize six architectural components which are:
• The browser as the client user interface [27],
• The Web server which hosts the Content Management
System (CMS) Applications for managing students and
their academic and financial situations [25, 27],
• The application server which incorporates the E-
learning platform; the request sent by the web server is
forwarded to the application server; therefore the
database concentrates on the storage, retrieval and
analysis of data. It hosts online courses and is
considered as the web server application programming

interface which forms a standard web browser related
to the organization [25, 27].
• The database server: is the core database and some
extension tables of the E-learning system [27],
• The firewall server secures internet input and output
traffic and filters high-risk codes, such as viruses [25],
• The mail server covers email application and user’s
mail boxes [25].
C. List of requirements
E-learning systems share similar security requirements with
other e-services related to the accessibility of service via
internet, the consumption of service by a person via internet
and the payment of a service by the consumer [16, 17]. The
basic security requirements are classified into six aspects [28]:
• Authentication: is required to identify the application
user of the platform and to give him the right to access
to the application with his own account [25].
• Confidentiality: is required to ensure that data and
resources available on the platform are accessible only
by those with right of access [5].
• Integrity: is required to ensure that the information like
data and resources are available on the platform and
can be modified only by authorized entities [28].
• Availability: is a very important subject, it is required
to ensure that the web application is always available
and operational when the user needs it [5, 28].
• Non-repudiation: is needed to ensure that no party in
an operation can deny participating in the operation.
We can also define the mechanism of non-repudiation
as the mechanism that ensures that the sender of the
message can’t deny having sent the message in the
future [28].
• Privacy: is necessary to ensure non-
disclosure of information [28].
D. List of threats
E-Learning systems allow multiple users or applications to
download, upload and exchange distributed information.
Communication issues between end-users’ computers and E-
learning site in these systems are very important, as the systems
are defined by widely dispersed elements in terms of network
topology and physical geography. Additionally, the systems
often allow many-to-many communication which provides
powerful capabilities and allows many systems nodes to have
the same communication at any given time. As noted in [16] a
system can be attacked by a lot of threats that we can
summarize the most important as follows:
• Viruses (VS),
• Denial of service (DoS),
• Acts of human error or failure like accidents (AH),
• Unauthorized access and/or data collection (DST),
• Deliberate acts of sabotage or vandalism (destruction
of information or system) (DSV),
• Deliberate acts of theft (illegal confiscation of
equipment or information) (TH),
• Compromises to intellectual property (piracy,
copyright, infringement) (CIP),
• Quality of Service deviations (QoS),
• Blackmail for information disclosure (BID).
V. COMPUTING MEAN FAILURE COST FOR E-
LEARNING SYSTEM
A. The stakes matrix (ST)
Each row of the matrix presented in Table I below is filled
by relevant stakeholders who have internal or external usage
for the platform, each cell expressed in dollars monetary terms
and it represents loss incurred and/or premium placed on
requirement. To fill ST Matrix we did a survey for EVT.
ST (Hi, Rj): Is the stake that stakeholders Hi has in meeting
requirement Rj.
B. The dependency matrix (DP)
Each row of the matrix presented in Table II below is filled
by system architects; each cell represents probability of failure
with respect to a requirement given that a component has
failed. DP (Rj, Ck): is the probability that the system fails to
meet requirement Rj if component Ck is compromise. To fill
this matrix we have used the values from [29].
ST Matrix Security Requirements
Stakeholders Confidentiality Integrity Availability Non-repudiation Authentication Privacy
Administrator 40 30 60 10 10 50
Teacher 20 20 60 20 30 40
Student 0 5 5 0 5 0
Technician 10 7 15 5 5 15
TABLE I: THE STAKES MATRIX (ST)

C. The impact matrix (IM)
Each row of the matrix presented in Table III is filled by
V&V Team; each cell represents probability of compromising
a component given that a threat has materialized, it depends on
the target of each threat, and likelihood of success of the threat.
To fill this matrix we have used the values from [29]. IM (Ck,
Th): is the probability that Component Ck is compromised if
Threat Th has materialized.
D. The threat vector (PT)
Each row of the vector presented in Table IV is filled by
security team; each cell represents probability of realization of
each threat, it depends on perpetrator models, empirical data,
known vulnerabilities, known counter-measures. PT (Ti): The
probability that threat Ti materialized for a unit of operation
time (one hour of operation). Using this data, we can now
compute the vector of MFC.
Table V. presents the MFC for each stakeholder, therefore
the system administrator stand to lose 0.785 $/ hour if the
system is threatened, also the teacher lose about 0.743 $/ hours.
For student and technician it can appear insignificant but for a
failure to long-term they are significant.
VI. CONCLUSION
As distributed systems, E-learning systems epitomize the
security concerns that such systems raise, including: Privacy of
student and teacher personal records, Confidentiality
(protection from exposure) and integrity (protection from
alteration) of student performance records and transcripts,
authentication and access rights to course materials, grade
records, etc. These systems present a relatively uniform
architecture, and a common set of stakeholders as such these
systems are prime candidates for the MFC as a measure of
cyber security, which offers the following attributes:
DP Matrix Components
Requirements Browser Web server Application server DB
server
Firewall server Mail server No failure
Confidentiality 0.2 0.333 0.333 0.5 1.0 0.333 0.0
Integrity 0.2 0.333 0.333 0.0 1.0 0.333 0.0
Availability 1 0.333 0.333 0.0 1.0 0.333 0.0
Non-repudiation 0.2 0.333 0.333 0.0 1.0 0.333 0.0
Authentication 0.2 0.333 0.333 0.5 1.0 0.333 0.0
Privacy 0.2 0.333 0.333 0.5 1.0 0.333 0.0
TABLE II: THE DEPENDENCY MATRIX (DP)
TABLE III: THE IMPACT MATRIX (IM)
IM Matrix Threats
Components VS DoS AH DST DSV TH CIP QOS DIE No Threats
Browser 0.004 0.005 0.100 0 0 0.300 0 0.200 0.200 0
Web Server 0.004 0.001 0 0 0 0 0.001 0.500 0 0
Application server 0.054 0.010 0.030 0.200 0.200 0.300 0.001 0.400 0 0
Database server 0.054 0.010 0.030 0.200 0.200 0.300 0.030 0.400 0 0
Firewall server 0.010 0.050 0.010 0 0 0.01 0 0.010 0 0
Mail server 0.054 0.010 0.030 0.200 0.200 0.300 0 0.400 0.400 0
No Failure 0.600 0.700 0.500 0.600 0.500 0.300 0.300 0.300 0.700 1
TABLE IV: THE VECTOR OF PROBABILITY (PT)
TABLE V: THE MFC FOR E-LEARIN G SYSTEM
Stakeholders Mean Failure Cost $ /hour
System administrator 0.785
Teacher 0.743
Student 0.056
Technician 0.223
Threats Probability/hour
VS 5.04 10-3
DoS 3.08 10-3
AH 0.1 10-3
DST 0.42 10-3
DSV 2.31 10-3
TH 2.5 10-3
CIP 0.7 10-3
QOS 2.5 10-3
BID 1.4 10-3
No Threats 0,9819

• MFC varies by stakeholders: The mean failure cost is
not a characteristic of the system but rather depends on
the system and the stakeholder/ user of the system.
• MFC varies by stakes: the same stakeholder may have
different stakes in meeting different security
requirements.
• MFC is cognizant of the system architecture: The
mean failure cost is calculated by estimating the
probability of failure of each component of the system,
and the probability that failure of each component may
affect each security requirement.
• MFC is cognizant of the threat configuration: The
mean failure cost is calculated by cataloging the list of
threats that the system is vulnerable to, the probability
that each one of these threats may materialize within a
unitary operation time, and the probability that each
threat, if it materializes, will affect each component of
the architecture.
• MFC is quantified in economic terms: The mean
failure cost is computed as a monetary value per unit of
operational time, and measure the amount of risk that
each stakeholder is incurring as a result of security
threats and system vulnerabilities. As such, it provides
adequate support for quantitative decision-making.
We envision to broaden the application of MFC to the
analysis of the security attributes of E-learning systems, by
refining the catalog of threats, collecting empirical information
that help us better estimate the matrices that are needed to
compute MFC, and explore more opportunities for security
related decision-making using MFC.
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